**Cotton (***Gossypium hirsutum* **L.) Response to Pendimethalin Formulation, Timing, and Method of Application**

Timothy Grey and Theodore Webster

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/56184

### **1. Introduction**

The introduction of glyphosate-resistant cotton for production in the southeast United States changed herbicide application strategies and increased the profitability of no-tillage and striptillage techniques. Glyphosate (*N*-[phosphonomethyl]-glycine) is a highly effective herbicide that controls a broad spectrum of annual and perennial grass and broadleaf weeds in cotton [3, 37]. When glyphosate-resistant cotton varieties were first introduced, glyphosate was applied two to four times on most fields and may have been the only herbicide used [4, 5]. In Georgia, 93% of the cotton acres received at least one glyphosate application in 2005 [3]. The technology allowed growers to reduce or eliminate soil-applied herbicides, allowing them to abandon cultivation and make the transition to conservation tillage, which promotes soil conservation and compliance with USDA Federal regulations. Greater than 50% of Georgia cotton was produced using no-tillage or strip-tillage techniques in 2007, a strategy that has been affected by glyphosate weed control [1, 11].

### **2. Importance**

With the elimination of cultivation as a control tactic in conservation tillage systems, herbicides were the primary and often only method used for weed control [24]. However, the incidence of herbicide-tolerant or resistant weeds emerging in the southeast United States [33, 34] has increased the need for multiple herbicide modes of action in both conservation tillage and conventional tillage weed management systems [3, 5, 16]. In Georgia, there are populations of Palmer amaranth (*Amaranthus palmeri* S. Wats.) (Figure 1) with resistance to glyphosate, ALS,

© 2013 Grey and Webster; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Grey and Webster; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

triazines, dinitroanilines, with some populations demonstrating resistance to multiple mechanisms of action [5, 26, 31, 38]. While glyphosate- and ALS-resistant Palmer amaranth is widespread in Georgia, the frequency and distribution of triazine- and dinitroaniline-resistant has not been characterized in Georgia. With the potential mobility of herbicide resistance traits, through movement of pollen [27, 28] or seed [18] and/or potentially high levels of naturally occurring mutations conferring resistance, cotton production in the region is threatened by herbicide resistant weeds.

**3. Background information on soil applied herbicides**

with preemergence applications either sprayed or impregnated on fertilizers.

Pendimethalin is a member of the dinitroanaline family of herbicides. Pendimethalin prevents plant cell growth by inhibiting spindle formation during cell division [6]. Pendimethalin is applied PRE to the soil surface, with or without incorporation into the soil, to approximately 37% of Georgia cotton [17] for control of grasses and small-seeded broadleaf weed species [2]. Pendimethalin inhibits mitotic cell division in susceptible plants [30], while tolerant crops grow through, or are planted below, the treated zone [13, 14]. Among the dinitroanaline herbicides, pendimethalin has greater water solubility of 0.275 *u*g mL-1 and less volatility at 9.4 x 10-6 mm Hg at 25 C [22], allowing it to be applied to the soil surface rather than needing mechanical incorporation [35, 36]. However, pendimethalin still requires moisture in the form of rainfall or irrigation in order to move it into the active zone of weed germination. Cotton selectivity of pendimethalin pre-emergence is due to differences in metabolism and sequestration of pendimethalin in the lysigenous glands [25]. Pendimethalin is registered for PRE application up to 2 days after cotton planting. However, delayed application in combination with excessive moisture (rainfall or irrigation) can result in injury to seedling cotton. Pendimethalin injury to

**3.1. Pendimethalin**

Herbicides with soil persistence and weed control activity were extensively used for preemergence weed control in cotton until the commercial release of herbicide-resistant cotton in 1997. Cotton herbicides with soil residual properties included cyanazine (2-((4-chloro-6- (ethylamino)-1,3,5-triazin-2-yl]amino]-2-methylpropanenitrile), diuron (*N*'-(3,4-dichloro‐ phenyl)-*N,N*-dimethylurea), flumeturon (*N,N*-dimethyl-*N'*(3-(trifluoromethyl)phenyl]urea), pendimethalin (N-(1-ethylpropyl)-3,4-dimethyl-2,6-dinitrobenzenamine), trifluralin (2,6 dinitro-N,N-dipropyl-4-(trifluoromethyl(benzenamine), and others. Pendimethalin was registered for cotton in 1975 [22]. These herbicides were applied pre-plant soil incorporated (PPI), pre-emergence (before cotton and weed emergence) and/or post-directed (where applications are directed to the soil and bottom portion of the stems of mature cotton plants). Cotton in the southeastern U.S. has a growing season that can extend to over 150 days ranging from late March to early November. Growers can PRE apply pendimethalin but have to PPI trifluralin. This allows conservation tillage cotton growers an option to use a dinitroaniline herbicide for grass and small seeded broadleaf weed control. A weakness in weed efficacy of these residual herbicides was the lack of extended weed control due to dissipation of the herbicide in the soil. With the introduction and high rate of adoption of glyphosate-resistant cotton varieties and almost exclusive use of glyphosate for weed control, the herbicides with soil residual activity was reduced in favor of total post-emergence weed control programs. The cotton registration for cyanazine was eventually canceled in 2002 in the United States. However, even with increased herbicide-resistant weeds in growers' fields in the first decade of the 2000's, diruon, flumeturon, and pendimethalin use did not increase, even though residual herbicides could improve weed control (Figure 2). Diuron and flumeturon are widely applied to cotton as post-directed sprays in this region. However, growers using conservation tillage practices in cotton often rely on pendimethalin for early season residual weed control

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

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**Figure 1.** Glyphosate resistant Palmer amaranth in conventional upland cotton in Georgia.

The increased occurrence of herbicide-resistant weeds necessitates the search for alternative control tactics. For instance, metolachlor had not been traditionally used in cotton because of excessive crop injury when applied preemergence after planting. However, changing its use pattern to be applied after cotton emergence avoided crop injury, while controlling an exotic weed that had become troublesome [4]. This technology and new mechanism of action has been instrumental in current management of glyphosate-resistant Palmer amaranth. Research on a new use pattern for pendimethalin may provide an additional tool for weed management at different times in the growing season.

## **3. Background information on soil applied herbicides**

Herbicides with soil persistence and weed control activity were extensively used for preemergence weed control in cotton until the commercial release of herbicide-resistant cotton in 1997. Cotton herbicides with soil residual properties included cyanazine (2-((4-chloro-6- (ethylamino)-1,3,5-triazin-2-yl]amino]-2-methylpropanenitrile), diuron (*N*'-(3,4-dichloro‐ phenyl)-*N,N*-dimethylurea), flumeturon (*N,N*-dimethyl-*N'*(3-(trifluoromethyl)phenyl]urea), pendimethalin (N-(1-ethylpropyl)-3,4-dimethyl-2,6-dinitrobenzenamine), trifluralin (2,6 dinitro-N,N-dipropyl-4-(trifluoromethyl(benzenamine), and others. Pendimethalin was registered for cotton in 1975 [22]. These herbicides were applied pre-plant soil incorporated (PPI), pre-emergence (before cotton and weed emergence) and/or post-directed (where applications are directed to the soil and bottom portion of the stems of mature cotton plants). Cotton in the southeastern U.S. has a growing season that can extend to over 150 days ranging from late March to early November. Growers can PRE apply pendimethalin but have to PPI trifluralin. This allows conservation tillage cotton growers an option to use a dinitroaniline herbicide for grass and small seeded broadleaf weed control. A weakness in weed efficacy of these residual herbicides was the lack of extended weed control due to dissipation of the herbicide in the soil. With the introduction and high rate of adoption of glyphosate-resistant cotton varieties and almost exclusive use of glyphosate for weed control, the herbicides with soil residual activity was reduced in favor of total post-emergence weed control programs. The cotton registration for cyanazine was eventually canceled in 2002 in the United States. However, even with increased herbicide-resistant weeds in growers' fields in the first decade of the 2000's, diruon, flumeturon, and pendimethalin use did not increase, even though residual herbicides could improve weed control (Figure 2). Diuron and flumeturon are widely applied to cotton as post-directed sprays in this region. However, growers using conservation tillage practices in cotton often rely on pendimethalin for early season residual weed control with preemergence applications either sprayed or impregnated on fertilizers.

#### **3.1. Pendimethalin**

triazines, dinitroanilines, with some populations demonstrating resistance to multiple mechanisms of action [5, 26, 31, 38]. While glyphosate- and ALS-resistant Palmer amaranth is widespread in Georgia, the frequency and distribution of triazine- and dinitroaniline-resistant has not been characterized in Georgia. With the potential mobility of herbicide resistance traits, through movement of pollen [27, 28] or seed [18] and/or potentially high levels of naturally occurring mutations conferring resistance, cotton production in the region is threatened by

**Figure 1.** Glyphosate resistant Palmer amaranth in conventional upland cotton in Georgia.

at different times in the growing season.

The increased occurrence of herbicide-resistant weeds necessitates the search for alternative control tactics. For instance, metolachlor had not been traditionally used in cotton because of excessive crop injury when applied preemergence after planting. However, changing its use pattern to be applied after cotton emergence avoided crop injury, while controlling an exotic weed that had become troublesome [4]. This technology and new mechanism of action has been instrumental in current management of glyphosate-resistant Palmer amaranth. Research on a new use pattern for pendimethalin may provide an additional tool for weed management

herbicide resistant weeds.

28 Herbicides - Current Research and Case Studies in Use

Pendimethalin is a member of the dinitroanaline family of herbicides. Pendimethalin prevents plant cell growth by inhibiting spindle formation during cell division [6]. Pendimethalin is applied PRE to the soil surface, with or without incorporation into the soil, to approximately 37% of Georgia cotton [17] for control of grasses and small-seeded broadleaf weed species [2]. Pendimethalin inhibits mitotic cell division in susceptible plants [30], while tolerant crops grow through, or are planted below, the treated zone [13, 14]. Among the dinitroanaline herbicides, pendimethalin has greater water solubility of 0.275 *u*g mL-1 and less volatility at 9.4 x 10-6 mm Hg at 25 C [22], allowing it to be applied to the soil surface rather than needing mechanical incorporation [35, 36]. However, pendimethalin still requires moisture in the form of rainfall or irrigation in order to move it into the active zone of weed germination. Cotton selectivity of pendimethalin pre-emergence is due to differences in metabolism and sequestration of pendimethalin in the lysigenous glands [25]. Pendimethalin is registered for PRE application up to 2 days after cotton planting. However, delayed application in combination with excessive moisture (rainfall or irrigation) can result in injury to seedling cotton. Pendimethalin injury to

formulated as a microencapsulated (ME) aqueous capsule suspension [12] (Figure 3). One potential method of obtaining extended weed control to apply pendimethalin as an in-season application, i.e. from emergence to when the cotton crop has up to six leaves, or just prior to canopy formation. However, injury to cotton from the EC formulation has prevented topical

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

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31

**Figure 3.** Pendimethalin microencapsulated aqueous capsule suspension (left) and pendimethalin emulsifiable con‐

Cotton response to pendimethalin ME applied at different growth stages is less injurious to cotton because of its formulation. An alternative method of application is to impregnate pendimethalin onto fertilizer for in-season application to extend residual weed control, reducing the number of herbicide applications [15, 20], and minimizing potential crop injury. Crop injury has been noted with pendimethalin EC and ME when applied topically to cotton at the 4th leaf growth stage [7] and its effects on cotton nutrient uptake [10]. Weed control for comparing pendimethalin EC to ME in cotton have been made using spray applications [11]. Florida pusley and Texas millet control were similar and consistent for PRE applied EC and ME formulations (Table 1). While weed control has been evaluated, cotton crop response to

applications in the past.

(Photo courtesy Sidney Cromer, University of Georgia).

centrate (right)

**3.4. Research**

**Figure 2.** Residual cotton herbicides use as compared to glyphosate in United States cotton production since the ad‐ vent of glyphosate resistant cotton [17].

cotton seedlings results in delayed hypocotyl development and can also cause abnormal root growth. This injury is commonly associated with enlarged lower stems and 'bottle brush' root development. Microbial decomposition is the main method of pendimethalin dissipation [19, 32]. While pendimethalin has a reported soil half-life of 74 to 114 days [30], surface applied half-lives of 4 to 6 days can occur due to volatilization, photo-chemical, and other degradation processes [21]. Additionally, increased degradation can occur with no-tillage application [9].

#### **3.2. Pendimethalin weed control**

Pendimethalin is often used in cotton to supplement control of grass weeds and small-seeded broadleaf weed species. According to the University of Georgia Extension recommendations, pendimethalin provides excellent (90%) control of crabgrass (*Digitaria sanguinalis* (L.) Scop.), crowfootgrass (*Dactyloctenium aegyptium* (L.) Willd.), foxtails (*Setaria* species), goosegrass (*Eleusine indica* (L.) Gaertn.), seedling johnsongrass (*Sorghum halepense* (L.) Pers.), and sandbur (*Cenchrus echinatus* L.); good control (80-90%) of fall panicum (*Panicum dichotomiflorum* Michx.) and Texas millet (*Urochloa texana* (Buckl.) R. Webster). Pendimethalin also provides excellent (90%) to good (80-90%) control of the broadleaf species Florida pusley (*Richardia scabra* L.), pigweeds (*Amaranthus* species), lambsquarters (*Chenopodium album* L.), and pink purslane (*Portulaca pilosa* L.); and fair to good (60-90%) control of Palmer amaranth.

#### **3.3. Pendimethalin formulation**

There are two liquid formulations of pendimethalin registered for cotton in the United States. One contains 37.4% pendimethalin (0.41 kg ai/L) formulated with aromatic naphtha as an emulsifiable concentrate (EC), and the other contains 38.7% pendimethalin (0.47 kg ai/L) formulated as a microencapsulated (ME) aqueous capsule suspension [12] (Figure 3). One potential method of obtaining extended weed control to apply pendimethalin as an in-season application, i.e. from emergence to when the cotton crop has up to six leaves, or just prior to canopy formation. However, injury to cotton from the EC formulation has prevented topical applications in the past.

(Photo courtesy Sidney Cromer, University of Georgia).

**Figure 3.** Pendimethalin microencapsulated aqueous capsule suspension (left) and pendimethalin emulsifiable con‐ centrate (right)

#### **3.4. Research**

cotton seedlings results in delayed hypocotyl development and can also cause abnormal root growth. This injury is commonly associated with enlarged lower stems and 'bottle brush' root development. Microbial decomposition is the main method of pendimethalin dissipation [19, 32]. While pendimethalin has a reported soil half-life of 74 to 114 days [30], surface applied half-lives of 4 to 6 days can occur due to volatilization, photo-chemical, and other degradation processes [21]. Additionally, increased degradation can occur with no-tillage application [9].

**Figure 2.** Residual cotton herbicides use as compared to glyphosate in United States cotton production since the ad‐

**GLYPHOSATE CYANAZINE DIURON PENDIMETHALIN FLUMETURON TRIFLURALIN** 

**Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010**

Pendimethalin is often used in cotton to supplement control of grass weeds and small-seeded broadleaf weed species. According to the University of Georgia Extension recommendations, pendimethalin provides excellent (90%) control of crabgrass (*Digitaria sanguinalis* (L.) Scop.), crowfootgrass (*Dactyloctenium aegyptium* (L.) Willd.), foxtails (*Setaria* species), goosegrass (*Eleusine indica* (L.) Gaertn.), seedling johnsongrass (*Sorghum halepense* (L.) Pers.), and sandbur (*Cenchrus echinatus* L.); good control (80-90%) of fall panicum (*Panicum dichotomiflorum* Michx.) and Texas millet (*Urochloa texana* (Buckl.) R. Webster). Pendimethalin also provides excellent (90%) to good (80-90%) control of the broadleaf species Florida pusley (*Richardia scabra* L.), pigweeds (*Amaranthus* species), lambsquarters (*Chenopodium album* L.), and pink purslane

There are two liquid formulations of pendimethalin registered for cotton in the United States. One contains 37.4% pendimethalin (0.41 kg ai/L) formulated with aromatic naphtha as an emulsifiable concentrate (EC), and the other contains 38.7% pendimethalin (0.47 kg ai/L)

(*Portulaca pilosa* L.); and fair to good (60-90%) control of Palmer amaranth.

**3.2. Pendimethalin weed control**

vent of glyphosate resistant cotton [17].

30 Herbicides - Current Research and Case Studies in Use

**Kilograms (x 1000)**

**3.3. Pendimethalin formulation**

Cotton response to pendimethalin ME applied at different growth stages is less injurious to cotton because of its formulation. An alternative method of application is to impregnate pendimethalin onto fertilizer for in-season application to extend residual weed control, reducing the number of herbicide applications [15, 20], and minimizing potential crop injury. Crop injury has been noted with pendimethalin EC and ME when applied topically to cotton at the 4th leaf growth stage [7] and its effects on cotton nutrient uptake [10]. Weed control for comparing pendimethalin EC to ME in cotton have been made using spray applications [11]. Florida pusley and Texas millet control were similar and consistent for PRE applied EC and ME formulations (Table 1). While weed control has been evaluated, cotton crop response to applications made PRE up to the 6th leaf growth stage comparing season- long factors is also needed. Therefore, this chapter will emphasize pendimethalin use, formulation (EC and ME), and cotton response. Additionally, this chapter will focus on pendimethalin formulations when applied as an aqueous solution in water or impregnated on fertilizers [15].


**Figure 4.** Pendimethalin impregnated fertilizer treatment on soil surface (left) and application (right).

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

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33

**Figure 5.** Fertilizer prior to (left) and after (right) treatment with pendimethalin formulation Prowl 3.3EC.

described by using the exponential growth, Stirling Model.

All plots received the same fertilizer rates to ensure no variability for fertility. Plots were then irrigated the day after treatments were applied. Treatments were made at four different application timings, at planting prior to plant emergence (PRE), at seedling emergence (AE), to 3rd leaf, or to 6th leaf cotton. A non-treated control was included for comparison for a total of 17 treatments. All plots were maintained weed free by hand pulling weed escapes and treatments with glyphosate. Other cultural and pest management practices were based upon recommendations by the Georgia Cooperative Extension Service. Supplemental overhead sprinkler irrigation was applied as needed. Cotton injury ratings were evaluated after applications using a scale of 0 (no injury) to 100 % (plant death) [8]. Cotton height measures were made up to five times in 2005, 2006 and 2007. Both rows of each plot were harvested with a spindle picker, and seed cotton yield was quantified. Data were subjected to mixed model ANOVA using Proc Mixed in SAS 9.1, with random effects of years and replications. Mean separation was determined using the PDMIX800 macro. Regression analysis was performed using Sigmaplot 12 nonlinear regression. The intent was to determine if the response could be

a Abbreviations: EC, emulsifiable concentrate; ME, microencapsulated; PRE, prior to plant emergence.

**Table 1.** Weed control in Georgia cotton with pendimethalin ECa and MEa formulations applied at planting.

#### **4. Studies**

#### **4.1. Field studies**

Field trials were conducted in 2005, 2006, and 2007 at the University of Georgia Ponder Research Station near Ty Ty, Georgia. Soil was Tifton loamy sand (fine-loamy, kaolinitic, thermic Plinthic Kandiadults) with 83% sand, 12% silt, 5% clay, organic matter content of 1 to 1.8%, and pH of 5.6 to 6.1. Conventional tillage was used during all three years of the study to obtain optimal herbicide/soil contact, since pendimethalin has been observed to adsorb to cover crop residue [9]. Delta and Pineland 555 BG/RR was planted in 2005 and Delta and Pineland Flex 445 BG/RR in 2006 and 2007 using a Monosem precision vacuum planter set to deliver 14 seeds per linear meter of row with 0.9 m between row centers. The experimental design was a two factor randomized complete block with treat‐ ments replicated four times. Plots were 1.8 m (two rows) wide by 8 m long. Four differ‐ ent methods of pendimethalin application were made at four different timings during the growing season. All herbicide treatments consisted of 1.1 kg active ingredient/ha of pen‐ dimethalin EC or ME. Only the method or time of application varied. Treatments were pendimethalin EC or ME applied as either an aqueous solution in water, or impregnated on fertilizer (10-10-10) that was applied at 280 kg ha-1 with a Gandy fertilizer applicator (Figure 4). All herbicide spray treatments were made with a CO2-pressurized backpack sprayer using Teejet 11002 flat fan nozzles, which delivered 140 L/ha of water at 130 kPa. For the fertilizer treatment, pendimethalin EC or ME at 1.1 kg active ingredient ha-1 was impregnated on fertilizer using a CO2–pressurized sprayer with a Teejet 8002 flat fan noz‐ zle at 130 kPa. Fertilizer was rotated at a constant speed of 12 meter minute-1 using a ro‐ tating steel drum. The drum freely rotated on a twin roller rod system set at a 30º angle, powered by an electric motor, with speed adjusted by a rheostat (Figure 5).

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application http://dx.doi.org/10.5772/56184 33

**Figure 4.** Pendimethalin impregnated fertilizer treatment on soil surface (left) and application (right).

applications made PRE up to the 6th leaf growth stage comparing season- long factors is also needed. Therefore, this chapter will emphasize pendimethalin use, formulation (EC and ME), and cotton response. Additionally, this chapter will focus on pendimethalin formulations

when applied as an aqueous solution in water or impregnated on fertilizers [15].

**Formulation Application method Timing Texas millet Florida pusley**

Pendimethalin EC Spray PRE 75 66 Pendimethalin ME Spray PRE 75 68

Abbreviations: EC, emulsifiable concentrate; ME, microencapsulated; PRE, prior to plant emergence.

Field trials were conducted in 2005, 2006, and 2007 at the University of Georgia Ponder Research Station near Ty Ty, Georgia. Soil was Tifton loamy sand (fine-loamy, kaolinitic, thermic Plinthic Kandiadults) with 83% sand, 12% silt, 5% clay, organic matter content of 1 to 1.8%, and pH of 5.6 to 6.1. Conventional tillage was used during all three years of the study to obtain optimal herbicide/soil contact, since pendimethalin has been observed to adsorb to cover crop residue [9]. Delta and Pineland 555 BG/RR was planted in 2005 and Delta and Pineland Flex 445 BG/RR in 2006 and 2007 using a Monosem precision vacuum planter set to deliver 14 seeds per linear meter of row with 0.9 m between row centers. The experimental design was a two factor randomized complete block with treat‐ ments replicated four times. Plots were 1.8 m (two rows) wide by 8 m long. Four differ‐ ent methods of pendimethalin application were made at four different timings during the growing season. All herbicide treatments consisted of 1.1 kg active ingredient/ha of pen‐ dimethalin EC or ME. Only the method or time of application varied. Treatments were pendimethalin EC or ME applied as either an aqueous solution in water, or impregnated on fertilizer (10-10-10) that was applied at 280 kg ha-1 with a Gandy fertilizer applicator (Figure 4). All herbicide spray treatments were made with a CO2-pressurized backpack sprayer using Teejet 11002 flat fan nozzles, which delivered 140 L/ha of water at 130 kPa. For the fertilizer treatment, pendimethalin EC or ME at 1.1 kg active ingredient ha-1 was impregnated on fertilizer using a CO2–pressurized sprayer with a Teejet 8002 flat fan noz‐ zle at 130 kPa. Fertilizer was rotated at a constant speed of 12 meter minute-1 using a ro‐ tating steel drum. The drum freely rotated on a twin roller rod system set at a 30º angle,

powered by an electric motor, with speed adjusted by a rheostat (Figure 5).

and MEa

**Table 1.** Weed control in Georgia cotton with pendimethalin ECa

32 Herbicides - Current Research and Case Studies in Use

a

**4. Studies**

**4.1. Field studies**

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_%\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

formulations applied at planting.

**Figure 5.** Fertilizer prior to (left) and after (right) treatment with pendimethalin formulation Prowl 3.3EC.

All plots received the same fertilizer rates to ensure no variability for fertility. Plots were then irrigated the day after treatments were applied. Treatments were made at four different application timings, at planting prior to plant emergence (PRE), at seedling emergence (AE), to 3rd leaf, or to 6th leaf cotton. A non-treated control was included for comparison for a total of 17 treatments. All plots were maintained weed free by hand pulling weed escapes and treatments with glyphosate. Other cultural and pest management practices were based upon recommendations by the Georgia Cooperative Extension Service. Supplemental overhead sprinkler irrigation was applied as needed. Cotton injury ratings were evaluated after applications using a scale of 0 (no injury) to 100 % (plant death) [8]. Cotton height measures were made up to five times in 2005, 2006 and 2007. Both rows of each plot were harvested with a spindle picker, and seed cotton yield was quantified. Data were subjected to mixed model ANOVA using Proc Mixed in SAS 9.1, with random effects of years and replications. Mean separation was determined using the PDMIX800 macro. Regression analysis was performed using Sigmaplot 12 nonlinear regression. The intent was to determine if the response could be described by using the exponential growth, Stirling Model.

$$y = y\,\text{O} + \begin{array}{c} \frac{\text{a}\left(e^{\text{b}\mathbf{x}}\right) - 1}{\text{b}} \end{array} \tag{1}$$

**5. Cotton response**

**5.1. Cotton injury**

the treated plots to simplify the model.

active ingredient/ha at cotton emergence (AE) applied.

There were significant formulation by application method, application method by timing, and formulation by timing interactions for cotton plant injury and cotton yield. Since the nontreated control had no associated timing effects and did not differ significantly in cotton yield or injury from the PRE applications (Table 2), comparisons of injury and yield included only

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

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35

Spray applications of pendimethalin EC resulted in greater crop injury (27%) than when pendimethalin EC was applied with fertilizer (12%) or both application methods of pendime‐ thalin ME (≤12%) (Table 2). Pendimethalin on fertilizer applied at the 3rd leaf stage and both application methods applied PRE or the 6th leaf stage of cotton had lower levels (≤7%) of cotton injury than all other treatments. For PRE applications, pendimethalin injury in the form of stunting, leaf curl, leathery cotyledons, swollen hypocotyl, and intense green color were observed, but this did not affect plant establishment, confirming previous results [14]. There was similar and significant injury when pendimethalin (Figure 7) was applied as cotton emerged (AE) with both the fertilizer (27%) and spray (42%) application and when sprayed at the 3rd leaf stage (27%). Previous reports of cotton injury resulting from a topical application of pendimethalin ME at the 4th leaf growth stage (≤20%) was lower than that from pendimen‐ talin EC (≤33%) [7]. When averaged over application method, there was minimal cotton injury when either pendimethalin formulation was applied PRE or at the 6th leaf stage. Greatest injury occurred when pendimethalin EC was applied AE (47%). At both the AE and 3rd leaf stage

timings, pendimethalin ME caused less cotton injury than pendimethalin EC.

**Figure 7.** Cotton injury from pendimethalin EC (110) as compared to pendimethalin ME (112). Both rates were 1.1 kg

Where *y* is the response variable of treatment, *y*0 is the value of the response variable (y) when *X* is equal to zero, *a* is the rate of growth, and *X* is time in days. Data for growth were analyzed by ANOVA under the general linear models procedure and used mean separation of 95% asymptotic confidence intervals for comparison of parameter estimates.

#### **4.2. Laboratory studies**

Fertilizer samples were taken prior to and after treatment with EC and ME pendimethalin. Samples were viewed at ×125 and ×200 magnification with a light microscope. Images were captured with a digital camera with image analysis software. Figure 6 notes the smooth surface for the EC formulations verses the course texture of the ME formulation alone and when impregnated on fertilizer.

**Figure 6.** Pendimethalin EC (top left) and ME (top right) formulations alone (x125 light microscope magnification), and EC (bottom left) and ME (bottom right) impregnated on fertilizers (x200).

### **5. Cotton response**

*<sup>y</sup>* <sup>=</sup> *<sup>y</sup>*<sup>0</sup> <sup>+</sup> a(*<sup>e</sup>* bx) - <sup>1</sup>

asymptotic confidence intervals for comparison of parameter estimates.

**4.2. Laboratory studies**

34 Herbicides - Current Research and Case Studies in Use

impregnated on fertilizer.

Where *y* is the response variable of treatment, *y*0 is the value of the response variable (y) when *X* is equal to zero, *a* is the rate of growth, and *X* is time in days. Data for growth were analyzed by ANOVA under the general linear models procedure and used mean separation of 95%

Fertilizer samples were taken prior to and after treatment with EC and ME pendimethalin. Samples were viewed at ×125 and ×200 magnification with a light microscope. Images were captured with a digital camera with image analysis software. Figure 6 notes the smooth surface for the EC formulations verses the course texture of the ME formulation alone and when

**Figure 6.** Pendimethalin EC (top left) and ME (top right) formulations alone (x125 light microscope magnification),

and EC (bottom left) and ME (bottom right) impregnated on fertilizers (x200).

<sup>b</sup> (1)

There were significant formulation by application method, application method by timing, and formulation by timing interactions for cotton plant injury and cotton yield. Since the nontreated control had no associated timing effects and did not differ significantly in cotton yield or injury from the PRE applications (Table 2), comparisons of injury and yield included only the treated plots to simplify the model.

### **5.1. Cotton injury**

Spray applications of pendimethalin EC resulted in greater crop injury (27%) than when pendimethalin EC was applied with fertilizer (12%) or both application methods of pendime‐ thalin ME (≤12%) (Table 2). Pendimethalin on fertilizer applied at the 3rd leaf stage and both application methods applied PRE or the 6th leaf stage of cotton had lower levels (≤7%) of cotton injury than all other treatments. For PRE applications, pendimethalin injury in the form of stunting, leaf curl, leathery cotyledons, swollen hypocotyl, and intense green color were observed, but this did not affect plant establishment, confirming previous results [14]. There was similar and significant injury when pendimethalin (Figure 7) was applied as cotton emerged (AE) with both the fertilizer (27%) and spray (42%) application and when sprayed at the 3rd leaf stage (27%). Previous reports of cotton injury resulting from a topical application of pendimethalin ME at the 4th leaf growth stage (≤20%) was lower than that from pendimen‐ talin EC (≤33%) [7]. When averaged over application method, there was minimal cotton injury when either pendimethalin formulation was applied PRE or at the 6th leaf stage. Greatest injury occurred when pendimethalin EC was applied AE (47%). At both the AE and 3rd leaf stage timings, pendimethalin ME caused less cotton injury than pendimethalin EC.

**Figure 7.** Cotton injury from pendimethalin EC (110) as compared to pendimethalin ME (112). Both rates were 1.1 kg active ingredient/ha at cotton emergence (AE) applied.


**5.2. Cotton height**

a

c

a

after planting.

after planting.

95% asymptotic confidence intervals.

Abbreviations: *a*, rate of cotton growth; CL, confidence limit.

separation with 95% asymptotic confidence intervals.

**Table 3.** Rate of cotton growth (*a*) as a response to pendimethalin formulation.a

There were no significant effects on cotton height during the year regardless of the pendime‐ thalin formulation or application type (Figures 8 to 10). The pendimethalin EC formulation (Figure 8) and spray application (Figure 9) did reduce height at 45 days after planting, but this was not significant and was not observed by 75 days after planting for either scenario. Cotton height was reflected in the injury for the timing of application (Figure 10). No differences were noted in height for the 6th leaf treatment timings. While there was cotton injury and height reduction when pendimethalin EC was spray applied at the AE or 3rd leaf timings, cotton recovered and height measures were equivalent by the end of the season. Utilizing exponential growth Stirling model, all curves converged with the analysis at no greater than 14 iterations (data not presented) with no differences for parameter estimates (Tables 3, 4 and 5). The long growing season in tandem with cotton's physiological ability to compensate for early season injury essentially explains why growth models can be effectively used to predict the lack of

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

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37

net negative effects from early season injury from pendimethalin applications.

**Herbicide** *ac* **95% CL b 95% CL** Pendimethalin EC 0.0537 a ±0.0179 0.0513 a ±0.00555 Pendimethalin ME 0.0516 a ±0.0173 0.0514 a ±0.0056 Nontreated 0.0669 a ±0.0558 0.0471 a ±0.0140

Each herbicide for first-order rate constants for each column followed by the same letter are not significantly different according to Fisher's protected LSD test (P≤0.05). General linear models procedures were used for mean separation with

bRates of cotton growth were calculated by nonlinear regression of the herbicide treatments with respect to time in days

**Application method** *ac* **95% CL b 95% CL** Fertilizer 0.0653 a ±0.0208 0.0485 a ±0.0053 Spray 0.0418 a ±0.0144 0.0545 a ±0.0057 Nontreated 0.0689 a ±0.0594 0.0463 a ±0.0145

Each application method for first-order rate constants for each column followed by the same letter are not significantly different according to Fisher's protected LSD test (P≤0.05). General linear models procedures were used for mean

bRates of cotton growth were calculated by nonlinear regression of the herbicide treatments with respect to time in days

**Rate of cotton growthb**

**Rate of cotton growthb**

a Because *proc Mixed* measures pair-wise differences, multiple LSDs may be obtained. In these cases, the LSD (α=0.05] included is the mean LSD for all treatments.

bPendimethalin rates were 1.1 kg ai/ha for the EC and ME formulations.

c Abbreviations: EC, emulsifiable concentrate (0.41 kg ai/L); ME, microencapsulated (0.47 kg ai/L); PRE, prior to plant emergence; AE, at seedling emergence; 3LF, to 3rd leaf cotton; 6LF, 6th leaf cotton

dMeans within a variable followed by the same letter are not significantly different using Fisher's protected LSD(P=0.05). Standard error of the mean for that treatment enclosed in ().

f Fertilizer [10 -10-10] rate was 280 kg/ha, with all plots equally treated. Pendimethalin EC and ME were spray impreg‐ nated.

**Table 2.** Interaction effects between pendimethalin formulation, application method, and application timing for injury in conventional tillage cotton.

#### **5.2. Cotton height**

**Injury LSDa**

**Formulation Application Timing \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_%\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_**

36 Herbicides - Current Research and Case Studies in Use

Pendimethalin ME Spray 12 b (4)

Pendimethalin ECbc Spray 27 ad (4)d 7

Fertilizerf 12 b (4)

Fertilizer 8 b (4)

Fertilizer PRE 6 c (5) Spray AE 42 a (5) Fertilizer AE 27 b (5) Spray 3LF 27 b (5) Fertilizer 3LF 5 c (5) Spray 6LF 1 c (5) Fertilizer 6LF 3 c (5)

Pendimethalin EC PRE 7 c (5) 10

Because *proc Mixed* measures pair-wise differences, multiple LSDs may be obtained. In these cases, the LSD (α=0.05]

Abbreviations: EC, emulsifiable concentrate (0.41 kg ai/L); ME, microencapsulated (0.47 kg ai/L); PRE, prior to plant

dMeans within a variable followed by the same letter are not significantly different using Fisher's protected LSD(P=0.05).

Fertilizer [10 -10-10] rate was 280 kg/ha, with all plots equally treated. Pendimethalin EC and ME were spray impreg‐

**Table 2.** Interaction effects between pendimethalin formulation, application method, and application timing for

Pendimethalin ME PRE 6 c (5) Pendimethalin EC AE 47 a (5) Pendimethalin ME AE 21 b (5) Pendimethalin EC 3LF 24 b (5) Pendimethalin ME 3LF 8 c (5) Pendimethalin EC 6LF 3 c (5) Pendimethalin ME 6LF 7 c (5)

a

c

f

nated.

included is the mean LSD for all treatments.

injury in conventional tillage cotton.

bPendimethalin rates were 1.1 kg ai/ha for the EC and ME formulations.

Standard error of the mean for that treatment enclosed in ().

emergence; AE, at seedling emergence; 3LF, to 3rd leaf cotton; 6LF, 6th leaf cotton

Spray PRE 7 c (5) 10

There were no significant effects on cotton height during the year regardless of the pendime‐ thalin formulation or application type (Figures 8 to 10). The pendimethalin EC formulation (Figure 8) and spray application (Figure 9) did reduce height at 45 days after planting, but this was not significant and was not observed by 75 days after planting for either scenario. Cotton height was reflected in the injury for the timing of application (Figure 10). No differences were noted in height for the 6th leaf treatment timings. While there was cotton injury and height reduction when pendimethalin EC was spray applied at the AE or 3rd leaf timings, cotton recovered and height measures were equivalent by the end of the season. Utilizing exponential growth Stirling model, all curves converged with the analysis at no greater than 14 iterations (data not presented) with no differences for parameter estimates (Tables 3, 4 and 5). The long growing season in tandem with cotton's physiological ability to compensate for early season injury essentially explains why growth models can be effectively used to predict the lack of net negative effects from early season injury from pendimethalin applications.


a Each herbicide for first-order rate constants for each column followed by the same letter are not significantly different according to Fisher's protected LSD test (P≤0.05). General linear models procedures were used for mean separation with 95% asymptotic confidence intervals.

bRates of cotton growth were calculated by nonlinear regression of the herbicide treatments with respect to time in days after planting.

c Abbreviations: *a*, rate of cotton growth; CL, confidence limit.

**Table 3.** Rate of cotton growth (*a*) as a response to pendimethalin formulation.a


a Each application method for first-order rate constants for each column followed by the same letter are not significantly different according to Fisher's protected LSD test (P≤0.05). General linear models procedures were used for mean separation with 95% asymptotic confidence intervals.

bRates of cotton growth were calculated by nonlinear regression of the herbicide treatments with respect to time in days after planting.

c Abbreviations: *a*, rate of cotton growth; CL, confidence limit.

**Table 4.** Rate of cotton growth (*a*) as a response to method of pendimethalin application.a

bRates of cotton growth were calculated by nonlinear regression of the herbicide treatments with respect to time in days

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

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39

**Days after planting 20 30 40 50 60 70**

**Figure 9.** Cotton growth response as affected by application method. The line represents the first-order regression

0.0485 P < 0.0001

0.0545 P < 0.0001

Cotton yields reflected the trends initially revealed with cotton injury. Pendimethalin EC spray applied (3,610 kg ha-1) had lower cotton yield than pendimethalin EC applied on fertilizer (4,010 kg ha-1) and both pendimethalin ME treatments (≥4,000 kg ha-1) (Table 6). The treatments that caused the greatest cotton injury for application method by timing interaction had the lowest yields, included both spray AE and 3rd leaf stage of cotton applications. Application timing of pendimethalin on fertilizer did not affect cotton yield. When averaged over appli‐ cation method, cotton yield for the pendimethalin ME treatments had equivalent cotton yields

equation. Data points are the means of replications with bars indicating the standard error of the mean:

0.0653 (*e* 0.0485x) - 1

0.0418 (*e* 0.0545x) - 1

0.0463 P < 0.0001

0.0689 (*e* 0.0463x) - 1

after planting.

**Plant cotton height (cm)**

**0**

Pendimethalin ME *y* =5.93 +

Pendimethalin EC *y* =5.95 +

Nontreated *y* =5.78 +

**5.3. Cotton yield**

**10**

**20**

**30**

**40**

**50**

**60**

Abbreviations: *a*, rate of cotton growth; CL, confidence limit.

**Table 5.** Rate of cotton growth (*a*) as a response to timing of pendimethalin application.a

**Nontreated**

**Pendimethalin fertilizer applied Pendimethalin spray applied**

c

**Figure 8.** Cotton growth response as affected by pendimethalin formulation. The line represents the first-order re‐ gression equation. Data points are the means of replications with bars indicating the standard error of the mean:

$$\text{Fertilizer applied } y = 6.31 + \frac{0.0537 \left[ \left( e^{0.0513 \text{\AA}} \right) - 1 \right]}{0.05137} \text{ P} < 0.00011$$

Spray applied *y* =5.62 + 0.0516 (*e* 0.0514x) - 1 0.0514 P < 0.0001

$$\text{Nontreatated } y = 5.83 + \frac{0.0669 \left[ \left( e^{0.0471 \times} \right) - 1 \right]}{0.0471} \text{ P} < 0.0001 \text{ .}$$


a Each application timing for first-order rate constants for each column followed by the same letter are not significantly different according to Fisher's protected LSD test (P≤0.05). General linear models procedures were used for mean separation with 95% asymptotic confidence intervals.

bRates of cotton growth were calculated by nonlinear regression of the herbicide treatments with respect to time in days after planting.

c Abbreviations: *a*, rate of cotton growth; CL, confidence limit.

c

Abbreviations: *a*, rate of cotton growth; CL, confidence limit.

38 Herbicides - Current Research and Case Studies in Use

**Cotton plant height (cm)**

**0**

Fertilizer applied *y* =6.31 +

Spray applied *y* =5.62 +

Nontreated *y* =5.83 +

a

**10**

**20**

**30**

**40**

**50**

**60**

**Table 4.** Rate of cotton growth (*a*) as a response to method of pendimethalin application.a

**Pendimethalin ME Pendimethalin EC Nontreated**

0.0537 (*e* 0.05137x) - 1

0.0516 (*e* 0.0514x) - 1

0.0669 (*e* 0.0471x) - 1

separation with 95% asymptotic confidence intervals.

**Days after planting 20 30 40 50 60 70**

**Rate of cotton growthb**

**Figure 8.** Cotton growth response as affected by pendimethalin formulation. The line represents the first-order re‐ gression equation. Data points are the means of replications with bars indicating the standard error of the mean:

0.05137 P < 0.0001

0.0514 P < 0.0001

**Application timing** *ac* **95% CL b 95% CL** Preemergence 0.1104 a ±0.0621 0.0395 a ±0.0067 At cotton emergence 0.0649 a ±0.0384 0.0488 a ±0.0099 3rd leaf cotton 0.0550 a ±0.0372 0.0512 a ±0.0112 6th leaf cotton 0.0415 a ±0.0319 0.0559 a ±0.0126 Nontreated 0.0689 a ±0.0594 0.0463 a ±0.0145

Each application timing for first-order rate constants for each column followed by the same letter are not significantly different according to Fisher's protected LSD test (P≤0.05). General linear models procedures were used for mean

0.0471 P < 0.0001

**Table 5.** Rate of cotton growth (*a*) as a response to timing of pendimethalin application.a

**Figure 9.** Cotton growth response as affected by application method. The line represents the first-order regression equation. Data points are the means of replications with bars indicating the standard error of the mean:

Pendimethalin ME *y* =5.93 + 0.0653 (*e* 0.0485x) - 1 0.0485 P < 0.0001 Pendimethalin EC *y* =5.95 + 0.0418 (*e* 0.0545x) - 1 0.0545 P < 0.0001 Nontreated *y* =5.78 + 0.0689 (*e* 0.0463x) - 1 0.0463 P < 0.0001

#### **5.3. Cotton yield**

Cotton yields reflected the trends initially revealed with cotton injury. Pendimethalin EC spray applied (3,610 kg ha-1) had lower cotton yield than pendimethalin EC applied on fertilizer (4,010 kg ha-1) and both pendimethalin ME treatments (≥4,000 kg ha-1) (Table 6). The treatments that caused the greatest cotton injury for application method by timing interaction had the lowest yields, included both spray AE and 3rd leaf stage of cotton applications. Application timing of pendimethalin on fertilizer did not affect cotton yield. When averaged over appli‐ cation method, cotton yield for the pendimethalin ME treatments had equivalent cotton yields across all application timings. Only pendimethalin EC applied AE or 3rd leaf stage cotton lower yields compared to the typical PRE use-pattern.

Pendmethalin 3 leaf applied *y* =5.87 +

Pendimethalin 6 leaf applied *y* =7.42 +

0.0689 (*e* 0.0463x) - 1

**Formulation Application Timing \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_kg/ha\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_**

Pendimethalin ME Spray 4000 a (149)

Pendimethalin ME PRE 4250 a (178) Pendimethalin EC AE 3630 bc (169) Pendimethalin ME AE 3980 ab (175) Pendimethalin EC 3LF 3510 c (169) Pendimethalin ME 3LF 4000 ab (174) Pendimethalin EC 6LF 3960 ab (185) Pendimethalin ME 6LF 4230 a (185)

0.0463 P < 0.0001

Pendimethalin EC Spray 3610 b (145) 252 Fertilizer 4010 a (149)

Fertilizer 4230 a (154)

Fertilizer PRE 4260 a (180) Spray AE 3570 b (172) Fertilizer AE 4050 a (175) Spray 3LF 3450 b (170) Fertilizer 3LF 4070 a (176) Spray 6LF 4080 a (188) Fertilizer 6LF 4110 a (182) Pendimethalin EC PRE 4140 a (181) 369

Because *proc Mixed* measures pair-wise differences, multiple LSDs may be obtained. In these cases, the LSD (α=0.05)

Spray PRE 4130 a (176) 370

Nontreated *y* =5.78 +

a

included is the mean LSD for all treatments.

bPendimethalin rates were 1.1 kg ai/ha for the EC and ME formulations.

0.0550 (*e* 0.0512x) - 1

0.0450 (*e* 0.00559x) - 1

0.0512 P < 0.0001

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

0.0559 P < 0.0001

**Yield LSD**

http://dx.doi.org/10.5772/56184

41

None of the PRE or 6th leaf application treatments displayed crop injury, significant decreased growth, or significant yield loss. The AE and 3rd leaf application treatments resulted in significant cotton crop injury and decreased yield, with pendimethalin EC treatments having greater injury than the pendimethalin ME, with spray applications exhibiting more injury than the fertilizer-applied treatments. The fertilizer application of pendimethalin at 3rd leaf did not significantly enhance crop injury, but did enhance injury at the AE application timing. Based on injury, subsequent height, and final yield measurements, pendimethalin ME caused less injury than pendimethalin EC, and fertilizer application of both formulations was less injurious than spray application. The AE application timing was prone to greater injury by any formu‐ lation or application method and should be avoided. The 3rd leaf appears to be more prone to spray injury than fertilizer injury.

**Figure 10.** Cotton growth response as affected by application timing. The line represents the first-order regression equation. Data points are the means of replications with bars indicating the standard error of the mean:

Pendimethalin PRE applied *y* =5.18 + 0.1104 (*e* 0.0395x) - 1 0.0395 P < 0.0001

Pendimethalin AE applied *y* =5.08 + 0.0649 (*e* 0.0488x) - 1 0.0545 P < 0.0001 Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application http://dx.doi.org/10.5772/56184 41

$$\text{Pendmethalin 3 leaf applied } y = 5.87 + \frac{0.0550 \left[ \left( e^{0.0512} \right) \cdot 1 \right]}{0.0512} \text{ P} < 0.00011$$

Pendimethalin 6 leaf applied *y* =7.42 + 0.0450 (*e* 0.00559x) - 1 0.0559 P < 0.0001

$$\text{Nontreated } y = 5.78 + \frac{0.0689 \left[ \left( e^{0.0463 \times} \right) - 1 \right]}{0.0463} \text{ P} < 0.00011$$

across all application timings. Only pendimethalin EC applied AE or 3rd leaf stage cotton lower

None of the PRE or 6th leaf application treatments displayed crop injury, significant decreased growth, or significant yield loss. The AE and 3rd leaf application treatments resulted in significant cotton crop injury and decreased yield, with pendimethalin EC treatments having greater injury than the pendimethalin ME, with spray applications exhibiting more injury than the fertilizer-applied treatments. The fertilizer application of pendimethalin at 3rd leaf did not significantly enhance crop injury, but did enhance injury at the AE application timing. Based on injury, subsequent height, and final yield measurements, pendimethalin ME caused less injury than pendimethalin EC, and fertilizer application of both formulations was less injurious than spray application. The AE application timing was prone to greater injury by any formu‐ lation or application method and should be avoided. The 3rd leaf appears to be more prone to

> **Days after planting 20 30 40 50 60 70**

> > 0.0395 P < 0.0001

0.0545 P < 0.0001

**Figure 10.** Cotton growth response as affected by application timing. The line represents the first-order regression

0.1104 (*e* 0.0395x) - 1

0.0649 (*e* 0.0488x) - 1

equation. Data points are the means of replications with bars indicating the standard error of the mean:

**Pendimethalin PRE applied Pendimethalin at emergence applied Pendimethalin 3 leaf applied PEndimethalin 6 leaf applied**

**Nontreated**

yields compared to the typical PRE use-pattern.

40 Herbicides - Current Research and Case Studies in Use

spray injury than fertilizer injury.

**Cotton plant height (cm)**

**0**

Pendimethalin PRE applied *y* =5.18 +

Pendimethalin AE applied *y* =5.08 +

**10**

**20**

**30**

**40**

**50**

**60**


a Because *proc Mixed* measures pair-wise differences, multiple LSDs may be obtained. In these cases, the LSD (α=0.05) included is the mean LSD for all treatments.

bPendimethalin rates were 1.1 kg ai/ha for the EC and ME formulations.

c Abbreviations: EC, emulsifiable concentrate (0.41 kg ai/L); ME, microencapsulated (0.47 kg ai/L); PRE, prior to plant emergence; AE, at seedling emergence; 3LF, to 3-leaf cotton; 6LF, 6-leaf cotton

**References**

nology , 18, 432-436.

Weed Sci. Soc. , 29-46.

620-626.

77-84.

536-539.

[1] AnonymousConservation Technology Information Center. (2005). National crop resi‐ due management survey. Available at www.ctic.purdue.edu/CTIC/CRM.htmlac‐

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

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43

[2] Byrd JrJ.D. and A.C. York. (1987). Annual grass control in cotton with fluazifop, se‐

[3] Culpepper, A. S. (2007). Cotton weed control. Georgia pest control handbook. Coop. Ext. Serv. The Univ. of Georgia College of Agr. and Environ. Sci., Athens, GA.

[4] Culpepper, A. S, Flanders, J. T, York, A. C, & Webster, T. M. (2004). Tropical spider‐ wort (Commelina benghalensis) control in glyphosate-resistant cotton. Weed Tech‐

[5] Culpepper, A. S, Grey, T. L, Vencill, W. K, Kichler, J. M, Webster, T. M, Brown, S. M, York, A. C, Davis, J. W, & Hanna, W. M. (2006). Glyphosate-resistant Palmer amar‐ anth (Amaranthus palmeri) confirmed in Georgia. Weed Sci. DOI:WS-06-001R.1., 54,

[6] Devine, M. D, Duke, S. O, & Fedtke, C. (1993). Physiology of Herbicide Action. Eng‐

[7] Dodds, D. M, Reynolds, D. B, Huff, J. A, & Irby, J. T. (2010). Effect of pendimethalin formulation and application rate on cotton fruit partitioning. Weed Technology , 24,

[8] Frans, R. E, Talbert, R, Marx, D, & Crowley, H. (1986). Experiment design and techni‐ ques for measuring and analyzing plant responses to weed control practices. In D. Camper, ed. Research Methods in Weed Science. 3rd ed. Champaign, IL: Southern

[9] Gaston, L. A, Boquet, D. J, & Bosch, M. A. (2003). Pendimethalin wash-off from cover crop residues and degradation in a loess soil. Communications in Soil Sci. and Plant

[10] Gordon, J. A, & Green, C. J. (1999). Comparative field and greenhouse studies of tri‐ fluralin and pendimethalin on cotton growth, development, and nutrient uptake. In Proc. Beltwide Cotton Conf., Orlando, FL, Natl. Cotton Counc. Am. Memphis, TN.,

[11] Grey, T. L, Webster, T. M, & Culpepper, A. S. (2008). Weed control as affected by pendimethalin timing and application method in conservation tillage cotton (Gos‐

thoxydim, and selected dinitroaniline herbicides. Weed Sci. , 35, 388-394.

cessed 12 Mar. 2009). CTIC, West Lafayette, IN. online].

lewood Cliffs, New Jersey: Prentice Hall. 441 p.

Analysis DOI:10.1081/CSS-120024783 , 34, 2515-2527.

sypium hirsutum). J. Cotton Sci. , 12, 318-324.

dMeans within a variable followed by the same letter are not significantly different using Fisher's protected LSD(P=0.05). Standard error of the mean for that treatment enclosed in ().

f Fertilizer (10-10-10) rate was 280 kg/ha, with all plots equally treated. Pendimethalin EC and ME were spray impregnated.

**Table 6.** Interaction effects between pendimethalin formulation, application method, and application timing for yield in conventional tillage cotton.

#### **6. Discussion**

Comparing the EC to ME pendimethalin formulations, when either spray or fertilizer impreg‐ nated applied, indicated the ME formulation consistently reduced cotton injury. The reason for the reduced cotton injury from the ME as compared to the EC-pendimethalin formulation is due to the microencapsulation. This has been observed with another ME formulated herbicide, alachlor [29]. While pendimethalin has lower volatilization than other dinitroana‐ line herbicides such as trifluralin [21], the ME formulation decreases volatilization and provides extended activity. As previously noted, pendimethalin half-lives of 74 to 114 days in soil have been reported [30], surface applied half-lives of 4 to 6 days can occur due to volati‐ lization, photo-chemical, and other degradation processes with EC formulation [21]. By utilizing the ME formulation, supplementing, or even delaying pendimethalin application to in-season timings impregnated on fertilizer, growers could extend residual weed control until cotton can canopy and suppress weed growth. Our recommendation would be to utilize pendimethalin as a PRE application followed by an in-season application impregnated on prilled fertilizers to extend weed control. Total seasonal pendimethalin applications in cotton are up to 2.24 kg ha-1. Cotton fertility recommendations for the southeast include in-season nitrogen applications which could be pendimethalin impregnated. Given advanced global positioning systems (GPS) used for accurate fertilizer applications, even greater precision for pesticide applications can now be achieved in tandem with these advanced technologies. These data indicate that cotton growers can successfully incorporate in-season pendimethalin application into their cotton production programs with minimal potential for cotton injury, while supplementing weed control with a residual herbicide.

#### **Author details**

Timothy Grey1\* and Theodore Webster2

\*Address all correspondence to: tgrey@uga.edu


### **References**

c

f

in conventional tillage cotton.

**6. Discussion**

**Author details**

Timothy Grey1\* and Theodore Webster2

\*Address all correspondence to: tgrey@uga.edu

Abbreviations: EC, emulsifiable concentrate (0.41 kg ai/L); ME, microencapsulated (0.47 kg ai/L); PRE, prior to plant

dMeans within a variable followed by the same letter are not significantly different using Fisher's protected LSD(P=0.05).

Fertilizer (10-10-10) rate was 280 kg/ha, with all plots equally treated. Pendimethalin EC and ME were spray impregnated.

**Table 6.** Interaction effects between pendimethalin formulation, application method, and application timing for yield

Comparing the EC to ME pendimethalin formulations, when either spray or fertilizer impreg‐ nated applied, indicated the ME formulation consistently reduced cotton injury. The reason for the reduced cotton injury from the ME as compared to the EC-pendimethalin formulation is due to the microencapsulation. This has been observed with another ME formulated herbicide, alachlor [29]. While pendimethalin has lower volatilization than other dinitroana‐ line herbicides such as trifluralin [21], the ME formulation decreases volatilization and provides extended activity. As previously noted, pendimethalin half-lives of 74 to 114 days in soil have been reported [30], surface applied half-lives of 4 to 6 days can occur due to volati‐ lization, photo-chemical, and other degradation processes with EC formulation [21]. By utilizing the ME formulation, supplementing, or even delaying pendimethalin application to in-season timings impregnated on fertilizer, growers could extend residual weed control until cotton can canopy and suppress weed growth. Our recommendation would be to utilize pendimethalin as a PRE application followed by an in-season application impregnated on prilled fertilizers to extend weed control. Total seasonal pendimethalin applications in cotton are up to 2.24 kg ha-1. Cotton fertility recommendations for the southeast include in-season nitrogen applications which could be pendimethalin impregnated. Given advanced global positioning systems (GPS) used for accurate fertilizer applications, even greater precision for pesticide applications can now be achieved in tandem with these advanced technologies. These data indicate that cotton growers can successfully incorporate in-season pendimethalin application into their cotton production programs with minimal potential for cotton injury,

emergence; AE, at seedling emergence; 3LF, to 3-leaf cotton; 6LF, 6-leaf cotton

while supplementing weed control with a residual herbicide.

1 Crop and Soil Sciences Department, University of Georgia, Tifton Georgia, USA

2 Crop Protection and Management Research Unit, USDA-ARS, Tifton Georgia, USA

Standard error of the mean for that treatment enclosed in ().

42 Herbicides - Current Research and Case Studies in Use


[12] Hatzinikolaou, A. S, Eleftherohorinos, I. G, & Vasilakoglou, I. B. (2004). Influence of formulation on the activity and persistence of pendimethalin. Weed Technol , 18, 397-403.

[26] Sosnoskie, L. M, Kichler, J. M, Wallace, R. D, & Culpepper, A. S. (2011). Multiple re‐ sistance in Palmer amaranth to glyphosate and pyrithiobac confirmed in Georgia.

Cotton (*Gossypium hirsutum* L.) Response to Pendimethalin Formulation, Timing, and Method of Application

http://dx.doi.org/10.5772/56184

45

[27] Sosnoskie, L. M, Webster, T. M, & Culpepper, A. S. (2012). Estimates of Palmer amar‐ anth (Amaranthus palmeri) seedbank longevity and potential post-dispersal herbivo‐

[28] Sosnoskie, L. M, Webster, T. M, Dales, D, Rains, G. C, Grey, T. L, & Culpepper, A. S. (2009). Pollen grain size, density, and settling velocity for Palmer amaranth (Amaran‐ thus palmeri). Weed Sci. Walker, A. and W. Bond. 1977. Persistence of the herbicide AC92,553,N-(1-ethylpropyl)-2,6 dinitro-3,4-xylidine in soils. Pestic. Sci. 8:359-365., 57,

[29] Vasilakoglou, I. B, & Eleftherohorinos, I. G. (1997). Activity, adsorption, mobility, ef‐ ficacy, and persistence of alachlor as influenced by formulation. Weed Sci. , 45,

[30] Vencill, W. K. (2002). Weed Science Society of America Herbicide Handbook, 8th ed.

[31] Vencill, W. K, Grey, T. L, Culpepper, A. S, Gaines, C, & Westra, R. (2008). Herbicideresistance in the Amaranthaceae. J. Plant Dis. Prot. Special Iss. XXI: , 41-44.

[32] Weber, J. B. (1990). Behavior of dinitroanaline herbicides in soils. Weed Technol. , 4,

[33] Webster, T. M, & Nichols, R. L. (2012). Changes in the prevalence of weed species in the major agronomic crops of the Southern United States: 1994/1995 to 2008/2009.

[34] Webster, T. M, & Sosnoskie, L. M. (2010). The loss of glyphosate efficacy: a changing

[35] Wilcut, J. W, Wehtje, G. R, & Hicks, T. V. (1990). Evaluation of herbicide systems in minimum-and conventional tillage peanuts (Arachis hypogaea). Weed Sci. , 38,

[36] Wilcut, J. W, Patterson, M. G, Wehtje, G. R, & Whitwell, T. (1988). Efficacy and eco‐ nomics of pendimethalin herbicide combinations for weed control in cotton (Gos‐

[37] Wilcut, J. W, Coble, H. D, York, A. C, & Monks, D. W. (1996). The niche for herbicideresistant crops in U.S. agriculture. In S.O. Duke (ed.) Herbicide-resistant crops: Agri‐ cultural, environmental, economic, regulatory, and technical aspects. CRC Press,

[38] Wise, A. M, Grey, T. L, Prostko, E. P, Vencill, W. K, & Webster, T. M. Establishing the geographical distribution and level of acetolactate synthase resistance of Palmer

weed spectrum in Georgia cotton. Weed Sci. , 58, 73-79.

sypium hirsutum). App. Ag. Res. , 3, 203-208.

Weed Sci. , 59, 321-325.

ry. Weed Sci. (submitted).

Lawrence, KS. , 231-234.

Weed Sci. , 60, 145-157.

Boca Raton, FL., 213-230.

404-409.

579-585.

394-406.

243-248.


[26] Sosnoskie, L. M, Kichler, J. M, Wallace, R. D, & Culpepper, A. S. (2011). Multiple re‐ sistance in Palmer amaranth to glyphosate and pyrithiobac confirmed in Georgia. Weed Sci. , 59, 321-325.

[12] Hatzinikolaou, A. S, Eleftherohorinos, I. G, & Vasilakoglou, I. B. (2004). Influence of formulation on the activity and persistence of pendimethalin. Weed Technol , 18,

[13] Keeling, J. W, & Abernathy, J. R. (1989). Response of cotton (Gossypium hirsutum) to repeated application of dinitroaniline herbicides. Weed Technol. , 3, 527-530.

[14] Keeling, J. W, Dotray, P. A, & Abernathy, J. R. (1996). Effects of repeated applications of trifluralin and pendimethalin on cotton (Gossypium hirsutum). Weed Technol. ,

[15] Martens, A. R, Burnside, O. C, & Cramer, G. L. (1978). Compatibility and phytotoxici‐

[16] Mueller, T. C, Mitchell, P. D, Yound, B. G, & Culpepper, A. S. (2005). Proactive Ver‐ sus Reactive Management of glyphosate-resistant or-tolerant weeds. Weed Technol. ,

[17] National Agricultural Statistics Service (NASS) (2010). National Agricultural Statis‐ tics Service U.S. Dept. of Agri.. Published Estimates Database. NASS-USDA, Wash‐ ington, DC. http://www.nass.usda.gov/Statistics\_by\_Subject/Environmental/

[18] Norsworthy, J. K, Smith, K. L, Steckel, L. E, & Koger, C. H. (2009). Weed seed con‐

[19] Parochetti, J. V, & Dec, G. W. Jr. (1978). Photodecomposition of eleven dinitroaniline

[20] Rabaey, T. L, & Harvey, R. G. (1994). Efficacy of corn (Zea mays) herbicides applied at reduced rates impregnated in dry fertilizer. Weed Technol. , 8, 830-835.

[21] Savage, K. E, & Jordan, T. N. (1980). Persistence of three dinitroaniline herbicides on

[22] Senseman, S. A. (2007). Weed Science Society of America Herbicide Handbook, 9th

[23] Shaner, D. L. (2000). The impact of glyphosate-tolerant crops on the use of other her‐

[24] Shaner, D. L. (2000). The impact of glyphosate-tolerant crops on the use of other her‐

[25] Shaner, D. L, Tecle, B, & Johnson, D. H. (1998). Mechanisms of selectivity of pendi‐ methalin and trifluralin in cotton (Gossypium hirsutum) and weeds. In Proc. Belt‐ wide Cotton Conf., San Diego, CA, Natl. Cotton Counc. Am. Memphis, TN.,

bicides on resistance management. Pest Manag. Sci. , 56, 320-326.

bicides on resistance management. Pest Manag. Sci. , 56, 320-326.

tamination of cotton gin trash. Weed Technol. , 23, 574-580.

herbicides. Weed Sci. , 26, 153-156.

the soil surface. Weed Sci. , 28, 105-110.

ed. Lawrence, KS. , 283-285.

1399-51402.

ty of herbicide-fertilizer. Agron. J. , 70, 1089-1098.

397-403.

44 Herbicides - Current Research and Case Studies in Use

10, 295-298.

19, 924-933.

index.asp


amaranth (Amaranthus palmeri) accessions in Georgia. Weed Tech. Weed Technol. , 23, 214-220.

**Chapter 3**

**Herbicide — Soil Interactions, Applied to Maize Crop**

This chapter discusses the behavior of herbicides in soil cultivated with maize crop in Brazilian conditions, reporting case studies of herbicide use in different periods, from the earliest to the present time, covering ecotoxicological aspects and reflections on the future of the use of the

Maize (*Zea mays* L.) is an annual herbaceous plant adapted to the most diverse ecological conditions. It is an economically important crop in tropical, subtropical and temperate climates, as well as in extreme altitudes, allowing its worldwide presence in several continents. Brazilian maize production is third in the world ranked behind United States and China. Currently, maize is one of the main crops in Brazil with annual grain yields around 57.5 million tons over a large area of production (13.8 million hectares). It is the most consumed cereal in the country under a variety of forms, in nature and processed food. The exportation volume estimate for 2012 is around 14 million tons, which corresponds to US \$ 2,766 billion income for

Since the late 1970's maize has been cropped in two distinct yearly periods, in the main Brazilian producing regions: one, called "full-season harvest" corn, sowed in the beginning of the rainy season (September, spring); and the other, called "safrinha" or "little harvest" or fallcorn cropping, sowed in the end of this rainy season (from January to April). Usually, fall corn is sowed after soybeans or common-beans harvest, in the same area where these crops had been previously grown, mainly in the South-Central Brazilian region, involving the States of

> © 2013 Blanco et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 Blanco et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

Paraná, São Paulo, Minas Gerais, Goiás, Mato Grosso and Mato Grosso do Sul.

**Under Brazilian Conditions**

Sydnei Dionisio Batista de Almeida and

Additional information is available at the end of the chapter

technology in herbicide-resistant transgenic maize.

Flavio Martins Garcia Blanco,

Marcus Barifouse Matallo

http://dx.doi.org/10.5772/56006

**1. Introduction**

Brazil [1].

## **Herbicide — Soil Interactions, Applied to Maize Crop Under Brazilian Conditions**

amaranth (Amaranthus palmeri) accessions in Georgia. Weed Tech. Weed Technol. ,

23, 214-220.

46 Herbicides - Current Research and Case Studies in Use

Flavio Martins Garcia Blanco, Sydnei Dionisio Batista de Almeida and Marcus Barifouse Matallo

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/56006

### **1. Introduction**

This chapter discusses the behavior of herbicides in soil cultivated with maize crop in Brazilian conditions, reporting case studies of herbicide use in different periods, from the earliest to the present time, covering ecotoxicological aspects and reflections on the future of the use of the technology in herbicide-resistant transgenic maize.

Maize (*Zea mays* L.) is an annual herbaceous plant adapted to the most diverse ecological conditions. It is an economically important crop in tropical, subtropical and temperate climates, as well as in extreme altitudes, allowing its worldwide presence in several continents.

Brazilian maize production is third in the world ranked behind United States and China. Currently, maize is one of the main crops in Brazil with annual grain yields around 57.5 million tons over a large area of production (13.8 million hectares). It is the most consumed cereal in the country under a variety of forms, in nature and processed food. The exportation volume estimate for 2012 is around 14 million tons, which corresponds to US \$ 2,766 billion income for Brazil [1].

Since the late 1970's maize has been cropped in two distinct yearly periods, in the main Brazilian producing regions: one, called "full-season harvest" corn, sowed in the beginning of the rainy season (September, spring); and the other, called "safrinha" or "little harvest" or fallcorn cropping, sowed in the end of this rainy season (from January to April). Usually, fall corn is sowed after soybeans or common-beans harvest, in the same area where these crops had been previously grown, mainly in the South-Central Brazilian region, involving the States of Paraná, São Paulo, Minas Gerais, Goiás, Mato Grosso and Mato Grosso do Sul.

© 2013 Blanco et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Blanco et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Therefore, the maize crop system adopted by Brazilian farmers has evolved from subsistence agriculture to technical agriculture by using improved adapted cultivars for each edaphocli‐ matic situation and pest management. Currently, maize cropping has shown expressive productivity increases, due to the modern crop production systems and top cultivars obtained via biotechnology. Farm unities with average grain yields above 7 ton per ha are commonly found in those regions.

out the highly technical breeding programs associated with biotechnology and modern crop

Herbicide — Soil Interactions, Applied to Maize Crop Under Brazilian Conditions

http://dx.doi.org/10.5772/56006

49

Inasmuch, weed control is the prevalent factor to an economically successful maize crop, and

Data from the National Association for Plant Defense (ANDEF) and the National Syndicate of Industrial Products for Agriculture Defense (SINDAG) indicated that Brazil is the world's largest pesticide market, and this industrial business mobilized US \$ 14.1 billion in 2010,

The maize crop was the third largest consumer of herbicides in 2011, ranked behind soybeans and sugarcane crops. Therefore, the knowledge on herbicide-soil interaction processes, applied to control weeds, is highly relevant to understanding the herbicide ecotoxicological

Since the first synthetic herbicide release of 2,4-D, a selective herbicide for Gramineae (Poa‐ ceae), in 1946, a revolution has occurred in the field for the crops of the Gramineae family, such

Concerning the maize crop, [7], cited by [8], reported grain yield increases of 25 thousand tons in a cropping area of 7,000 ha, due only to the use of 2,4-D, just after its release in EUA.

Furthermore, another positive aspect provided by herbicide use in the maize crop was the lower spacing among plant rows adopted, with consequent early shading. The old cultivators that required larger spacing among rows to cultivate the soil and eliminate emerging weeds were not necessary anymore. Therefore, [7] affirmed that only this row spacing change in the field allowed increasing plant population from 30 (in 1950) to 50 thousand plants per hectare

Another factor contributing to farmers' fast adoption of herbicides in maize cropping was the fact that women and children were set free of the hard work of hand-weeding. Weeds were removed by hand among plants within rows because cultivators would remove weeds between rows but not between plants in the row. In hand-weeded maize cropping, a man would spend 12 hours per hectare and the whole crop cycle would require three to five handweeding procedures [8, 9]. [10] calculated the human workpower necessary just to maintain the same level of annual production at that time and concluded that 18 million men would be required only to hand-weed maize cropping. Considering the work-hour average cost increase from US \$ 0.50 (in 1950) to the current US \$ 7.50, the choice for herbicide use is almost obligatory

The advent of s-triazines started in 1952 by researchers from the J. R. Geigy Ltd. Enterprise, in Basel, Swiss: the first patent was obtained in 1954 for the 2-chloro-4,6-bis (alkylamine)-striazines; 2-metoxi and 2-methylthio-4,6 bis (alkylamine)-s-triazines. The triazine selectivity

management procedures.

effects on the maize crop.

(in 1970).

economic success in maize.

for that, herbicide use is required.

divided into the classes described in Figure 1.

**2. Herbicide use in maize crop — A retrospective**

as the cereals (wheat, rice, maize, barley and oats).

Despite the fact that fall corn is subjected to higher production risks during the dry season, there is an economical compensation, due to the new market situation (better grain prices) after the full-season harvest offer. Additionally, there are lower production costs because farmers usually use second generation seeds from the hybrid full-season harvest and grow plants only with the residual fertilizers and herbicides, without any extra management.

This type of crop management has contributed to improved corn production in Brazil during the last 30 years: the production area increased from 11.6 to 13 million ha; annual grain yield increased from 19 to 54.1 thousand tons and average productivity from 1.6 to 4.1 kg ha-1. It is important to emphasize the small production area increase (10.7%) compared to the significant increases in grain yields (184%) and crop productivity (156%). Evidently, such increases, besides the two harvest seasons per year, were mainly due to research improvements in crop management, plant breeding and biotechnology areas.

**Figure 1.** Agricultural pesticides sales (%) in Brazil (2011). SINDAG [6]

Concerning the research results on maize/ weed cohabitation under Brazilian conditions, classic papers [2-5] have demonstrated yield losses between 22% and 83% due to weed competition with the maize crop within a critical period between 15 and 45 days after seedling emergence. There is evidence that weeds prevent maize plants from expressing their maximum production potential, impairing grain yields, even using top maize cultivars obtained through‐ out the highly technical breeding programs associated with biotechnology and modern crop management procedures.

Inasmuch, weed control is the prevalent factor to an economically successful maize crop, and for that, herbicide use is required.

Data from the National Association for Plant Defense (ANDEF) and the National Syndicate of Industrial Products for Agriculture Defense (SINDAG) indicated that Brazil is the world's largest pesticide market, and this industrial business mobilized US \$ 14.1 billion in 2010, divided into the classes described in Figure 1.

The maize crop was the third largest consumer of herbicides in 2011, ranked behind soybeans and sugarcane crops. Therefore, the knowledge on herbicide-soil interaction processes, applied to control weeds, is highly relevant to understanding the herbicide ecotoxicological effects on the maize crop.

### **2. Herbicide use in maize crop — A retrospective**

Therefore, the maize crop system adopted by Brazilian farmers has evolved from subsistence agriculture to technical agriculture by using improved adapted cultivars for each edaphocli‐ matic situation and pest management. Currently, maize cropping has shown expressive productivity increases, due to the modern crop production systems and top cultivars obtained via biotechnology. Farm unities with average grain yields above 7 ton per ha are commonly

Despite the fact that fall corn is subjected to higher production risks during the dry season, there is an economical compensation, due to the new market situation (better grain prices) after the full-season harvest offer. Additionally, there are lower production costs because farmers usually use second generation seeds from the hybrid full-season harvest and grow plants only with the residual fertilizers and herbicides, without any extra management.

This type of crop management has contributed to improved corn production in Brazil during the last 30 years: the production area increased from 11.6 to 13 million ha; annual grain yield increased from 19 to 54.1 thousand tons and average productivity from 1.6 to 4.1 kg ha-1. It is important to emphasize the small production area increase (10.7%) compared to the significant increases in grain yields (184%) and crop productivity (156%). Evidently, such increases, besides the two harvest seasons per year, were mainly due to research improvements in crop

Concerning the research results on maize/ weed cohabitation under Brazilian conditions, classic papers [2-5] have demonstrated yield losses between 22% and 83% due to weed competition with the maize crop within a critical period between 15 and 45 days after seedling emergence. There is evidence that weeds prevent maize plants from expressing their maximum production potential, impairing grain yields, even using top maize cultivars obtained through‐

management, plant breeding and biotechnology areas.

**Figure 1.** Agricultural pesticides sales (%) in Brazil (2011). SINDAG [6]

found in those regions.

48 Herbicides - Current Research and Case Studies in Use

Since the first synthetic herbicide release of 2,4-D, a selective herbicide for Gramineae (Poa‐ ceae), in 1946, a revolution has occurred in the field for the crops of the Gramineae family, such as the cereals (wheat, rice, maize, barley and oats).

Concerning the maize crop, [7], cited by [8], reported grain yield increases of 25 thousand tons in a cropping area of 7,000 ha, due only to the use of 2,4-D, just after its release in EUA.

Furthermore, another positive aspect provided by herbicide use in the maize crop was the lower spacing among plant rows adopted, with consequent early shading. The old cultivators that required larger spacing among rows to cultivate the soil and eliminate emerging weeds were not necessary anymore. Therefore, [7] affirmed that only this row spacing change in the field allowed increasing plant population from 30 (in 1950) to 50 thousand plants per hectare (in 1970).

Another factor contributing to farmers' fast adoption of herbicides in maize cropping was the fact that women and children were set free of the hard work of hand-weeding. Weeds were removed by hand among plants within rows because cultivators would remove weeds between rows but not between plants in the row. In hand-weeded maize cropping, a man would spend 12 hours per hectare and the whole crop cycle would require three to five handweeding procedures [8, 9]. [10] calculated the human workpower necessary just to maintain the same level of annual production at that time and concluded that 18 million men would be required only to hand-weed maize cropping. Considering the work-hour average cost increase from US \$ 0.50 (in 1950) to the current US \$ 7.50, the choice for herbicide use is almost obligatory economic success in maize.

The advent of s-triazines started in 1952 by researchers from the J. R. Geigy Ltd. Enterprise, in Basel, Swiss: the first patent was obtained in 1954 for the 2-chloro-4,6-bis (alkylamine)-striazines; 2-metoxi and 2-methylthio-4,6 bis (alkylamine)-s-triazines. The triazine selectivity description for maize was published in 1955 [11, 12]. The first assays with triazines began in 1952 with the chlorazine molecule. In the following years, so many molecules were synthesized in the same chemical group that a specific symposium was organized in Riverside, California, in 1969 [13].

been observed to efficiently control weeds and not cause any toxicity to maize plants, allowing

Herbicide — Soil Interactions, Applied to Maize Crop Under Brazilian Conditions

http://dx.doi.org/10.5772/56006

51

This occurred at the same time that new post-emergent herbicides were released for maize including: nicosulfuron, isoxaflutole, foramsulfuron + iodosulfuron-methyl, mesotrione and tembotrione. The main advantage of the post-emergent procedure is to better adjust the herbicide dose to control the emergent weed flora, avoiding excessive rates, saving money and decreasing environmental impact. However, there are toxicity risks mainly concerning maize or other more susceptible crops in succession to maize due to residual herbicide effects in the soil. Since the herbicides are indicated for post-emergent application and they are applied over plants, at first, it might erroneously suggest that such chemical products do not persist in the

It is important to highlight that many of those new herbicides have been indicated for agricultural use as components of mixtures with atrazine, similar to the usual recommendation for metolachlor (chloroacetamides group). The herbicide action of atrazine + metolachlor mixture consists of the inhibition of weed cellular division mainly in plants from Poaceae (Gramineae group), complementing the broadleaf weed atrazine action (dicotyledonous plants). Therefore, this herbicide mixture has a wider range of action over weed species which explains its commercial success; up to now, it is considered the best standard herbicide mixture

Now, research work must focus on these two herbicides in studies concerning the herbicidesoil interactions, applied to maize, since herbicide residues might persist in soils for longer periods than expected, causing phytotoxicity to the next season crop in succession or rotation practices. The knowledge on herbicide persistence in soils is critically important for the

In agricultural systems, the soil represents the final destination of large numbers of herbicides

Herbicides interact with the environment throughout three main routes: (1) physical processes such as soil desorption, volatilization, lixiviation (by water) and erosion together with soil (by wind and water); (2) chemical processes such as photodecomposition, adsorption, reaction with soil components; and (3) biological processes such as molecule decomposition by

According to [18-22], all those processes are dependent on the soil chemical and physical characteristics (soil texture, structure, colloid nature and concentration, pH, etc.) and climatic conditions, particularly, the soil temperature and moisture. On the other hand, the herbicide chemical characteristics depend on the molecular structure, ionization, water solubility,

adequate use of such products in sustainable environmental systems.

its recommendation also as a post-emergent herbicide.

soil or show low persistence.

**3. Herbicide interaction in soils**

applied directly on the soil or over the plant shoots [15].

microorganisms and absorption by plants [16, 17].

liposolubility, polarization and volatization.

for maize.

Since then, herbicide use in the maize increased significantly, because s-triazines were more selective than 2,4-D, which were more phytotoxic to several maize genotypes than s-triazines. Atrazine, specifically, showed low phytotoxicity to maize plants and could also control some dicotyledonous weeds, a distinct property not shown by 2,4-D that is a specific graminicide herbicide. Therefore, important competitive weeds to the maize crop could then be controlled, such as *Bidens pilosa, Emilia sonchifolia, Amaranthus sp, Euphorbia heterophylla, Portulaca olera‐ ceae,* and *Sonchus oleraceae*, representing an advance in weed control management in maize.

Extensive literature concerning s-triazines interactions in the soil can be found because they are among the soil applied herbicides most used worldwide, making it difficult to present a complete review on this subject. A significant number of international reports about atrazine and simazine are available about the most used triazines in maize, but little literature on the environmental toxicology area for Brazilian conditions is available.

Among the herbicides of the s-triazine group used in maize is atrazine; since its release up to now, it has been considered an excellent herbicide due to its selectivity, range of weed control and safety, not causing phytotoxicity for successive crops. At present, it is estimated that 75% of maize-cropped area in the USA is treated with atrazine.

Atrazine (C8H14ClN5) properties are: chemical name (IUPAC) 6-chloro-*N2* -ethyl-*N4* -isoprop‐ yl-1,3,5-triazine-2,4-diamine; fusion point = 175ºC; solubility in H2O(20º) = 33 mg kg-1; vapor pressure = 3.0 10-7; pK(21º) = 1.68 and Log Kow(25º) = 2.61, [12].

In Brazil, atrazine is largely used and registered for pineapple, sugarcane, pine, rubber-tree, sorghum and maize.

Atrazine is mainly taken up by roots and also through leaves of plants. When absorbed by roots, it is rapidly transported upwards via xylem and accumulated in the meristems; its movement in the phloem is restricted. Atrazine functions through photosynthesis inhibition by impairing the Hill reaction in the photosystem II, leading to death of susceptible plants. In tolerant plants, like maize and sorghum, atrazine is bound to glutathione (GHS), blocking the atrazine molecule herbicide action [14].

At first, atrazine and other s-triazines were recommended only as pre-emergent herbicides, that is, applied directly on the soil or incorporated just after sowing. However, in the early 1990's, farmers faced climate difficulties that impeded application as recommended, because the pre-emergent application would require a dry period without rain just after sowing to put the implements in the field; in many cases, the dry period would not occur and when the climate conditions were favorable, both the maize seeds and weeds had already emerged their second leaves, characteristic of the first emergence flow. Then, farmers did not have other options than that of applying the herbicide over the plants in the initial stage of development, characterizing a post-emergent herbicide application. From then on and to date, atrazine has been observed to efficiently control weeds and not cause any toxicity to maize plants, allowing its recommendation also as a post-emergent herbicide.

This occurred at the same time that new post-emergent herbicides were released for maize including: nicosulfuron, isoxaflutole, foramsulfuron + iodosulfuron-methyl, mesotrione and tembotrione. The main advantage of the post-emergent procedure is to better adjust the herbicide dose to control the emergent weed flora, avoiding excessive rates, saving money and decreasing environmental impact. However, there are toxicity risks mainly concerning maize or other more susceptible crops in succession to maize due to residual herbicide effects in the soil. Since the herbicides are indicated for post-emergent application and they are applied over plants, at first, it might erroneously suggest that such chemical products do not persist in the soil or show low persistence.

It is important to highlight that many of those new herbicides have been indicated for agricultural use as components of mixtures with atrazine, similar to the usual recommendation for metolachlor (chloroacetamides group). The herbicide action of atrazine + metolachlor mixture consists of the inhibition of weed cellular division mainly in plants from Poaceae (Gramineae group), complementing the broadleaf weed atrazine action (dicotyledonous plants). Therefore, this herbicide mixture has a wider range of action over weed species which explains its commercial success; up to now, it is considered the best standard herbicide mixture for maize.

Now, research work must focus on these two herbicides in studies concerning the herbicidesoil interactions, applied to maize, since herbicide residues might persist in soils for longer periods than expected, causing phytotoxicity to the next season crop in succession or rotation practices. The knowledge on herbicide persistence in soils is critically important for the adequate use of such products in sustainable environmental systems.

### **3. Herbicide interaction in soils**

description for maize was published in 1955 [11, 12]. The first assays with triazines began in 1952 with the chlorazine molecule. In the following years, so many molecules were synthesized in the same chemical group that a specific symposium was organized in Riverside, California,

Since then, herbicide use in the maize increased significantly, because s-triazines were more selective than 2,4-D, which were more phytotoxic to several maize genotypes than s-triazines. Atrazine, specifically, showed low phytotoxicity to maize plants and could also control some dicotyledonous weeds, a distinct property not shown by 2,4-D that is a specific graminicide herbicide. Therefore, important competitive weeds to the maize crop could then be controlled, such as *Bidens pilosa, Emilia sonchifolia, Amaranthus sp, Euphorbia heterophylla, Portulaca olera‐ ceae,* and *Sonchus oleraceae*, representing an advance in weed control management in maize.

Extensive literature concerning s-triazines interactions in the soil can be found because they are among the soil applied herbicides most used worldwide, making it difficult to present a complete review on this subject. A significant number of international reports about atrazine and simazine are available about the most used triazines in maize, but little literature on the

Among the herbicides of the s-triazine group used in maize is atrazine; since its release up to now, it has been considered an excellent herbicide due to its selectivity, range of weed control and safety, not causing phytotoxicity for successive crops. At present, it is estimated that 75%

yl-1,3,5-triazine-2,4-diamine; fusion point = 175ºC; solubility in H2O(20º) = 33 mg kg-1; vapor

In Brazil, atrazine is largely used and registered for pineapple, sugarcane, pine, rubber-tree,

Atrazine is mainly taken up by roots and also through leaves of plants. When absorbed by roots, it is rapidly transported upwards via xylem and accumulated in the meristems; its movement in the phloem is restricted. Atrazine functions through photosynthesis inhibition by impairing the Hill reaction in the photosystem II, leading to death of susceptible plants. In tolerant plants, like maize and sorghum, atrazine is bound to glutathione (GHS), blocking the

At first, atrazine and other s-triazines were recommended only as pre-emergent herbicides, that is, applied directly on the soil or incorporated just after sowing. However, in the early 1990's, farmers faced climate difficulties that impeded application as recommended, because the pre-emergent application would require a dry period without rain just after sowing to put the implements in the field; in many cases, the dry period would not occur and when the climate conditions were favorable, both the maize seeds and weeds had already emerged their second leaves, characteristic of the first emergence flow. Then, farmers did not have other options than that of applying the herbicide over the plants in the initial stage of development, characterizing a post-emergent herbicide application. From then on and to date, atrazine has



environmental toxicology area for Brazilian conditions is available.

Atrazine (C8H14ClN5) properties are: chemical name (IUPAC) 6-chloro-*N2*

of maize-cropped area in the USA is treated with atrazine.

pressure = 3.0 10-7; pK(21º) = 1.68 and Log Kow(25º) = 2.61, [12].

in 1969 [13].

50 Herbicides - Current Research and Case Studies in Use

sorghum and maize.

atrazine molecule herbicide action [14].

In agricultural systems, the soil represents the final destination of large numbers of herbicides applied directly on the soil or over the plant shoots [15].

Herbicides interact with the environment throughout three main routes: (1) physical processes such as soil desorption, volatilization, lixiviation (by water) and erosion together with soil (by wind and water); (2) chemical processes such as photodecomposition, adsorption, reaction with soil components; and (3) biological processes such as molecule decomposition by microorganisms and absorption by plants [16, 17].

According to [18-22], all those processes are dependent on the soil chemical and physical characteristics (soil texture, structure, colloid nature and concentration, pH, etc.) and climatic conditions, particularly, the soil temperature and moisture. On the other hand, the herbicide chemical characteristics depend on the molecular structure, ionization, water solubility, liposolubility, polarization and volatization.

Different external factors exert important roles on herbicide-soil interactions, such as the herbicide formula, rate and mode of application, which are illustrated in Figure 2.

fundamental factor in environmental toxicological studies, because it is determinant to other

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Soil sorption is affected by the involved molecule size. [24] demonstrated that large organic molecules, like herbicides, when adsorbed in montmorillonite clay type, can hardly be substituted by small ions. However, the authors affirmed that the most influential property of clay is the charge type. A stronger electrical charge is generated from dissociation and a weaker charge is resultant from a non-uniform electron distribution on the molecule surface, causing

Briggs [18, 19], affirmed that the extension and intensity of processes involved in the sorption/ desorption phenomena are greatly dependent on the herbicide molecular properties and soil temperature and moisture. Similarly, [15] cited the importance of herbicide physical-chemical

Velini [22], evidenced that the knowledge on how much the sorption process influences the herbicide sorption on soil colloids is fundamental to define the herbicide application rate to

According to [28], the sorption/desorption processes are highly influenced by the soil colloid type because the larger the specific surface (organic matter, 2:1 clay type), the larger the sorption on soil colloid. Soil moisture also significantly affects the process, once the higher the moisture the lower the sorption. This is due to the fact that H+ ions, with concentrations dependent on the soil moisture content, compete with the herbicide molecules for the sorption sites at the soil colloids' surface. Therefore, higher herbicide sorption occurs under a water

The acidic and alkaline compounds' ionization is dependent on the soil pH and herbicide pK. In the case of atrazine, pK(21º) = 1.68; and under Brazilian soil pH conditions (pH>5.5), most

In accordance [50], the lack of knowledge about the sorption/desorption phenomena is not surprising because the soil is a highly complex biological and chemical medium, making it difficult to completely understand the interdependent relationships and interactions among the several components involved which certainly affect the herbicide sorption/desorption

Pre-emergent herbicides are expected to present a certain movement in the soil and to be taken up by weed seedling roots because such movement provides an important soil surface

, subject to the non-ionic sorption processes, such

properties, as well as of soil pH, soil colloid type and soil cation retention.

processes like lixiviation and microbial decomposition [26, 27].

weak polarity.

deficit.

processes in the soil.

<sup>1</sup>*%ionization*(*base*)= <sup>100</sup>

efficiently control weeds.

molecules would be in the molecular form1

**5. Herbicide movement in the soil**

1 + *anti*log(*pH* − *pK*)

as hydrogen bridges and van der Waals forces.

**Figure 2.** Diagram of the main herbicide-soil interaction processes, adapted from [20].

The processes of soil colloid adsorption-desorption of herbicide molecules greatly influence herbicide movement and transformation in the environment.

### **4. Soil sorption (adsorption) and desorption of herbicide molecules**

The soil adsorption process is understood as the adherence of a molecule, an ion or other particle on the soil surface, as a result of the interaction between both the adsorbing (clay, organic matter) and adsorbed surfaces' field strengths (in this case, the herbicide). Herbicide particles may also be *absorbed* (taken up) by soil colloids. [23], discussed about the difficulty in differentiating between the absorption and adsorption phenomena, suggesting the term "sorption" to express both processes.

Soil sorption is generally a reversible phenomenon (sorption/desorption) and an equilibrium is reached between the adsorbed (sorbed) herbicide concentration on clay/organic matter and the herbicide concentration in the soil solution [24, 25]. The soil sorption is generally a physical process in which attraction forces are involved: such as the van der Waals strengths, bipolar particle interactions, hydrogen bridges and hydrophobic binds. When soil sorption is resultant from chemical processes, an irreversible chemical reaction (herbicide-soil colloid interaction) might occur and a third compound or a stable complex molecule is formed. Soil sorption is a fundamental factor in environmental toxicological studies, because it is determinant to other processes like lixiviation and microbial decomposition [26, 27].

Soil sorption is affected by the involved molecule size. [24] demonstrated that large organic molecules, like herbicides, when adsorbed in montmorillonite clay type, can hardly be substituted by small ions. However, the authors affirmed that the most influential property of clay is the charge type. A stronger electrical charge is generated from dissociation and a weaker charge is resultant from a non-uniform electron distribution on the molecule surface, causing weak polarity.

Briggs [18, 19], affirmed that the extension and intensity of processes involved in the sorption/ desorption phenomena are greatly dependent on the herbicide molecular properties and soil temperature and moisture. Similarly, [15] cited the importance of herbicide physical-chemical properties, as well as of soil pH, soil colloid type and soil cation retention.

Velini [22], evidenced that the knowledge on how much the sorption process influences the herbicide sorption on soil colloids is fundamental to define the herbicide application rate to efficiently control weeds.

According to [28], the sorption/desorption processes are highly influenced by the soil colloid type because the larger the specific surface (organic matter, 2:1 clay type), the larger the sorption on soil colloid. Soil moisture also significantly affects the process, once the higher the moisture the lower the sorption. This is due to the fact that H+ ions, with concentrations dependent on the soil moisture content, compete with the herbicide molecules for the sorption sites at the soil colloids' surface. Therefore, higher herbicide sorption occurs under a water deficit.

The acidic and alkaline compounds' ionization is dependent on the soil pH and herbicide pK. In the case of atrazine, pK(21º) = 1.68; and under Brazilian soil pH conditions (pH>5.5), most molecules would be in the molecular form1 , subject to the non-ionic sorption processes, such as hydrogen bridges and van der Waals forces.

In accordance [50], the lack of knowledge about the sorption/desorption phenomena is not surprising because the soil is a highly complex biological and chemical medium, making it difficult to completely understand the interdependent relationships and interactions among the several components involved which certainly affect the herbicide sorption/desorption processes in the soil.

### **5. Herbicide movement in the soil**

Pre-emergent herbicides are expected to present a certain movement in the soil and to be taken up by weed seedling roots because such movement provides an important soil surface

<sup>1</sup>*%ionization*(*base*)= <sup>100</sup> 1 + *anti*log(*pH* − *pK*)

Different external factors exert important roles on herbicide-soil interactions, such as the

herbicide formula, rate and mode of application, which are illustrated in Figure 2.

**Figure 2.** Diagram of the main herbicide-soil interaction processes, adapted from [20].

herbicide movement and transformation in the environment.

"sorption" to express both processes.

52 Herbicides - Current Research and Case Studies in Use

The processes of soil colloid adsorption-desorption of herbicide molecules greatly influence

The soil adsorption process is understood as the adherence of a molecule, an ion or other particle on the soil surface, as a result of the interaction between both the adsorbing (clay, organic matter) and adsorbed surfaces' field strengths (in this case, the herbicide). Herbicide particles may also be *absorbed* (taken up) by soil colloids. [23], discussed about the difficulty in differentiating between the absorption and adsorption phenomena, suggesting the term

Soil sorption is generally a reversible phenomenon (sorption/desorption) and an equilibrium is reached between the adsorbed (sorbed) herbicide concentration on clay/organic matter and the herbicide concentration in the soil solution [24, 25]. The soil sorption is generally a physical process in which attraction forces are involved: such as the van der Waals strengths, bipolar particle interactions, hydrogen bridges and hydrophobic binds. When soil sorption is resultant from chemical processes, an irreversible chemical reaction (herbicide-soil colloid interaction) might occur and a third compound or a stable complex molecule is formed. Soil sorption is a

**4. Soil sorption (adsorption) and desorption of herbicide molecules**

incorporation, allowing a better herbicide contact with greater number of weed seeds or seedlings and maximizing weed control.

In Brazil, significant amounts of atrazine and simazine residues were detected in artesian wellwaters in the recharge area of Guarani aquifer, an important underwater natural resource [34]. Almeida [35], carried out detailed s-triazine sorption/ desorption studies on different soils from the region of Ubatuba municipal district, State of São Paulo, Brazil. The authors reported that potential herbicide lixiviation and/or superficial runoff would depend on the intrinsic soil characteristics and that the herbicide recommendation must be supported and evaluated based on such soil attributes. Furthermore, the authors observed high s-triazine sorption and consequently lower lixiviation potential in high organic-C content soils; and low herbicide sorption in low C-content soils, favoring desorption and increasing the potential risk of subsoil contamination. They concluded that the soil organic-C content is directly related to the striazine sorption and it might be an important indicator of herbicide lixiviation potential,

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**6. Determination of herbicide persistence and lixiviation: Simazine,**

Blanco [37], determined herbicide persistence and lixiviation up to 50 cm soil depth, using gaschromatography, in a field experiment with simazine applied as a pre-emergent herbicide in maize at the rate of 3 kg ha-1 (a.i. = active ingredient), in the State of São Paulo, Brazil. The

> 0 14 37 65 100 127 183 360  **Days after treatment (DAT)**

**Figure 3.** Simazine residue means determined in several soil depth samples (layers from 0-10 until 40-50 cm), collect‐

The highest simazine concentration was found in the 0-10 cm superficial soil layer (Figure 3) and decreasing simazine concentrations were found in deeper layers (30-40 cm), 14 until 65

0-10 10-20 20-30 30-40 40-50

soil layer depth (cm)

corroborating the results observed in [36].

results obtained are described as follows:

0

ed in different sampling dates [37].

0,5

1

1,5

**Simazine concentration in the soil (mg kg-1)**

2

2,5

3

**atrazine and metolachlor**

Herbicides applied to the soil might move in all directions and phases - gaseous or liquid phases – in areas exposed to intense winds during specific year periods, which could transport considerable herbicide amounts [28], but the vertical descendent route is the most significant movement, characterizing herbicide lixiviation [29, 15].

The herbicide lixiviation in soils is a relevant factor affecting herbicide persistence in the environment. Herbicide lixiviation is dependent on several factors related to the herbicide molecule properties (as intrinsic molecule unity - volatilization, ionization capacity, water solubility, molecular size and weight and lipophilicity) and edaphoclimatic factors (soil type, organic matter content, relief, rainfall and temperature), as well as the herbicide application method. All these factors will determine an herbicide immobilization rate by soil sorption and will influence the herbicide lixiviation. When the herbicide is dragged into deeper soil layers by lixiviation, it persists for longer periods in the environment due to the absence or lower number of microorganisms responsible for the molecule decomposition [30].

The knowledge on herbicide movement routes in soils is essential to a better herbicide/weed management (dose and application method) as well as to understand the potential contami‐ nation risks to the environment. The possible herbicide routes that might severely contaminate environment resources include lixiviation to underground waters, superficial molecular movement in solution or suspension (erosion) to water flows, volatilization (air contamina‐ tion), and removal by live organisms [30].

The higher the herbicide lipophilicity, the higher the tendency to be sorbed on soil colloids, and consequently, lower herbicide lixiviation would be expected. On the other hand, high hydro‐ philic herbicides would be expected to show lower soil sorption and higher lixiviation rates.

Besides the herbicide vertical movement in the soil profile being an important indicator of its potential contamination risk to underground water and deeper layers, it is also an indicator of herbicide persistence and potential contamination risks to plants with deeper root systems.

Herbicide soil persistence can be determined by biological methods (using bio-indicators) and by chemical or radiometric methods. Both methodologies have advantages and disadvantages and allow assessing the period of herbicide presence in the soil within the detection limits of each method used [31].

Several research works of environment monitoring for potentially toxic residues have been carried out during the last decades, mainly in developed countries. For instance, [32] reported the soil analysis results of 130 different pesticide and herbicide residues applied to agricultural soils in annual crops of 43 USA states. Among the 130 chemical products, only 24 were found in soils during the harvest period: 6 herbicides, 5 phosphorous pesticides, 11 chlorinated pesticides and 2 arsenium pesticides. Among the herbicides, atrazine and simazine, both from the triazine group, persisted in the soil for periods of 12 and 10 months, respectively. [33], when monitoring more than 2200 wells in areas of irrigated maize, detected the presence of several herbicides, such as atrazine, simazine, propazine, prometon and ametrine, and also traces of metolachlor in several well-water samplings.

In Brazil, significant amounts of atrazine and simazine residues were detected in artesian wellwaters in the recharge area of Guarani aquifer, an important underwater natural resource [34].

incorporation, allowing a better herbicide contact with greater number of weed seeds or

Herbicides applied to the soil might move in all directions and phases - gaseous or liquid phases – in areas exposed to intense winds during specific year periods, which could transport considerable herbicide amounts [28], but the vertical descendent route is the most significant

The herbicide lixiviation in soils is a relevant factor affecting herbicide persistence in the environment. Herbicide lixiviation is dependent on several factors related to the herbicide molecule properties (as intrinsic molecule unity - volatilization, ionization capacity, water solubility, molecular size and weight and lipophilicity) and edaphoclimatic factors (soil type, organic matter content, relief, rainfall and temperature), as well as the herbicide application method. All these factors will determine an herbicide immobilization rate by soil sorption and will influence the herbicide lixiviation. When the herbicide is dragged into deeper soil layers by lixiviation, it persists for longer periods in the environment due to the absence or lower

The knowledge on herbicide movement routes in soils is essential to a better herbicide/weed management (dose and application method) as well as to understand the potential contami‐ nation risks to the environment. The possible herbicide routes that might severely contaminate environment resources include lixiviation to underground waters, superficial molecular movement in solution or suspension (erosion) to water flows, volatilization (air contamina‐

The higher the herbicide lipophilicity, the higher the tendency to be sorbed on soil colloids, and consequently, lower herbicide lixiviation would be expected. On the other hand, high hydro‐ philic herbicides would be expected to show lower soil sorption and higher lixiviation rates. Besides the herbicide vertical movement in the soil profile being an important indicator of its potential contamination risk to underground water and deeper layers, it is also an indicator of herbicide persistence and potential contamination risks to plants with deeper root systems. Herbicide soil persistence can be determined by biological methods (using bio-indicators) and by chemical or radiometric methods. Both methodologies have advantages and disadvantages and allow assessing the period of herbicide presence in the soil within the detection limits of

Several research works of environment monitoring for potentially toxic residues have been carried out during the last decades, mainly in developed countries. For instance, [32] reported the soil analysis results of 130 different pesticide and herbicide residues applied to agricultural soils in annual crops of 43 USA states. Among the 130 chemical products, only 24 were found in soils during the harvest period: 6 herbicides, 5 phosphorous pesticides, 11 chlorinated pesticides and 2 arsenium pesticides. Among the herbicides, atrazine and simazine, both from the triazine group, persisted in the soil for periods of 12 and 10 months, respectively. [33], when monitoring more than 2200 wells in areas of irrigated maize, detected the presence of several herbicides, such as atrazine, simazine, propazine, prometon and ametrine, and also traces of

number of microorganisms responsible for the molecule decomposition [30].

seedlings and maximizing weed control.

54 Herbicides - Current Research and Case Studies in Use

tion), and removal by live organisms [30].

metolachlor in several well-water samplings.

each method used [31].

movement, characterizing herbicide lixiviation [29, 15].

Almeida [35], carried out detailed s-triazine sorption/ desorption studies on different soils from the region of Ubatuba municipal district, State of São Paulo, Brazil. The authors reported that potential herbicide lixiviation and/or superficial runoff would depend on the intrinsic soil characteristics and that the herbicide recommendation must be supported and evaluated based on such soil attributes. Furthermore, the authors observed high s-triazine sorption and consequently lower lixiviation potential in high organic-C content soils; and low herbicide sorption in low C-content soils, favoring desorption and increasing the potential risk of subsoil contamination. They concluded that the soil organic-C content is directly related to the striazine sorption and it might be an important indicator of herbicide lixiviation potential, corroborating the results observed in [36].

### **6. Determination of herbicide persistence and lixiviation: Simazine, atrazine and metolachlor**

Blanco [37], determined herbicide persistence and lixiviation up to 50 cm soil depth, using gaschromatography, in a field experiment with simazine applied as a pre-emergent herbicide in maize at the rate of 3 kg ha-1 (a.i. = active ingredient), in the State of São Paulo, Brazil. The results obtained are described as follows:

**Figure 3.** Simazine residue means determined in several soil depth samples (layers from 0-10 until 40-50 cm), collect‐ ed in different sampling dates [37].

The highest simazine concentration was found in the 0-10 cm superficial soil layer (Figure 3) and decreasing simazine concentrations were found in deeper layers (30-40 cm), 14 until 65 days after treatment (DAT), but at levels near the method detection limit (0.05 mg.kg-1). No simazine residue was found in the 20-30 and 30-40 cm layers, 100 DAT. Simazine persisted in the 0-10 cm layer until 360 DAT in concentrations near the method detection limit. At 10-20 cm layer, simazine persisted until 100 DAT, and afterwards (127 and 183 DAT), only residues near the detection limit were found. The simazine persistence curve was obtained by regression analysis, considering the total residue data in the soil profile (0-50 cm depth, Figure 4).

Dawson [41], found simazine residues one year after the last annual application (of a total of six applications) in the 10-20 cm depth layer; Albers and Homburg cited by [44], also found

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In this experiment, [37] observed that the soil solution pH varied from 6.8 to 5.3 in soil samples; and the simazine pK(21°C) = 1.7 indicated that, under these conditions and despite simazine being a weak base, most herbicide molecules would be in the molecular form (only 0.006% would be ionized). According to [45, 46], simazine presents log Kow = 1.51 characterizing its lipophilic property, and increasing the chances of herbicide molecule sorption by soil colloids. Gast [13] cited by [30], demonstrated that simazine mobility is affected by soil organic matter (OM). In soil columns with 27 to 30% of OM, the herbicide did not percolate, but in sandy soils, herbicide lixiviation occurred until 17.50 cm depth. In field experiments, [39] found higher simazine concentrations below 30 cm than in the first 15 cm above, 16 months after application. These authors' results were related with the low soil OM (0-10 cm layer = 0.60% OM; and 40-50 cm layer = 0.19% OM) what might explain the simazine

In another research, following the same procedures, [47] evaluated the atrazine and metola‐ chlor herbicide persistence and lixiviation, applied pre-emergence to maize, as the commercial product Primestra at the rate of 8.0 L.ha-1 (1600 g ai atrazine + 2400 g ai metolachlor). The highest atrazine herbicide concentration was found restricted to the superficial soil layer (0-10 cm) (Figure 6). In the 10-20 cm depth layer, the herbicide was found only 15 DAT; and no residue was found in deeper layers until 380 DAT. Atrazine persistence was detected until 184 DAT. The atrazine persistence curve fitted an exponential equation obtained by regression analysis of the total residue data from 0 to 50 cm depth layers (Figure 7). The initial atrazine residue level was depleted very rapidly from soil and tended to stabilize 100 DAT, remaining constant

simazine movement below 15 cm depth for a six-month period in several soil types.

**Figure 5.** Daily rainfall occurred during the experiment period, January 14th, 1992 to January 8th, 1993, [37].

lixiviation until deeper soil layers (40 cm).

**Figure 4.** Simazine persistence curve determined until 360 days after treatment, applied as pre-emergent herbicide in maize crop [37].

The persistence curve (Figure 4) fitted an exponential equation, showing a fast decrease of soil simazine concentration until 120 DAT; and afterwards, a slower decreasing slope was observed until 360 DAT. These results might be explained by the rainfall distribution (Figure 3), because a dry period occurred between 112 and 215 DAT, causing adverse conditions to microbial development with consequent increased herbicide molecule adsorption and decreased availability/ dissipation. After 230 days, frequent rainfalls and high soil moisture favored dissipation by biotic agents and soil desorption, once the higher the soil moisture the higher molecule availability and dissipation; other dissipation types might also occur.

Researchers tended to confirm these results, that is, under different Brazilian conditions, simazine remained in the superficial soil layer [38 – 44]. Nevertheless, such affirmations must be supported with information on soil conditions and the triazine group that the studied molecule belongs to as well as on the field experiment local climate where the results were obtained.

days after treatment (DAT), but at levels near the method detection limit (0.05 mg.kg-1). No simazine residue was found in the 20-30 and 30-40 cm layers, 100 DAT. Simazine persisted in the 0-10 cm layer until 360 DAT in concentrations near the method detection limit. At 10-20 cm layer, simazine persisted until 100 DAT, and afterwards (127 and 183 DAT), only residues near the detection limit were found. The simazine persistence curve was obtained by regression analysis, considering the total residue data in the soil profile (0-50 cm depth, Figure 4).

56 Herbicides - Current Research and Case Studies in Use

**Figure 4.** Simazine persistence curve determined until 360 days after treatment, applied as pre-emergent herbicide in

The persistence curve (Figure 4) fitted an exponential equation, showing a fast decrease of soil simazine concentration until 120 DAT; and afterwards, a slower decreasing slope was observed until 360 DAT. These results might be explained by the rainfall distribution (Figure 3), because a dry period occurred between 112 and 215 DAT, causing adverse conditions to microbial development with consequent increased herbicide molecule adsorption and decreased availability/ dissipation. After 230 days, frequent rainfalls and high soil moisture favored dissipation by biotic agents and soil desorption, once the higher the soil moisture the higher

Researchers tended to confirm these results, that is, under different Brazilian conditions, simazine remained in the superficial soil layer [38 – 44]. Nevertheless, such affirmations must be supported with information on soil conditions and the triazine group that the studied molecule belongs to as well as on the field experiment local climate where the results were

molecule availability and dissipation; other dissipation types might also occur.

maize crop [37].

obtained.

**Figure 5.** Daily rainfall occurred during the experiment period, January 14th, 1992 to January 8th, 1993, [37].

Dawson [41], found simazine residues one year after the last annual application (of a total of six applications) in the 10-20 cm depth layer; Albers and Homburg cited by [44], also found simazine movement below 15 cm depth for a six-month period in several soil types.

In this experiment, [37] observed that the soil solution pH varied from 6.8 to 5.3 in soil samples; and the simazine pK(21°C) = 1.7 indicated that, under these conditions and despite simazine being a weak base, most herbicide molecules would be in the molecular form (only 0.006% would be ionized). According to [45, 46], simazine presents log Kow = 1.51 characterizing its lipophilic property, and increasing the chances of herbicide molecule sorption by soil colloids.

Gast [13] cited by [30], demonstrated that simazine mobility is affected by soil organic matter (OM). In soil columns with 27 to 30% of OM, the herbicide did not percolate, but in sandy soils, herbicide lixiviation occurred until 17.50 cm depth. In field experiments, [39] found higher simazine concentrations below 30 cm than in the first 15 cm above, 16 months after application. These authors' results were related with the low soil OM (0-10 cm layer = 0.60% OM; and 40-50 cm layer = 0.19% OM) what might explain the simazine lixiviation until deeper soil layers (40 cm).

In another research, following the same procedures, [47] evaluated the atrazine and metola‐ chlor herbicide persistence and lixiviation, applied pre-emergence to maize, as the commercial product Primestra at the rate of 8.0 L.ha-1 (1600 g ai atrazine + 2400 g ai metolachlor). The highest atrazine herbicide concentration was found restricted to the superficial soil layer (0-10 cm) (Figure 6). In the 10-20 cm depth layer, the herbicide was found only 15 DAT; and no residue was found in deeper layers until 380 DAT. Atrazine persistence was detected until 184 DAT.

The atrazine persistence curve fitted an exponential equation obtained by regression analysis of the total residue data from 0 to 50 cm depth layers (Figure 7). The initial atrazine residue level was depleted very rapidly from soil and tended to stabilize 100 DAT, remaining constant

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

380 DAT.

**Metolachlor in the soil (mg kg-1)**

0 15 36 65 100 127 184 380 **Days after treatment (DAT)**

**Figure 8.** Average metolachlor values found in different soil depth layers and sampling dates, in maize crop [47].

persistence curve fitted an exponential equation (Figure 9).

**Figure 9.** Metolachlor herbicide persistence, applied pre-emergence to maize [47].

Regression analysis was applied to the total residue data up to the 50 cm depth and the

A rapid decrease of metolachlor residue concentrations were observed until 100 DAT (0.20 mg kg-1), and afterwards it tended to stabilize reaching the method detection limit (0.05 mg kg-1)

The rainfall regime is presented in Figure 10. In the experiment beginning, rainfalls were not abundant favoring metolachlor sorption and immobilization on soil colloids, and thus,

0-10 10-20 20-30 30-40 40-50

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**Figure 6.** Average atrazine values found in different soil depth layers and sampling dates, in maize crop [47].

until 184 DAT. Afterwards, it tended to zero, and it was not detected at any other sampling dates.

**Figure 7.** Atrazine herbicide persistence, applied in pre-emergence to maize crop [47].

The metolachlor persistence curve (Figure 8) was similar to the atrazine curve, showing higher residue concentration in the 0-10 cm depth layer. However, metolachlor persistence differed from atrazine due to the fact that it was detected until 380 DAT, and also, because metolachlor lixiviated until 20-30 cm and 10-20 cm depth, 15 and 100 DAT, respectively.

**Figure 8.** Average metolachlor values found in different soil depth layers and sampling dates, in maize crop [47].

Regression analysis was applied to the total residue data up to the 50 cm depth and the persistence curve fitted an exponential equation (Figure 9).

**Figure 9.** Metolachlor herbicide persistence, applied pre-emergence to maize [47].

until 184 DAT. Afterwards, it tended to zero, and it was not detected at any other sampling

**Figure 6.** Average atrazine values found in different soil depth layers and sampling dates, in maize crop [47].

0 15 36 65 100 127 184 380 **Days after treatment (DAT)**

0-10 10-20 20-30 30-40 40-50

soil layer depth (cm)

The metolachlor persistence curve (Figure 8) was similar to the atrazine curve, showing higher residue concentration in the 0-10 cm depth layer. However, metolachlor persistence differed from atrazine due to the fact that it was detected until 380 DAT, and also, because metolachlor

**Figure 7.** Atrazine herbicide persistence, applied in pre-emergence to maize crop [47].

lixiviated until 20-30 cm and 10-20 cm depth, 15 and 100 DAT, respectively.

dates.

0

0,2

0,4

0,6

**Atrazine in the soil (mg kg-1)**

0,8

1

1,2

58 Herbicides - Current Research and Case Studies in Use

A rapid decrease of metolachlor residue concentrations were observed until 100 DAT (0.20 mg kg-1), and afterwards it tended to stabilize reaching the method detection limit (0.05 mg kg-1) 380 DAT.

The rainfall regime is presented in Figure 10. In the experiment beginning, rainfalls were not abundant favoring metolachlor sorption and immobilization on soil colloids, and thus, reducing the dissipation factors. The frequent and abundant rainfalls observed 220 DAT favored metolachlor desorption; its molecules were released in the soil solution and entered through dissipation processes and, consequently, the metolachlor concentration was fast depleted from the soil solution.

atrazine that is largely studied in foreign countries. However, data from foreign countries

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For example, [48] studied atrazine dissipation in a clayey loam type soil cropped with maize in England (with atrazine rates of 1.10 and 3.30 kg ha-1) and observed an exponential atrazine dissipation, but longer half-life (3 to 3.6 months), much different from the half-life found by

It is described in the paper [49], studying atrazine degradation in field soils of Spain, found a half-life of 30 days, and demonstrated the microbial and chemical nature of atrazine degrada‐ tion, corroborating the results reported by [11]. The latter authors affirmed there is a strong relationship between s-triazines' inactivation and optimal conditions for microbial community growth. Nevertheless, several soil factors such as increasing soil temperature and moisture, low pH and high soil organic matter content usually favor triazine chemical degradation by

The foreign literature has cited metolachlor (acetanilide group) as the most persistent herbicide in soils, superior to propachlor and alachlor. [50] and [28] reported metalochlor half-life of 33 and 15 days for sandy loam soils and clayey loam soils, respectively, both soils under 80% of water field capacity. Results reported in [47], found similar metalochlor half-life (11.16 days)

Many authors reported metolachlor degradation as an essentially microbial degradation type [51-54]; the soil organic matter is preponderant to metolachlor dissipation because this herbicide shows lipophilic molecule characteristics (log Kow > 3) and it is strongly adsorbed in high OM-soils [45, 55]; thus, explaining the metalochlor lixiviation observed in low OM-soil

When herbicide persistence is determined through biological methods, a specific susceptible test plant is used as an indicator. For that, the test plant is submitted to herbicide residue and the time period of herbicide bioactivity is evaluated as well as its molecule impact on the environment. Since test plants are more susceptible than crop plants, it is possible to estimate the time period that an herbicide is potentially active in the soil to cause damage to susceptible

**7. Determination of mesotrione and tembotrione herbicide persistence in**

Results described in [56], evaluated the tembotrione and mesotrione persistences, applied at two rates, as post-emergent herbicides to maize under different planting systems, using beetroot (*Beta vulgaris*, Early Wonder cv) as a test plant. Soil samples from the field experiment were collected at predetermined dates and used to grow potted test plants under growthchamber conditions (Conviron phytotron, PVG386 model). After 14 days, plants were cut above the soil and evaluated for shoot fresh matter. The treatment means with and without

[45] under Brazilian conditions for the same herbicide (13.58 days) (Figure 7).

cannot be extrapolated to Brazilian soil and climate conditions.

hydrolysis [11].

**soils**

in clayey loam soil (Figure 9).

until 30 cm depth reported by [47] (Figure 8).

crop plants in succession to the previously treated crop [31].

(control) herbicide were compared by *t* test at 0.05 (t5%).

**Figure 10.** Daily rainfall occurred during the experiment period, January 14th, 1992 to January 20th, 1993 [47].

Blanco et. al [37, 47] carried out field experiments in the same period and edaphoclimatic conditions, allowing the comparison between simazine and metolachlor results: metolachlor presented higher persistence (380 DAT) than atrazine (184 DAT), and this latter showed lesser lixiviation (until 20 cm depth), once metolachlor and simazine lixiviated until 30 and 40 cm depth, respectively.

From these results it might also be inferred that when these herbicides are sequentially used in successive crops, undesirable product residue amount might accumulate in the soil. For instance, at maize harvest (100-120 days after sowing), significant herbicide residual concen‐ trations might be left until the next crop sowing date, causing damage to the environment and plants as well as promoting plant resistance to herbicides.

In the research described in item [56] used bioassay methods to evaluate the atrazine persis‐ tence applied as post-emergent herbicide in maize at rates of 1000 and 2000 g ha-1 and observed that persistence ended 56 DAT, independently of the atrazine rate. Although comparing different methods, the above result was similar to the one presented in Figure 7, where the end of atrazine persistence was found 83 DAT, determined by gas-chromatography.

The edaphoclimatic condition effects on herbicide persistence in soils are well-known. Soil and climate conditions may directly alter the herbicide persistence or impair different degradation routes in many ways, whatever biotic (caused by microorganisms) or abiotic processes occur. Little Brazilian literature is found concerning the environmental impact caused by herbicide persistence, dissipation and lixiviation, when compared to foreign literature, especially about atrazine that is largely studied in foreign countries. However, data from foreign countries cannot be extrapolated to Brazilian soil and climate conditions.

reducing the dissipation factors. The frequent and abundant rainfalls observed 220 DAT favored metolachlor desorption; its molecules were released in the soil solution and entered through dissipation processes and, consequently, the metolachlor concentration was fast

**Figure 10.** Daily rainfall occurred during the experiment period, January 14th, 1992 to January 20th, 1993 [47].

Blanco et. al [37, 47] carried out field experiments in the same period and edaphoclimatic conditions, allowing the comparison between simazine and metolachlor results: metolachlor presented higher persistence (380 DAT) than atrazine (184 DAT), and this latter showed lesser lixiviation (until 20 cm depth), once metolachlor and simazine lixiviated until 30 and 40 cm

From these results it might also be inferred that when these herbicides are sequentially used in successive crops, undesirable product residue amount might accumulate in the soil. For instance, at maize harvest (100-120 days after sowing), significant herbicide residual concen‐ trations might be left until the next crop sowing date, causing damage to the environment and

In the research described in item [56] used bioassay methods to evaluate the atrazine persis‐ tence applied as post-emergent herbicide in maize at rates of 1000 and 2000 g ha-1 and observed that persistence ended 56 DAT, independently of the atrazine rate. Although comparing different methods, the above result was similar to the one presented in Figure 7, where the end

The edaphoclimatic condition effects on herbicide persistence in soils are well-known. Soil and climate conditions may directly alter the herbicide persistence or impair different degradation routes in many ways, whatever biotic (caused by microorganisms) or abiotic processes occur. Little Brazilian literature is found concerning the environmental impact caused by herbicide persistence, dissipation and lixiviation, when compared to foreign literature, especially about

of atrazine persistence was found 83 DAT, determined by gas-chromatography.

plants as well as promoting plant resistance to herbicides.

depleted from the soil solution.

60 Herbicides - Current Research and Case Studies in Use

depth, respectively.

For example, [48] studied atrazine dissipation in a clayey loam type soil cropped with maize in England (with atrazine rates of 1.10 and 3.30 kg ha-1) and observed an exponential atrazine dissipation, but longer half-life (3 to 3.6 months), much different from the half-life found by [45] under Brazilian conditions for the same herbicide (13.58 days) (Figure 7).

It is described in the paper [49], studying atrazine degradation in field soils of Spain, found a half-life of 30 days, and demonstrated the microbial and chemical nature of atrazine degrada‐ tion, corroborating the results reported by [11]. The latter authors affirmed there is a strong relationship between s-triazines' inactivation and optimal conditions for microbial community growth. Nevertheless, several soil factors such as increasing soil temperature and moisture, low pH and high soil organic matter content usually favor triazine chemical degradation by hydrolysis [11].

The foreign literature has cited metolachlor (acetanilide group) as the most persistent herbicide in soils, superior to propachlor and alachlor. [50] and [28] reported metalochlor half-life of 33 and 15 days for sandy loam soils and clayey loam soils, respectively, both soils under 80% of water field capacity. Results reported in [47], found similar metalochlor half-life (11.16 days) in clayey loam soil (Figure 9).

Many authors reported metolachlor degradation as an essentially microbial degradation type [51-54]; the soil organic matter is preponderant to metolachlor dissipation because this herbicide shows lipophilic molecule characteristics (log Kow > 3) and it is strongly adsorbed in high OM-soils [45, 55]; thus, explaining the metalochlor lixiviation observed in low OM-soil until 30 cm depth reported by [47] (Figure 8).

When herbicide persistence is determined through biological methods, a specific susceptible test plant is used as an indicator. For that, the test plant is submitted to herbicide residue and the time period of herbicide bioactivity is evaluated as well as its molecule impact on the environment. Since test plants are more susceptible than crop plants, it is possible to estimate the time period that an herbicide is potentially active in the soil to cause damage to susceptible crop plants in succession to the previously treated crop [31].

### **7. Determination of mesotrione and tembotrione herbicide persistence in soils**

Results described in [56], evaluated the tembotrione and mesotrione persistences, applied at two rates, as post-emergent herbicides to maize under different planting systems, using beetroot (*Beta vulgaris*, Early Wonder cv) as a test plant. Soil samples from the field experiment were collected at predetermined dates and used to grow potted test plants under growthchamber conditions (Conviron phytotron, PVG386 model). After 14 days, plants were cut above the soil and evaluated for shoot fresh matter. The treatment means with and without (control) herbicide were compared by *t* test at 0.05 (t5%).

In this way, bioassays with test plants were used to determine tembotrione and mesotrione soil persistence during four consecutive field experiments.

The rainfall regime during the field experiment is shown in Figure 12. In the beginning of the experiment less frequent and little rainfall occurred. Despite the considerable 140 mm rainfall peak volume between 30 and 40 DAT, the favorable situation did not persist and it was followed by a 130 day-dry period. This fact favored herbicide sorption to soil colloids making

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63

0 14 28 44 58 84 114 149 177 205 237

0 50 100 150 200

**Figure 12.** Rainfall distribution observed during the experiment period described in Figure 11. [56]

persistence end for the second rate (384 g ha-1).

tembotrione persistence 75 DAT.

**Days after treatments (DAT)**

Such rainfall distribution explained the slow mesotrione dissipation during the initial dry period because the herbicide final persistence was only found 114 DAT, for the lower treatment rate. When rainfall started 130 DAT, mesotrione desorption was favored, increasing its availability, followed by its depletion from the soil solution through dissipation processes. At this point, the test plants were not affected anymore (177 DAT), indicating the mesotrione

The results obtained with test plants grown in soil samples with residual tembotrione from the "safrinha" field corn crop (medium texture soil, pH 5.1 and OM = 1.1%) are presented in

The beetroot shoot fresh matter for different soil sampling periods (Figure 13) showed that these susceptible plants started to grow after the third soil sampling (32 DAT). This means that the null hypothesis (H0) for the rate of 100.8 g ha-1 was rejected at this time (significant differences between treatment and control means were found by t test 0.05). The null hypoth‐ esis (H0) was only accepted between 55 and 120 DAT, meaning that no significant differences in plant growth among treatments and control were observed at this time, and that the tembotrione persistence ended 55 DAT for the first rate (100.8 g ha-1). For the second rate (201.6 g ha-1), the test plant growth occurred between 75 and 120 DAT, evidencing the end of

it unavailable in the soil solution and restricting the dissipation processes.

0

Figure 13.

20

40

60

80

**Rainfall (mm)** 

100

120

140

*Tembotrione* (2-{2-chloro-4-mesil-3-[(2,2,2-trifluoroetoxi) metil]benzoil} ciclohexane -1,3 dione), solubility = 28 mg L-1, pKa= 4.22, and *mesotrione* (2-(4-mesyl-2-nitrobenzoyl)cyclohex‐ ane-1,3-dione), solubility = 168.7 mg L-1, pKa = 3.07, is an herbicide from the triketone group. The herbicide mechanism of action is the inhibition of the hydroxyphenylpyruvate-dioxyge‐ nase enzyme impairing carotenoids biosynthesis and destroying cellular membranes, leading to the death of susceptible plants.

In Brazil, they are indicated as post-emergent herbicides in both maize growth periods (fullseason harvest and little harvest or "safrinha" corn).

### **8. Mesotrione and tembotrione herbicide persistence determination in "safrinha" corn**

The bioassay was carried out in potted test plants grown in medium texture soil (pH 4.9 and 3% OM), treated with two mesotrione rates (192 and 384 g ha-1). The results (Figure 9) showed that beetroot plants were able to grow and develop only after the sixth soil sampling (84 DAT), with the lower herbicide rate. With the double rate, the test plants grew only 114 DAT. From then on, plants showed increasing shoot fresh matter yields in both treatments, until the moment when no significant differences were found between the control and treated plants (H0 - null hypothesis accepted). Therefore, the end of mesotrione persistence was determined 114 DAT and 177 DAT for the first and second rates (192 and 384 g ha-1), respectively.

**Figure 11.** Residual effects of mesotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were compared by t test (0.05). [56].

The rainfall regime during the field experiment is shown in Figure 12. In the beginning of the experiment less frequent and little rainfall occurred. Despite the considerable 140 mm rainfall peak volume between 30 and 40 DAT, the favorable situation did not persist and it was followed by a 130 day-dry period. This fact favored herbicide sorption to soil colloids making it unavailable in the soil solution and restricting the dissipation processes.

In this way, bioassays with test plants were used to determine tembotrione and mesotrione

*Tembotrione* (2-{2-chloro-4-mesil-3-[(2,2,2-trifluoroetoxi) metil]benzoil} ciclohexane -1,3 dione), solubility = 28 mg L-1, pKa= 4.22, and *mesotrione* (2-(4-mesyl-2-nitrobenzoyl)cyclohex‐ ane-1,3-dione), solubility = 168.7 mg L-1, pKa = 3.07, is an herbicide from the triketone group. The herbicide mechanism of action is the inhibition of the hydroxyphenylpyruvate-dioxyge‐ nase enzyme impairing carotenoids biosynthesis and destroying cellular membranes, leading

In Brazil, they are indicated as post-emergent herbicides in both maize growth periods (full-

**8. Mesotrione and tembotrione herbicide persistence determination in**

The bioassay was carried out in potted test plants grown in medium texture soil (pH 4.9 and 3% OM), treated with two mesotrione rates (192 and 384 g ha-1). The results (Figure 9) showed that beetroot plants were able to grow and develop only after the sixth soil sampling (84 DAT), with the lower herbicide rate. With the double rate, the test plants grew only 114 DAT. From then on, plants showed increasing shoot fresh matter yields in both treatments, until the moment when no significant differences were found between the control and treated plants (H0 - null hypothesis accepted). Therefore, the end of mesotrione persistence was determined

114 DAT and 177 DAT for the first and second rates (192 and 384 g ha-1), respectively.

84

114

**\***

0 50 100 150 200 250 **Days after treatment (DAT) Control mesotrione192 gha-1 mesotrione384 g ha-1**

**Figure 11.** Residual effects of mesotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were compared by t test

149

**\***

177

**\*** Accepted H0

**\***

**\***

205

\*

**\***

237

**\* \***

soil persistence during four consecutive field experiments.

season harvest and little harvest or "safrinha" corn).

to the death of susceptible plants.

62 Herbicides - Current Research and Case Studies in Use

**"safrinha" corn**

0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

**Beetroot shootfresh**

(0.05). [56].

**matter (g)**

14

28

44 58

**Figure 12.** Rainfall distribution observed during the experiment period described in Figure 11. [56]

Such rainfall distribution explained the slow mesotrione dissipation during the initial dry period because the herbicide final persistence was only found 114 DAT, for the lower treatment rate. When rainfall started 130 DAT, mesotrione desorption was favored, increasing its availability, followed by its depletion from the soil solution through dissipation processes. At this point, the test plants were not affected anymore (177 DAT), indicating the mesotrione persistence end for the second rate (384 g ha-1).

The results obtained with test plants grown in soil samples with residual tembotrione from the "safrinha" field corn crop (medium texture soil, pH 5.1 and OM = 1.1%) are presented in Figure 13.

The beetroot shoot fresh matter for different soil sampling periods (Figure 13) showed that these susceptible plants started to grow after the third soil sampling (32 DAT). This means that the null hypothesis (H0) for the rate of 100.8 g ha-1 was rejected at this time (significant differences between treatment and control means were found by t test 0.05). The null hypoth‐ esis (H0) was only accepted between 55 and 120 DAT, meaning that no significant differences in plant growth among treatments and control were observed at this time, and that the tembotrione persistence ended 55 DAT for the first rate (100.8 g ha-1). For the second rate (201.6 g ha-1), the test plant growth occurred between 75 and 120 DAT, evidencing the end of tembotrione persistence 75 DAT.

Although both experiments were carried out under "safrinha" fall conditions (dry season), the mesotrione and tembotrione persistence results (Figures 11 and 13) cannot be compared to each other, because different rainfall regimes occurred during the two field experiments (Figures 12 and 14). Therefore, a third experiment was carried out in a medium texture soil (pH 6.6 and OM = 3%), also under fall conditions ("safrinha" corn) as presented in Figure 15.

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65

**Figure 15.** Residual effects of mesotrione and tembotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were com‐

The herbicides tembotrione and mesotrione were observed to differently affect the beetroot

The mesotrione residual effect of the first rate (192 g ha-1) actually restricted the susceptible plant growth until 45 DAT, meanwhile the tembotrione residues did not restrict plant growth, except for the period 0-30 DAT at the second rate (201.6 g ha-1). These differences were pointed out by the null hypothesis analysis (Figure 15), which indicated significant contrast differences between the control and the herbicide treatments. The analysis also indicated that tembotrione persistence ended 60 DAT and mesotrione persistence ended 129 DAT, independently of both

The rainfall regime during the experiment period (Figure 16) showed that the rain volume and intensity until 75 DAT favored tembotrione dissipation that was completely depleted from soil solution 60 DAT, and from then on, did not affect beetroot plant growth (Figure 15). A dry

shoot fresh matter during the experiment time period (Figure 15).

pared by t test (0.05). [56].

herbicide rates.

**Figure 13.** Residual effects of tembotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were compared by t test (0.05). [56]

The rainfall regime during the experiment (Figure 14) showed frequent and abundant rains in the period beginning, and consequently, the high soil moisture favored herbicide release in the soil solution and its subsequent rapid dissipation. This fact explains the low soil herbicide persistence - 55 and 75 DAT - obtained for the first (100.8 g ha-1) and second doses (201.6 g ha-1), respectively. The soil moisture favorable conditions persisted until 70 DAT, almost coincident with the second rate persistence end (75 DAT).

**Figure 14.** Rainfall regime during the experiment period described in Figure 13. [56]

Although both experiments were carried out under "safrinha" fall conditions (dry season), the mesotrione and tembotrione persistence results (Figures 11 and 13) cannot be compared to each other, because different rainfall regimes occurred during the two field experiments (Figures 12 and 14). Therefore, a third experiment was carried out in a medium texture soil (pH 6.6 and OM = 3%), also under fall conditions ("safrinha" corn) as presented in Figure 15.

The rainfall regime during the experiment (Figure 14) showed frequent and abundant rains in the period beginning, and consequently, the high soil moisture favored herbicide release in the soil solution and its subsequent rapid dissipation. This fact explains the low soil herbicide persistence - 55 and 75 DAT - obtained for the first (100.8 g ha-1) and second doses (201.6 g ha-1), respectively. The soil moisture favorable conditions persisted until 70 DAT, almost

**Figure 13.** Residual effects of tembotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were compared by t

coincident with the second rate persistence end (75 DAT).

test (0.05). [56]

64 Herbicides - Current Research and Case Studies in Use

**Figure 14.** Rainfall regime during the experiment period described in Figure 13. [56]

**Figure 15.** Residual effects of mesotrione and tembotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were com‐ pared by t test (0.05). [56].

The herbicides tembotrione and mesotrione were observed to differently affect the beetroot shoot fresh matter during the experiment time period (Figure 15).

The mesotrione residual effect of the first rate (192 g ha-1) actually restricted the susceptible plant growth until 45 DAT, meanwhile the tembotrione residues did not restrict plant growth, except for the period 0-30 DAT at the second rate (201.6 g ha-1). These differences were pointed out by the null hypothesis analysis (Figure 15), which indicated significant contrast differences between the control and the herbicide treatments. The analysis also indicated that tembotrione persistence ended 60 DAT and mesotrione persistence ended 129 DAT, independently of both herbicide rates.

The rainfall regime during the experiment period (Figure 16) showed that the rain volume and intensity until 75 DAT favored tembotrione dissipation that was completely depleted from soil solution 60 DAT, and from then on, did not affect beetroot plant growth (Figure 15). A dry period occurred from 75 to 115 DAT, which restricted mesotrione dissipation and favored its molecule sorption on soil colloids. After that period, new rainfalls caused fast mesotrione dissipation, evidenced by the persistence end 129 DAT.

**Figure 16.** Rainfall regime occurred during the experiment period described in Figure 15. [56]

### **9. Herbicide persistence determination under full-season cropping conditions**

Bailey & Coffey [54] complemented the research work and carried out the same trials during the full-season maize crop, occurred during spring/summer seasons.

The rainfall regime during the experiment period (Figure 18) indicated a typical condition observed during full-season maize crop in the State of São Paulo, Brazil, with frequent and

**Figure 17.** Residual effects of mesotrione and tembotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were com‐

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67

1 35 56 83 99 132

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140

**Days after treatment (DAT)** rain sampling

**Figure 18.** Rainfall regime observed during the experiment period described in Figure 17 [56].

abundant rains.

pared by t test (0.05). [56]

**Rainfall (mm)**

The results obtained with test plants grown in soil samples with residual mesotrione and tembotrione (applied to a full-season maize crop, grown in a medium texture soil, pH 5.9 and OM = 2.5%) are presented in Figure 17.

The results indicated that beetroot plants (shoot fresh matter) grown in soil samples with tembotrione residues did not differ from the control plants 56 DAT, independently of the herbicide rate, until the end of the experiment (132 DAT). Plants grown in soil samples with mesotrione residues (first rate = 144 g ha-1) did not differ from the control plants 83 DAT until the end of experiment (132 DAT). However, plants grown in soil samples treated with the second rate (288 g ha-1) were severely affected, except for the last sampling period, when test plants did not show any phytotoxicity symptoms (132 DAT).

Therefore, tembotrione persistence ended 56 DAT independently of the field rate applied; mesotrione persistence ended 83 and 132 DAT for the first and second rates applied to the field (144 and 288 g ha-1), respectively.

Herbicide — Soil Interactions, Applied to Maize Crop Under Brazilian Conditions http://dx.doi.org/10.5772/56006 67

period occurred from 75 to 115 DAT, which restricted mesotrione dissipation and favored its molecule sorption on soil colloids. After that period, new rainfalls caused fast mesotrione

0 10 20 30 40 50 60 70 80 90 100 110 120 130

**Days after treatment (DAT)**

**9. Herbicide persistence determination under full-season cropping**

Bailey & Coffey [54] complemented the research work and carried out the same trials during

The results obtained with test plants grown in soil samples with residual mesotrione and tembotrione (applied to a full-season maize crop, grown in a medium texture soil, pH 5.9 and

The results indicated that beetroot plants (shoot fresh matter) grown in soil samples with tembotrione residues did not differ from the control plants 56 DAT, independently of the herbicide rate, until the end of the experiment (132 DAT). Plants grown in soil samples with mesotrione residues (first rate = 144 g ha-1) did not differ from the control plants 83 DAT until the end of experiment (132 DAT). However, plants grown in soil samples treated with the second rate (288 g ha-1) were severely affected, except for the last sampling period, when test

Therefore, tembotrione persistence ended 56 DAT independently of the field rate applied; mesotrione persistence ended 83 and 132 DAT for the first and second rates applied to the field

**Figure 16.** Rainfall regime occurred during the experiment period described in Figure 15. [56]

the full-season maize crop, occurred during spring/summer seasons.

plants did not show any phytotoxicity symptoms (132 DAT).

dissipation, evidenced by the persistence end 129 DAT.

66 Herbicides - Current Research and Case Studies in Use

**conditions**

OM = 2.5%) are presented in Figure 17.

(144 and 288 g ha-1), respectively.

**mm de chuva**

**Figure 17.** Residual effects of mesotrione and tembotrione herbicides on potted beetroot plants, used as susceptible test plants, grown under growth-chamber conditions. Data is referred to shoot fresh matter (g) and means were com‐ pared by t test (0.05). [56]

The rainfall regime during the experiment period (Figure 18) indicated a typical condition observed during full-season maize crop in the State of São Paulo, Brazil, with frequent and abundant rains.

**Figure 18.** Rainfall regime observed during the experiment period described in Figure 17 [56].

The rainfall distribution favored lower herbicide sorption in soil colloids and higher availa‐ bility in the soil solution, and thus, the herbicides were easily subject to biological and/or chemical dissipation processes. This explains the shorter tembotrione persistence (56 DAT). However, longer mesotrione persistence was observed (83 DAT) for the first rate (144 g ha-1), which required one more rain period to be dissipated; and still longer (132 DAT) for the second rate (288 g ha-1) that required even another period of rain to be dissipated.

**Author details**

**References**

309-320.

ference, 8-12 1947.

1975. 10-12.

Technology 2007; 21(1) 559–566.

NY, 1999. Cooperative Extension NRAES-104.

Marcus Barifouse Matallo

Flavio Martins Garcia Blanco, Sydnei Dionisio Batista de Almeida and

Instituto Biológico de São Paulo, Centro Experimental, Campinas, Brazil

[1] Companhia Nacional de Abastecimento. CONAB: Acompanhamento da Safra Brasi‐ leira de Grãos:http://www.conab.gov.br/OlalaCMS/uploads/arquivos/ 12\_08\_27\_09\_50\_57\_boletim\_portugues\_agosto\_2012.pdf (accessed 10 October 2012)

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[2] Blanco, H. G.; Oliveira, D. A.; Araujo, J. B. M. Estudo sobre a competição das plantas daninhas na cultura do milho (Zea mays L.). I – Experimento para verificar onde re‐ alizar o controle do mato. Arquivos do Instituto Biológico, São Paulo 1973; 40(4)

[3] Blanco, H. G.; Haag, H. P.; Oliveira, D. A. Estudo sobre a competição das plantas daninhas na cultura do milho (Zea mays L.). II – Influência do mato na nutrição do

[4] Blanco, H. G.; Araujo, J. B. M.; Oliveira, D. A. Estudo sobre a competição das plantas daninhas na cultura do milho (Zea mays L.). IV – Determinação do período de com‐

[5] Blanco, H. G.; Oliveira, D. A.; Araujo, J. B. M. Estudo sobre a competição das plantas daninhas na cultura do milho (Zea mays L.). III – Controle do mato em faixas sobre a

[6] Sindicato Nacional da Indústria de Produtos para Defesa Agrícola. SINDAG: http:// www.sindag.com.br/noticia.php?News\_ID=2256 (accessed 10 October 2012)

[7] Hanson, N. S.; Past, present, and future in the North Central Weed Control: confer‐ ence. proceedings of the 4th Annual Meeting of the North Central Weed Control con‐

[8] Gianssi, L. & N. Reigner, N. The Value of Herbicides in U.S. Crop Production, Weed

[9] Grubinger, V. P.; Sustainable Vegetable Production From Start-Up To Market. Ithaca,

[10] Nalewaja, J. D. Herbicidal weed control uses energy efficiently. Weeds Today, Fall

linha da cultura. Arquivos do Instituto Biológico, São Paulo 1976; 43(1-2) 3-8.

petição. Arquivos do Instituto Biológico, São Paulo 1976; 45(3-4) 105-114.

milho. Arquivos do Instituto Biológico São Paulo 1974; 41(1) 5-14.

Beetroot plants showed similar susceptibility to both herbicides, but it is possible to infer that tembotrione has a shorter persistence in the soil than mesotrione, independently of the crop season, and that tembotrione provides less environmental impact and toxicity risk to succes‐ sive crops.

### **10. Current scenario in Brazil**

During the human evolution process, since the beginning of agriculture 7,000 years ago, man has continuously developed technology for that activity, which nowadays, is a highly technical agriculture. However, certain facts have made us think about Carl Gustav Jung's (1875-1961) citation: *"knowledge does not mean wisdom".*

When mesotrione and tembotrione herbicides, among others, were released in the market, one of the main highlighted advantages at that time was the lower rates required to control weeds, which would result in significantly less environmental impact and phytotoxicity risks to crops in rotation.

Nowadays, such advantage is being revealed, because with the advent of glyphosate-resistant transgenic soybeans, the first resistant weed biotypes started to appear. Currently, there is an increasing concern about glyphosate-resistant weed biotypes after transgenic maize release, which is also resistant to glyphosate. For this reason, a glyphosate mixture with other herbi‐ cides, or else a sequential application, has been recommended justified by the need for herbicide rotation or another option to control weeds.

Actually, there has been a tendency to go back to the past with all the old misconceptions and misdirections, that is, to recommend the use of residual herbicides with high environmental impact and risk to successive crops.

It seems that it would be imperative to put in practice not only an herbicide rotation, but also a rotation between transgenic and conventional crops in order to decrease the selection pressure over weed communities, attempting to more efficiently postpone the appearance of herbicide resistant weed biotypes.

This subject will certainly be the new challenge for weed science.

### **Author details**

The rainfall distribution favored lower herbicide sorption in soil colloids and higher availa‐ bility in the soil solution, and thus, the herbicides were easily subject to biological and/or chemical dissipation processes. This explains the shorter tembotrione persistence (56 DAT). However, longer mesotrione persistence was observed (83 DAT) for the first rate (144 g ha-1), which required one more rain period to be dissipated; and still longer (132 DAT) for the second

Beetroot plants showed similar susceptibility to both herbicides, but it is possible to infer that tembotrione has a shorter persistence in the soil than mesotrione, independently of the crop season, and that tembotrione provides less environmental impact and toxicity risk to succes‐

During the human evolution process, since the beginning of agriculture 7,000 years ago, man has continuously developed technology for that activity, which nowadays, is a highly technical agriculture. However, certain facts have made us think about Carl Gustav Jung's (1875-1961)

When mesotrione and tembotrione herbicides, among others, were released in the market, one of the main highlighted advantages at that time was the lower rates required to control weeds, which would result in significantly less environmental impact and phytotoxicity risks to crops

Nowadays, such advantage is being revealed, because with the advent of glyphosate-resistant transgenic soybeans, the first resistant weed biotypes started to appear. Currently, there is an increasing concern about glyphosate-resistant weed biotypes after transgenic maize release, which is also resistant to glyphosate. For this reason, a glyphosate mixture with other herbi‐ cides, or else a sequential application, has been recommended justified by the need for

Actually, there has been a tendency to go back to the past with all the old misconceptions and misdirections, that is, to recommend the use of residual herbicides with high environmental

It seems that it would be imperative to put in practice not only an herbicide rotation, but also a rotation between transgenic and conventional crops in order to decrease the selection pressure over weed communities, attempting to more efficiently postpone the appearance of

rate (288 g ha-1) that required even another period of rain to be dissipated.

sive crops.

in rotation.

**10. Current scenario in Brazil**

68 Herbicides - Current Research and Case Studies in Use

citation: *"knowledge does not mean wisdom".*

herbicide rotation or another option to control weeds.

This subject will certainly be the new challenge for weed science.

impact and risk to successive crops.

herbicide resistant weed biotypes.

Flavio Martins Garcia Blanco, Sydnei Dionisio Batista de Almeida and Marcus Barifouse Matallo

Instituto Biológico de São Paulo, Centro Experimental, Campinas, Brazil

### **References**


[11] Esser, H.O., Dupuis, G., Ebert, E., Vogel, C., Marco, G.J. S-triazines. In: P.C. Kearney & D.D.Kaufamn, ed. Herbicides: Chemistry, Degradation and Mode of Action, N.Y. 1975; 1(2) 129-208.

[28] Walker, A. & Brown, P.A. The relative persistence in soil of acetanilide herbicides.

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[29] Riley, D. Physical loss and redistribution of pesticides in the liquid phase. The British

[30] Helling, G.S. Movement of s-triazine herbicides in soils. Residue Reviews 1970; 32(1)

[31] Blanco, F. M. G.; Velini E. D.; Batista Filho, A. Persistence of Herbicide Sulfentrazone in Soil Cultivated with Sugarcane and Soy and Effect on Crop Rotation, Herbicides - Properties, Synthesis and Control of Weeds, Mohammed Naguib Abd El-Ghany Ha‐ saneen (Ed.), ISBN:978-953-307-803-8,InTech;2012.Availablefrom: http:// www.intechopen.com/books/herbicides-properties-synthesis-and-control-of-weeds/ persistence-of-herbicide-sulfentrazone-in-soil-cultivated-with-sugarcane-and-soy-

[32] Kenaka, E. E. Evaluation of the harzard of pesticides residues in the environment. In: Watson, D. L., Brown, A. W. A. (ed) Pesticides management and insecticides resist‐

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[34] Cerdeira, A.L.; Santos, N. A. G.; Ueta, J.; Shuhama, I. K.; Pessoa, M.C.P.Y.; Smith JR, S.; Lanchote, V. L. Atrazine in Water and Biodegradation in a Recharge Area of Guar‐ any Aquifer in Brazil. Bulletin of Environmental Contamination and Toxicology

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[36] Piccolo, A. & Conte, P.. Advances in nuclear magnetic resonance and infrared spec‐ troscopies of soil organic particles. In: Structure and Surface Reactions of Soil Parti‐ cles (eds P.M. Huang, N. Senesi & J. Buffle), Wiley-Interscience, New York, 1998,

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[11] Esser, H.O., Dupuis, G., Ebert, E., Vogel, C., Marco, G.J. S-triazines. In: P.C. Kearney & D.D.Kaufamn, ed. Herbicides: Chemistry, Degradation and Mode of Action, N.Y.

[12] Worthing, C. R. The Pestcide Manual. 7 ed. Croydon: The British Crop Council, 1983.

[13] Gast, A. Use and performance of triazines herbicides on major crops and major

[14] Dan Hess, F. Herbicide effects on plant structure, physiology, and biochemistry. In:

[15] Walker, A. Evaluation of simulation model for prediction of herbicide movement

[16] Kearney, P. C., Sheets, P. J., Smith, J. W. Volatility of seven s-triazines. Weed 1964;

[17] Blanco, H. G. Destino, comportamento e resíduos de herbicidas no solo. O Biológico

[18] Briggs, G. G. Degradation in soil.In: Persistence of insecticides and herbicides. The

[19] Briggs, G. G. Molecular structure of herbicide and their sortion by soil. Nature 1969;

[20] Walker, A. The fate and significance of herbicide residue in soil. In: Scientific horti‐

[21] Walker, A.; Allen, J. G. Influence of soil and environmental factors on pesticide. Soil

[22] Velini, E. D. Comportamento de herbicidas no solo. In: Simpósio Nacional Sobre Manejo Integrado de Plantas Daninhas em Hortaliças. FCA-UNESP, Botucatu, 1992.

[23] Harper, S. S. Sortion-desorption and herbicide behavior in soil. Rev. Weed Sci. 1994;

[24] Bailey, G. W., White, J. L. Factors influencing the adsorption, desorption, and move‐

[25] Hayes, M. H. B Adsorption of triazine herbicides on soil organic matter, including a short review on soil organic matter chemistry. Residue Reviews 1970; 32(1) 131-174.

[26] Weber, J. B., Weed, J. B., Ward, T. M. Adsorption of s-triazines by soil organic matter.

[27] Weber, J. B. Mechanism of adsorption of s-triazines by clay colloids and factors af‐

Pesticide interactions in crop production. CRC Press Inc. 1993. p13-34.

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[40] Clay. D.V., Mckone, C.E. The persistence of chlorthiamid, lenacil and simazine in un‐ cropped soil. British Weed Control Conference, 9, Brigthon, England 1968. Proceed‐ ings; 2(1) 933-938.

[54] Bailey, A. M. & Coffey, M. D. Characterization of microorganisms involved in accel‐ erated biodegradation of metalaxyl and metolachlor in soils. Can. J. Microbiol. 1986;

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[55] Peter, C. J. & Weber, J. B. Adsorption, mobility and efficacy of alachlor and metola‐

[56] Blanco, F. M. G.; Franco, G. V.; Ramos, Y. G. Persistência dos herbicidas Tembo‐ trione, mesotrione e atrazina aplicados na cultura do milho. In: 27º Congresso Brasi‐

leiro da Ciência das plantas daninhas. Ribeirão Preto, SP, 2010. p1738-1742

chlor as influenced by soil properties. Weed Sci. 1985; 33(1) 874-81.

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[54] Bailey, A. M. & Coffey, M. D. Characterization of microorganisms involved in accel‐ erated biodegradation of metalaxyl and metolachlor in soils. Can. J. Microbiol. 1986; 32(1) 562-569.

[40] Clay. D.V., Mckone, C.E. The persistence of chlorthiamid, lenacil and simazine in un‐ cropped soil. British Weed Control Conference, 9, Brigthon, England 1968. Proceed‐

[41] Dawson, J.H., Bruns, V.F., Clore, W.J. Residual monuron, diuron and simazine in a

[42] Kozlowski, T.T., Kuntz, J.E. Effects of simazine, atrazine, propazine, and Eptan on

[43] Kozaczenko, H. Factores affecting the efficiency of herbicides. Biul. Warzyw. 8 (31).

[44] Sheets, T.J. The comparative toxicities of monuron and simazine in soil. Weeds 1959;

[45] Briggs, G.G. Theoretical and experimental relationships between soil adsorption, oc‐ tanol - water partition coefficients, water solubilities, bioconcentration factors, and

[46] Briggs, G.G. Factors affecting the uptake of soil-applied chemicals by plants and oth‐ er organisms., Proceedings, symposium on soil and crop protection chemicals 1984;

[47] Blanco, F. M. G.; Machado, T. R. Persistence and leaching of atrazine and metolachlor in soil under corn. In: Third International Weed Science Congress. Fox do Iguassu,

[48] Frank, R. & Sirons, G. J. Dissipation of atrazine residues from soils. Bulletin of Envi‐

[49] Durand, G. & Barcelo, D. Environmental degradation of atrazine, linuron and feni‐ trothion in soil samples. Toxicological and Environmental Chemistry 1992; 36(3-4)

[50] Zindahl, R. L. & Clark, S. K. Degradation of three acetanilide herbicides in soils.

[51] Beestman, G. B. & Deming, J. M. Dissipation of acetanilide herbicides from soil.

[52] Mcgahen, L. L. & Tidge, J. M. Metabolism of two new acetanilide herbicides, Antor herbicides (H-22234) and Dual (metolachlor) by the soils fungus Chaetomiun globo‐

[53] Dermont, C. B.; Lavy, T. L.; Marx, D. B. Rate of metribuzin, metolachlor and fluome‐

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tron in soil. Weed Sci. 1982; 30(1) 629-632.

vineyard soil. Weed Sci. 1968; 16(1) 63-65.

1965. Apud. Weed Abstracts, 1966; 15 (1), 1780 p.

the parachor. J. Agric. Food Chem. 1981; 29(1) 1050-1059.

ronmental Contamination and Toxicology 1985; 34(4) 541-48.


**Chapter 4**

**Integration of Allelopathy to Control Weeds in Rice**

Rice (*Oryza sative* L.) is the main food crop in Asia and the staple food of the majority of the population in many regions of the world. The population pressure in rice-consuming countries demands that more attention be directed towards new approaches to sustainable rice produc‐ tion. Improvement of both crop quality and yield is an urgent task [1]. Optimally, rice yield improvement must be sought through agronomic approaches that are environmentally safe [2]. Weed management using allelopathy may effect a yield improvement without environ‐ mental cost, which is one of the most important considerations for worldwide scientists

Allelopathy is described as the ability of plants to inhibit or stimulate growth of other plants in the environment by exuding chemicals. The concept of allelopathy was first raised by Hans Molisch to describe both the beneficial and the detrimental chemical interactions of plants and microorganisms [3]. Since then, the term "allelopathy" has undergone several changes and it has been described as any direct or indirect harmful or beneficial effects of one plant on another through the production of chemical compounds that it releases into the environment [4]. The subject of allelopathy currently receives much attention from scientists; the increasing interest in allelopathy in recent years has been stimulated by the recognition that agro-ecological applications of allelopathy may provide alternatives to synthetic herbicides for weed man‐ agement [5] and with the evidence that allelopathy has the potential for weed control [6-7]. The overuse of agrochemicals has caused environmental degradation, pest tolerance and human health concerns. Agriculture worldwide is currently using about 3 million tons of herbicides annually, and herbicide-resistant weeds have become more prolific, which has further expanded the use of herbicides [8]. To solve these problems, it is necessary to develop

> © 2013 Khanh et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 Khanh et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

T.D. Khanh, L.H. Linh, T.H. Linh, N.T. Quan,

Additional information is available at the end of the chapter

T.D. Xuan

http://dx.doi.org/10.5772/56035

**1. Introduction**

D.M. Cuong, V.T.T. Hien, L.H. Ham, K.H. Trung and

working to secure the world's food supply for future generations.

## **Integration of Allelopathy to Control Weeds in Rice**

T.D. Khanh, L.H. Linh, T.H. Linh, N.T. Quan, D.M. Cuong, V.T.T. Hien, L.H. Ham, K.H. Trung and T.D. Xuan

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/56035

### **1. Introduction**

Rice (*Oryza sative* L.) is the main food crop in Asia and the staple food of the majority of the population in many regions of the world. The population pressure in rice-consuming countries demands that more attention be directed towards new approaches to sustainable rice produc‐ tion. Improvement of both crop quality and yield is an urgent task [1]. Optimally, rice yield improvement must be sought through agronomic approaches that are environmentally safe [2]. Weed management using allelopathy may effect a yield improvement without environ‐ mental cost, which is one of the most important considerations for worldwide scientists working to secure the world's food supply for future generations.

Allelopathy is described as the ability of plants to inhibit or stimulate growth of other plants in the environment by exuding chemicals. The concept of allelopathy was first raised by Hans Molisch to describe both the beneficial and the detrimental chemical interactions of plants and microorganisms [3]. Since then, the term "allelopathy" has undergone several changes and it has been described as any direct or indirect harmful or beneficial effects of one plant on another through the production of chemical compounds that it releases into the environment [4]. The subject of allelopathy currently receives much attention from scientists; the increasing interest in allelopathy in recent years has been stimulated by the recognition that agro-ecological applications of allelopathy may provide alternatives to synthetic herbicides for weed man‐ agement [5] and with the evidence that allelopathy has the potential for weed control [6-7].

The overuse of agrochemicals has caused environmental degradation, pest tolerance and human health concerns. Agriculture worldwide is currently using about 3 million tons of herbicides annually, and herbicide-resistant weeds have become more prolific, which has further expanded the use of herbicides [8]. To solve these problems, it is necessary to develop

© 2013 Khanh et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Khanh et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

sustainable weed management systems that may reduce both herbicide dependency and the burden of manual weeding. With attempts to exploit rice's allelopathic properties for weed control in rice growing, research into rice allelopathy was begun in the early 1970s and has been widely studied in the USA, Europe, Japan, Korea, India and China. If the allelopathic property of crops can be improved, it implies that the competitive ability of crops against weeds can be strengthened, the amount of applied herbicides lowered and environmental risks reduced. Improved crops' allelopathic potential may be useful for rice and all other crops [9]. Crop allelopathy may be a successful tool to manage weed infestations in agricultural production, if it can be exploited appropriately in a rotational cropping system [10]. However, in the case of rice, it is difficult to rotate different crops in a paddy field; therefore, enhancing weed suppression by rice itself may be among the most feasible means of controlling weeds. The isolation and identification of allelochemicals responsible for weed suppression by rice plants may be helpful for understanding the chemical interactions of rice. The introduction of allelopathic traits into cultivated rice via a breeding program may give the possibility of utilizing rice allelopathy in agricultural production.

ment and humans. Therefore, a new strategy for biological weed management in sustainable

Integration of Allelopathy to Control Weeds in Rice

http://dx.doi.org/10.5772/56035

77

*Ammannia* spp (Redstems) *Jussiaea decurrens* Walt.(Winged waterprimrose)

*Dactyloctenium aegyptium* L. Beauv (Crowfoot grass) *Leptochloa chinensis* L. Nees ( Red spangletop)

Agriculture worldwide has struggled to control weed interference and the appearance of herbicide-resistant weeds that require the development of new herbicides, and increasing doses of synthetic herbicides in practice. There are about 30000 species of weeds affecting food crops, which cause great losses of crop yields worldwide [17]. In the USA alone, about \$20 billion worth of crops are lost each year, accounting for 10% of production [18]. Many highyield crops have been bred, but this simultaneously increases the heavy dependence on agrochemicals. The desire for safer control of weeds with less environmental impact has become a worldwide concern. In this regard, integrating allelopathy can be a source of new methods for

Weeds compete with crops for nutrients, water, space, and requirements for photosynthesis, which reduces crop yield. Synthetic herbicides can control weeds effectively and reduce labor in weeding but can cause numerous detriments to the environment and humans, and increase

*Brachiaria mutica* Forssk(Bufallo grass) *Marsilea quadrifolia* L. (Waterclover) *Bacopa* spp.(Waterhyssops) *Monochoria vaginalis* Burm.f.(Monochoria) *Cyperus iria*. L (Ricefield flatsedge) *Murdannia nudiflora* L.(Nakedstem dewflower) *Cyperus difformis*.L (Dirty-dora) *Murdannia keisak* Hassk. (Wartremoving herb) *Commelina diffusa*. Burm (Dayflower) *Ischaemum rugosum* Salisb (Wrinkle grass)

*Dopatrium junceum* Roxb Hamilt (Horsefly's eye) *Lindernia pyxidaria* L. (Lindern)

*Echinochloa colonum* L. Link ( Shama millet) *Paspalum distichum* L.(Knotgrass) *Echinochloa crus-galli* L. Beauv (Barnyardgrass) *Leptochloa fascicularis* Lam.(Sprangletop) *Eleocharis acicularis* L. Roemer (Needle spikerush) *Rotala indica* Wild. (India toothcup) *Elatine triandra* Schkuhr (Waterwort) *Sagittaria longiloba* Engelm. (Arrow head) *Fimbristylis dichotoma* L. Vahl (Forked fimbry) *Sphenoclea zeylanica* Gaertin (Gooseweed)

*Fimbristylis miliacea* L. Vahl (Grasslike fimbry) *Scirpus mucronatus* L.(Bulrush) *Isachne globosa* Thumb (Chigozasa) *Salvinia molesta* Mitchel.(Kariba weed) *Heteranthera limosa* Sw.Willd (Ducksalad) *Scirpus juncoides* Ferm(Weakstalk bulrush)

agriculture should be developed.

**Table 1.** List of major rice weeds in paddy field

sustainability of agriculture systems.

**4. Weed control by allelopathy**

**3. Role of allelopathy in weed management**

**Botanical and common name**

The aims of this chapter are to present some aspects of integration of allelopathy to control weeds in rice that is pertinent to sustainable agriculture. The following points are discussed: (i) role of allelopathy in weed management; (ii) methodology of allelopathy utilization in rice; (iii) incorporation of higher plants with strong allelopathy to control weeds; (iv) developing allelochemicals and their derivatives for weed management; (v) effort to utilize rice allelopathy for rice weed control; (vi) benefits from allelopathy integrated into sustainable agriculture.

### **2. Rice weeds**

Weeds cause major yield losses in crops and also reduce their quality. Without weed man‐ agement, rice yield may be reduced by 16 to 86%, or even 100% [11]. Worldwide more than 1000 weed species have been reported in rice [12]. However, 13 species are the most serious weeds spp.: *Cyperus rotundus* L. (purple nutsedge), *Cynodon dactylon* (L.) Pers. (Bermunda grass), *Echinochloa crus-galli* (L.) Beauv (barnyardgrass), *Echinochloa colonum* (L.) Link. (jungle rice), *Eleusine indica* (L.) Gaertner (goosegrass), *Eichhornia crassipes* (Mart.) Solms (water hyacinth), *Portulaca oleracea* L. (purslane), *Chenopodium album* L. (lambsquarter), *Digitaria arvensis* L. (field bindweed), *Sorghum halepense* (L.) Pers. (Johnson grass), *Imperata cylindrical* (L.) Beauv. (spear grass), *Avena fatua* L. (wild oat), and *Amaranthus retroflexus* L. (redroot pigweed) [13-14]. The type of weed species to infest mainly depends on weather, temperature and latitude, and where the rice crop is grown. For instance in Australia, *Cyperus difformis* L. (dirty dora), *Elatine gratioloides* (waterwort), *D. minus* (starfruit) and *E. crus-galli* (L.) Beauv. (barnyardgrass) are major noxious weeds [15] (Table 1). The overuse of herbicides results in herbicide resistance in weeds, which cause more difficulties in weed management. Approxi‐ mately 200 weed biotypes from 125 different species worldwide have become resistant to herbicides [16]. Traditional weed management in rice was dependent on weather, water coverage and hand weeding. These methods are time-consuming and labor intensive, hence, current weed control depends on synthetic herbicides, but these are harmful to the environ‐ ment and humans. Therefore, a new strategy for biological weed management in sustainable agriculture should be developed.


**Table 1.** List of major rice weeds in paddy field

sustainable weed management systems that may reduce both herbicide dependency and the burden of manual weeding. With attempts to exploit rice's allelopathic properties for weed control in rice growing, research into rice allelopathy was begun in the early 1970s and has been widely studied in the USA, Europe, Japan, Korea, India and China. If the allelopathic property of crops can be improved, it implies that the competitive ability of crops against weeds can be strengthened, the amount of applied herbicides lowered and environmental risks reduced. Improved crops' allelopathic potential may be useful for rice and all other crops [9]. Crop allelopathy may be a successful tool to manage weed infestations in agricultural production, if it can be exploited appropriately in a rotational cropping system [10]. However, in the case of rice, it is difficult to rotate different crops in a paddy field; therefore, enhancing weed suppression by rice itself may be among the most feasible means of controlling weeds. The isolation and identification of allelochemicals responsible for weed suppression by rice plants may be helpful for understanding the chemical interactions of rice. The introduction of allelopathic traits into cultivated rice via a breeding program may give the possibility of

The aims of this chapter are to present some aspects of integration of allelopathy to control weeds in rice that is pertinent to sustainable agriculture. The following points are discussed: (i) role of allelopathy in weed management; (ii) methodology of allelopathy utilization in rice; (iii) incorporation of higher plants with strong allelopathy to control weeds; (iv) developing allelochemicals and their derivatives for weed management; (v) effort to utilize rice allelopathy for rice weed control; (vi) benefits from allelopathy integrated into sustainable agriculture.

Weeds cause major yield losses in crops and also reduce their quality. Without weed man‐ agement, rice yield may be reduced by 16 to 86%, or even 100% [11]. Worldwide more than 1000 weed species have been reported in rice [12]. However, 13 species are the most serious weeds spp.: *Cyperus rotundus* L. (purple nutsedge), *Cynodon dactylon* (L.) Pers. (Bermunda grass), *Echinochloa crus-galli* (L.) Beauv (barnyardgrass), *Echinochloa colonum* (L.) Link. (jungle rice), *Eleusine indica* (L.) Gaertner (goosegrass), *Eichhornia crassipes* (Mart.) Solms (water hyacinth), *Portulaca oleracea* L. (purslane), *Chenopodium album* L. (lambsquarter), *Digitaria arvensis* L. (field bindweed), *Sorghum halepense* (L.) Pers. (Johnson grass), *Imperata cylindrical* (L.) Beauv. (spear grass), *Avena fatua* L. (wild oat), and *Amaranthus retroflexus* L. (redroot pigweed) [13-14]. The type of weed species to infest mainly depends on weather, temperature and latitude, and where the rice crop is grown. For instance in Australia, *Cyperus difformis* L. (dirty dora), *Elatine gratioloides* (waterwort), *D. minus* (starfruit) and *E. crus-galli* (L.) Beauv. (barnyardgrass) are major noxious weeds [15] (Table 1). The overuse of herbicides results in herbicide resistance in weeds, which cause more difficulties in weed management. Approxi‐ mately 200 weed biotypes from 125 different species worldwide have become resistant to herbicides [16]. Traditional weed management in rice was dependent on weather, water coverage and hand weeding. These methods are time-consuming and labor intensive, hence, current weed control depends on synthetic herbicides, but these are harmful to the environ‐

utilizing rice allelopathy in agricultural production.

76 Herbicides - Current Research and Case Studies in Use

**2. Rice weeds**

### **3. Role of allelopathy in weed management**

Agriculture worldwide has struggled to control weed interference and the appearance of herbicide-resistant weeds that require the development of new herbicides, and increasing doses of synthetic herbicides in practice. There are about 30000 species of weeds affecting food crops, which cause great losses of crop yields worldwide [17]. In the USA alone, about \$20 billion worth of crops are lost each year, accounting for 10% of production [18]. Many highyield crops have been bred, but this simultaneously increases the heavy dependence on agrochemicals. The desire for safer control of weeds with less environmental impact has become a worldwide concern. In this regard, integrating allelopathy can be a source of new methods for sustainability of agriculture systems.

### **4. Weed control by allelopathy**

Weeds compete with crops for nutrients, water, space, and requirements for photosynthesis, which reduces crop yield. Synthetic herbicides can control weeds effectively and reduce labor in weeding but can cause numerous detriments to the environment and humans, and increase the occurrence of herbicide-resistant weeds. Since it is known that plants can self-regulate their densities and distribution in nature via allelopathic interactions, scientists have attempted to exploit these characteristics of crops and weeds in agriculture. The use of allelopathy for biological control of weeds in agriculture practice has attracted the interest of many agronomic scientists [1].

gramine or hyroxamic acids were useful for controlling fields with high aphid populations. Allelochemical interactions of plants–plants, plants–soils, plants-micro-organisms, and plant residues from a crop rotation play an active role in enhancing crop yields. Those allelochem‐ icals released from rotated crops then interacted with many physiological processes, which could help promote the growth and yield of crops. If plants used in a rotational system can be determined appropriately, the amount of chemical nitrogenous fertilizers is lowered and environmental hazard is reduced, whereas the sustainability of agriculture by substituting them with biologically fixed nitrogen from legumes is enhanced [31]. However, at present, negligible work has been done on the mode of action of allelochemicals in crop rotation, maybe due to their complicated transformation in nature. Moreover, Chou et al 1980 [77] reported 25% reduction in rice yield of second crop in Taiwan due to the phytotoxins produced during the decomposition of rice residues of first crop left in the soil. The phytotoxic effects of decomposing rice residues in the soil on the succeeding crop are problematic in some countries. In Southeast Asia, rotational systems give greater rice yield than rice monoculture and use of appropriate crops can also minimize the weed biomass significantly. In general, legume crops

Integration of Allelopathy to Control Weeds in Rice

http://dx.doi.org/10.5772/56035

79

are preferred as preceding crops to suppress the weeds in succeeding rice crops [1].

The term 'cover crop' is defined as crops cultivated with regular cropping for soil and moisture conservation, promotion of nutrient recycling, biomass production, temperature lowering, nuisance weed inhibition, and forage supply [32, 33, 34]. Cover crops may be referred to as either green manure crops or sometimes implied catch crops [35]. Popular allelopathic crops used as cover crops are: barley (*Hordeum vulgare*), sorghum (*Sorghum* spp.), maize (*Z. mays*), wheat (*T. aestivum*), rye (*S. cereale*), buckwheat. (*Fagoprum esculentum*), velvetbean (*M. pruri‐ ens*), crimson clover (*Trifolium incarnatum*), subterranean clover (*Trifolium subterraneum*), hairy vetch (*Vicia vilosa*) sweet potato (*I. batatas*), and convolvulaceae (*Tricolor batatas*) [32]. These allelopathic plants exhibited significant weed reduction [36-37]. Excluding phytotoxins released from cover crops into soil, shading effects of the cover crops as well as their thick and dense population, and fast growth could effectively suppress weeds [38]. Legume species and some cruciferous plants could improve soil fertility contributing organic matter and nitrogen to the soil. Successfully established cover crops can develop sufficiently dense canopies in the autumn to interfere with growth of perennial and winter annual weeds [39]. Application of green manure crops can enhance soil organic matter and reduce weed growth. Some plants are used as green manures, including: *Mucuna* spp., *Canavalia* spp., *Trifolium* spp., *Brassica* spp., and *Ipomoea* spp. [32]. Several non-leguminous plants belonging to the family of Brassicaceae, such as field mustard (*Brassica campestris*), white or yellow mustard (*Brassica hirta*), brown/ Indian mustard (*Brassica nigra*), rapeseed/soilseed rape/canola (*B. napus*), black mustard (*B. nigra*), and garden cress (*L. sativum*), were promising sources of green manure and significantly reduced weed biomass [40-41]. Among crops used for covering and green manure, leguminous species should be given priority as they provide rich nutrients including nitrogen to soil [42].When bracken fern (*Pteridium aquilinum*) was used as a green manure, it showed significant herbicidal and fungitoxic activities [43]. The integration of a cover crop into a cropping system

**5.2. Cover crops, green manure, mulch and intercropping**

One approach of utilizing the allelopathic property of crops is to screen accessions to examine their potential for weed suppression [11, 19]. To place crops in a more favourable competitive position in relation to allelopathy over weeds is important for the establishment of sustainable agriculture [20]. The strategy for using allelopathy for weed management could be either through directly exploiting natural allelopathic interactions, especially of crop plants, or applying allelochemicals as a source of natural herbicides. Derivatives of allelochemicals from plants used as herbicides with environmental properties include mesotrione [21-22] and citronella and bilanaphos oil [21]. Several microbial allelochemical products are marketed worldwide, such as glufosinate and bialaphos.

### **5. Methodology of allelopathy utilization**

#### **5.1. Crop rotation**

Crop rotation is one of the traditional practices whereby some crops, particularly leguminous species, are grown in short rotation with the main crops [1]. Crop rotation implies growing different crops in systematic and recurring sequence on the same land. This rotational system can help minimize the interference of weeds, fungi, pathogens, insects, and nematodes, and improve soil physical properties, fertility, and organic matter content and reduce soil erosion and heal soil sickness, and crop yields are therefore increased. Allelopathy and crop selection may play a key role in management strategies of weeds and pests. Use of allelopathy in a cropping system relies on better knowledge of the chemicals involved and their behaviour in the agro-ecosystem [23]. Lampkin, 1994 [24] suggested that the principles of selecting crops for rotational sequences should be: (i) alternating between autumn and spring germinating crops, (ii) rotating between annual and perennial crops, (iii) replacing between closed and dense crops, which shade out weeds and open crops such as maize (*Z. mays*), which encourage weeds, and (iv) cutting or topping operations (in particular the traditional cleaning crops, leys, and green manures). Some reports indicated that rotation of maize–cowpea and maize– soybean gave higher yield than monoculture, and the nutrient status of soil was also improved [25-26]. Rotating tobacco–rye grass–maize could minimize the root rot diseases caused by a soil-borne pathogen [27]. This may be the result of the fungitoxins produced by rye grass that inhibited the germination of conidia or chlamydospores of *Thielaviopsis basicola* [28]. Johnson, 1985 [29] conducted a series of exhaustive field trials to determine the suitability of various non-host/poor-host plants for various cropping systems of sweet corn–soybean–wheat– soybean–spinach (*Spinacia oleracea*) that showed significant control of Meloidogyne incognita infestation. Furthermore, Rizvi and Rizvi, 1992 [30] demonstrated that some food crops such as wheat, barley, rye, maize, and triticale (*Triticosecale wittmack*) with high concentrations of gramine or hyroxamic acids were useful for controlling fields with high aphid populations. Allelochemical interactions of plants–plants, plants–soils, plants-micro-organisms, and plant residues from a crop rotation play an active role in enhancing crop yields. Those allelochem‐ icals released from rotated crops then interacted with many physiological processes, which could help promote the growth and yield of crops. If plants used in a rotational system can be determined appropriately, the amount of chemical nitrogenous fertilizers is lowered and environmental hazard is reduced, whereas the sustainability of agriculture by substituting them with biologically fixed nitrogen from legumes is enhanced [31]. However, at present, negligible work has been done on the mode of action of allelochemicals in crop rotation, maybe due to their complicated transformation in nature. Moreover, Chou et al 1980 [77] reported 25% reduction in rice yield of second crop in Taiwan due to the phytotoxins produced during the decomposition of rice residues of first crop left in the soil. The phytotoxic effects of decomposing rice residues in the soil on the succeeding crop are problematic in some countries. In Southeast Asia, rotational systems give greater rice yield than rice monoculture and use of appropriate crops can also minimize the weed biomass significantly. In general, legume crops are preferred as preceding crops to suppress the weeds in succeeding rice crops [1].

#### **5.2. Cover crops, green manure, mulch and intercropping**

the occurrence of herbicide-resistant weeds. Since it is known that plants can self-regulate their densities and distribution in nature via allelopathic interactions, scientists have attempted to exploit these characteristics of crops and weeds in agriculture. The use of allelopathy for biological control of weeds in agriculture practice has attracted the interest of many agronomic

One approach of utilizing the allelopathic property of crops is to screen accessions to examine their potential for weed suppression [11, 19]. To place crops in a more favourable competitive position in relation to allelopathy over weeds is important for the establishment of sustainable agriculture [20]. The strategy for using allelopathy for weed management could be either through directly exploiting natural allelopathic interactions, especially of crop plants, or applying allelochemicals as a source of natural herbicides. Derivatives of allelochemicals from plants used as herbicides with environmental properties include mesotrione [21-22] and citronella and bilanaphos oil [21]. Several microbial allelochemical products are marketed

Crop rotation is one of the traditional practices whereby some crops, particularly leguminous species, are grown in short rotation with the main crops [1]. Crop rotation implies growing different crops in systematic and recurring sequence on the same land. This rotational system can help minimize the interference of weeds, fungi, pathogens, insects, and nematodes, and improve soil physical properties, fertility, and organic matter content and reduce soil erosion and heal soil sickness, and crop yields are therefore increased. Allelopathy and crop selection may play a key role in management strategies of weeds and pests. Use of allelopathy in a cropping system relies on better knowledge of the chemicals involved and their behaviour in the agro-ecosystem [23]. Lampkin, 1994 [24] suggested that the principles of selecting crops for rotational sequences should be: (i) alternating between autumn and spring germinating crops, (ii) rotating between annual and perennial crops, (iii) replacing between closed and dense crops, which shade out weeds and open crops such as maize (*Z. mays*), which encourage weeds, and (iv) cutting or topping operations (in particular the traditional cleaning crops, leys, and green manures). Some reports indicated that rotation of maize–cowpea and maize– soybean gave higher yield than monoculture, and the nutrient status of soil was also improved [25-26]. Rotating tobacco–rye grass–maize could minimize the root rot diseases caused by a soil-borne pathogen [27]. This may be the result of the fungitoxins produced by rye grass that inhibited the germination of conidia or chlamydospores of *Thielaviopsis basicola* [28]. Johnson, 1985 [29] conducted a series of exhaustive field trials to determine the suitability of various non-host/poor-host plants for various cropping systems of sweet corn–soybean–wheat– soybean–spinach (*Spinacia oleracea*) that showed significant control of Meloidogyne incognita infestation. Furthermore, Rizvi and Rizvi, 1992 [30] demonstrated that some food crops such as wheat, barley, rye, maize, and triticale (*Triticosecale wittmack*) with high concentrations of

scientists [1].

**5.1. Crop rotation**

worldwide, such as glufosinate and bialaphos.

78 Herbicides - Current Research and Case Studies in Use

**5. Methodology of allelopathy utilization**

The term 'cover crop' is defined as crops cultivated with regular cropping for soil and moisture conservation, promotion of nutrient recycling, biomass production, temperature lowering, nuisance weed inhibition, and forage supply [32, 33, 34]. Cover crops may be referred to as either green manure crops or sometimes implied catch crops [35]. Popular allelopathic crops used as cover crops are: barley (*Hordeum vulgare*), sorghum (*Sorghum* spp.), maize (*Z. mays*), wheat (*T. aestivum*), rye (*S. cereale*), buckwheat. (*Fagoprum esculentum*), velvetbean (*M. pruri‐ ens*), crimson clover (*Trifolium incarnatum*), subterranean clover (*Trifolium subterraneum*), hairy vetch (*Vicia vilosa*) sweet potato (*I. batatas*), and convolvulaceae (*Tricolor batatas*) [32]. These allelopathic plants exhibited significant weed reduction [36-37]. Excluding phytotoxins released from cover crops into soil, shading effects of the cover crops as well as their thick and dense population, and fast growth could effectively suppress weeds [38]. Legume species and some cruciferous plants could improve soil fertility contributing organic matter and nitrogen to the soil. Successfully established cover crops can develop sufficiently dense canopies in the autumn to interfere with growth of perennial and winter annual weeds [39]. Application of green manure crops can enhance soil organic matter and reduce weed growth. Some plants are used as green manures, including: *Mucuna* spp., *Canavalia* spp., *Trifolium* spp., *Brassica* spp., and *Ipomoea* spp. [32]. Several non-leguminous plants belonging to the family of Brassicaceae, such as field mustard (*Brassica campestris*), white or yellow mustard (*Brassica hirta*), brown/ Indian mustard (*Brassica nigra*), rapeseed/soilseed rape/canola (*B. napus*), black mustard (*B. nigra*), and garden cress (*L. sativum*), were promising sources of green manure and significantly reduced weed biomass [40-41]. Among crops used for covering and green manure, leguminous species should be given priority as they provide rich nutrients including nitrogen to soil [42].When bracken fern (*Pteridium aquilinum*) was used as a green manure, it showed significant herbicidal and fungitoxic activities [43]. The integration of a cover crop into a cropping system by relay cropping, over- seeding, inter-seeding, and double cropping may be useful to supply nitrogen for grain crops and reduce soil erosion and interference of weeds [44]. Some secondary metabolites from cover crops such as volatile glucosinolates and the breakdown isothiocya‐ nates, nitriles, epithinitriles, and ionic thiocyanates were responsible for weed and fungi inhibitory activities [45]. When plants with different growth habits and morphology are intercropped, weed biomass can be lowered. For instance, in maize, mung bean provides more weed suppression than peanut [46]. Barley, rye, and *Vicia faba* were planted in monoculture after the harvest of summer crop [47]. Barley+ V. faba and rye+ V. faba showed effective weed suppression. This was explained by the release of allelochemicals from root exudates during crop growth and from decomposing crop residues [47].

**Plant species Weed reduction (%) Increased in rice yield**

*Ageratum conyzoides* L. (billy goat weed) 80.8 20.9 *Alocasia cucullata* (Chinese taro) 78.4 17.0 *Azadirachta indica* A.Juss (neem) 91.0\* − *Bidens pilosa* L.(Beggar tick) 81.8 23.3 *Blechnum orientale* L.(White fern) 74.7 23.3 *Eupatorium canabium* L.(Fragrant thoughoutwork) 75.8 23.3 *Euphobia hirta* L. (Asthma weed) 87.9 23.3 *Helianthus tuberosus* (Jerusalem artichoke) 77.8 17.0 *Galactia pendula* Pers (Galactia) 84.8 7.0 *Fagopyrum esculentum* Moench (Buckwheat) Pellets 70.0 − *Leucaena glauca* L.(White lead-tree) 85.9 23.3 *Melia azedarach* L.(Chinaberry) 86.9 4.7 *Nerium odeander* (Oleander) 74.5 19.5 *Medicago sativa* L. (Alfalfa) Pellets 70.0 − cv. Rasen 80.0 80.6 cv. Yuba 65.0 29.0 *Morus alba* L. (Mulberry) 72.7 23.3

Hulls 51.7 19.4 Bran 25.1 -6.5\* Hulls +Rasen 88.3 77.4 Bran+Yuba 53.1 29.0 *Piper methysticum* (Kava) 86.3\* − *Passiflora incarnate* (Passionflower) 75.1 21.5 *Passiflora edulis* (Passionflower) 72.7 34.5 *Sophora japonica* (Japanese pagoda tree) 84.1 9.9 *Stylosanthes guianensis* (Stylo) 72.0 25.8 *Tephrosia candela* L. (White tephrosia) 91.9 23.3 Herbicide (5L ha-1)\*\* 77.8 11.6 Hand weeding 71.7 25.6

(-) Calculation was not conducted; Inhibited compared with the control, applied dose: 1-2 tons ha-1; \*: only greenhouse trial was conducted; \*\* : active ingredients in herbicides: pyributicard, bromobutide, butanamide, benzofenap [Shizetto furoaburu (5 L ha-1), Sankyo Ltd., Japan], and butachlor (600 g L-1 (Butataf, Monsato company, UK). Source: [48, 50].

**Table 2.** Allelopathic plants inhibitory to paddy weeds and stimulatory to rice yields over their control

*O. sativa* L. (Rice)

**ton/ha-1**

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## **6. Incorporation of higher plants with strong allelopathy to control weeds in rice**

#### **6.1. Direct use of plant materials in rice fields**

Many plants in the plant ecosystem exert significant allelopathic potential, and when they were incorporated into paddy fields, it resulted in excellent weed reduction. Our research, conduct‐ ed during 1999–2006, was mainly exploring allelopathic potential of plants in Southeast Asia and Japan for paddy weed control. The preliminary screening for the allelopathic potential of plants in the plant ecosystem should be made with the following requirements: (i) an assess‐ ment of their invasiveness and area in the plant ecosystem; (ii) ensuring the plants have less natural weed density in their canopy and surroundings than other plants in their ecosystem; and (iii) using those are traditionally used as green manure, weed or pest management by local farmers [48-49]. Minimizing the hazardous impacts of pesticides (herbicides, insecticides, nematicides and fungicides) in agriculture is the current trend in modern agriculture. Many plants with strong allelopathic properties inhibited the growth of indicator test plants in our laboratory and greenhouse studies. Afterwards, plant species with strong weed suppression were examined against weeds grown in paddy fields. The direct incorporation of allelopathic plant materials into rice fields remarkably reduced the weed interference [48-49].

Southeast Asia has a rich diversity in plant ecosystems; hence, we tested a few hundred plants. More than 30 species including crops strongly inhibited the emergence of pathogens and weeds. In a preliminary investigation, we separated leaves, stems and roots of plants to test their effects on germination and growth of indicator plants (lettuce, radish) and noxious weeds in paddy fields [*E. crus-galli* (barnyardgrass) and *Monochoria vaginalis* (monochoria)] in bioassays and in greenhouse trials. In field trials, some plant species reduced weeds and increased the rice yield (Table 1). We suggested that these plants could be used as source of natural herbicides.


by relay cropping, over- seeding, inter-seeding, and double cropping may be useful to supply nitrogen for grain crops and reduce soil erosion and interference of weeds [44]. Some secondary metabolites from cover crops such as volatile glucosinolates and the breakdown isothiocya‐ nates, nitriles, epithinitriles, and ionic thiocyanates were responsible for weed and fungi inhibitory activities [45]. When plants with different growth habits and morphology are intercropped, weed biomass can be lowered. For instance, in maize, mung bean provides more weed suppression than peanut [46]. Barley, rye, and *Vicia faba* were planted in monoculture after the harvest of summer crop [47]. Barley+ V. faba and rye+ V. faba showed effective weed suppression. This was explained by the release of allelochemicals from root exudates during

**6. Incorporation of higher plants with strong allelopathy to control weeds**

Many plants in the plant ecosystem exert significant allelopathic potential, and when they were incorporated into paddy fields, it resulted in excellent weed reduction. Our research, conduct‐ ed during 1999–2006, was mainly exploring allelopathic potential of plants in Southeast Asia and Japan for paddy weed control. The preliminary screening for the allelopathic potential of plants in the plant ecosystem should be made with the following requirements: (i) an assess‐ ment of their invasiveness and area in the plant ecosystem; (ii) ensuring the plants have less natural weed density in their canopy and surroundings than other plants in their ecosystem; and (iii) using those are traditionally used as green manure, weed or pest management by local farmers [48-49]. Minimizing the hazardous impacts of pesticides (herbicides, insecticides, nematicides and fungicides) in agriculture is the current trend in modern agriculture. Many plants with strong allelopathic properties inhibited the growth of indicator test plants in our laboratory and greenhouse studies. Afterwards, plant species with strong weed suppression were examined against weeds grown in paddy fields. The direct incorporation of allelopathic

plant materials into rice fields remarkably reduced the weed interference [48-49].

Southeast Asia has a rich diversity in plant ecosystems; hence, we tested a few hundred plants. More than 30 species including crops strongly inhibited the emergence of pathogens and weeds. In a preliminary investigation, we separated leaves, stems and roots of plants to test their effects on germination and growth of indicator plants (lettuce, radish) and noxious weeds in paddy fields [*E. crus-galli* (barnyardgrass) and *Monochoria vaginalis* (monochoria)] in bioassays and in greenhouse trials. In field trials, some plant species reduced weeds and increased the rice yield (Table 1). We suggested that these plants could be used as source of

crop growth and from decomposing crop residues [47].

80 Herbicides - Current Research and Case Studies in Use

**6.1. Direct use of plant materials in rice fields**

**in rice**

natural herbicides.

(-) Calculation was not conducted; Inhibited compared with the control, applied dose: 1-2 tons ha-1; \*: only greenhouse trial was conducted; \*\* : active ingredients in herbicides: pyributicard, bromobutide, butanamide, benzofenap [Shizetto furoaburu (5 L ha-1), Sankyo Ltd., Japan], and butachlor (600 g L-1 (Butataf, Monsato company, UK). Source: [48, 50].

**Table 2.** Allelopathic plants inhibitory to paddy weeds and stimulatory to rice yields over their control

### **6.2. Dose of application**

The application of 1-2 tons ha-1 biomass of alfalfa (*Medicago sativa*), buckwheat (*Fagopyrum esculentum*), kava (*Piper methysticum*), neem (*Azadirachta indica*), leucaena (*Leucaena glauca*), billy goat weed (*Ageratum conyzoides*), galactia (*Galactia pendula*), chinaberry (*Melia azedarach*), frangrant thoroughwort (*Eupatorium canabium*) and passion fruit (*Passiflora edulis*), strongly reduced the growth of major paddy weeds including *E. crus-galli, M. vaginalis, Rotala indica, Cyperus difformis, Digitaria ciliaris* [50-54]. Plant species exhibiting suppression > 20% were selected for weed control. Plant materials applied < 1 ton ha-1 suppresses only weed emergence. The application of alfalfa plants and its pellets or buckwheat pellets at 1-2 tons ha-1 caused significant reduction in weeds. The magnitude of weed reduction in rice fields was propor‐ tional to the applied dose of plant materials. However, it should not exceed 2 tons ha-1, because application of higher rates causes practical problems for its application, etc. [48]. Despite drastic suppression of paddy weed biomass, the allelopathic plants did not injure the rice plants, rather enhanced their yields by 20% (Table 2). The magnitude of weed inhibition depended on applied plant species. The nutrients released from the plants applied to paddy fields increased the rice yields.

inhibit the paddy weed growth at low concentrations in bioassays. However, the evidence of how these growth inhibitors act in paddy field conditions has remained unclear. We also examined the correlation of inhibitory potential of plant materials [alfalfa (*M. sativa*) and kava (*P. methysticum*)] incorporated in paddy soil against weeds [60]. Both alfalfa and kava strongly inhibited barnyardgrass and monochoria (*M. vaginalis*) growth up to 10 days after incorpora‐ tion (80-100% weed control) and suppression persisted for 20-25 days (50% weed control). Many phenolic acids were found in the soil even after 50 days in low concentration, but their concentrations was maximized at 10-15 days and were efficacious until 20-25 days after incorporation. Some growth inhibitors found in the kava treatment showed strong inhibition until 25 days after application, these may be lactones (major constituents in kava roots) and

Integration of Allelopathy to Control Weeds in Rice

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83

Observations from laboratory, greenhouse and field trials showed that the effects of plant materials on weed species are selective [48]. Different plant materials may possess different quantities and types of toxins, of which the amount released into soil after incorporation, is also species dependent. Despite the identification of many growth inhibitors, their fates after penetrating the soil, how they accumulate at phytotoxic levels and influence the weed growth, the interaction of these compounds with soil factors such as nutrients, pH, minerals and soil microbes, have not yet been fully understood. Even though these issues are complex, we need to understand the actual mode of action of allelochemicals in the environment, so that their efficacies can be increased and become more helpful to develop novel bioactive herbicides.

Searching the growth inhibitors from plants and testing their efficacies against weeds in the laboratory, greenhouse and fields are just the initial steps to developing bioactive herbicides. However, it is necessary to develop bioactive herbicides, because: (i) direct use of allelochem‐ icals as herbicides is not successful as these compounds are degraded in nature, before reaching the targets, (ii) to isolate allelochemicals from plants is complex, promising compounds for weed suppression exist in low quantities in plants, hence, it is too costly to use as herbicides and (iii) despite the promising weed reduction by direct application of plant materials to paddy soils, it requires a very high amount of plant biomass, therefore, does not meet the current requirements of trend in agricultural production in many countries. However, despite obtaining numerous compounds with herbicidal activities, very few constituents from plants have been marketed as herbicides than from bacteria and fungi [65]. Further, most reported secondary metabolites with strong herbicidal activity have complex chemical structures, hence, may not be processed as novel herbicides, because of difficulties in their synthesis and thus become costly. Thus searching for compounds having a simple form with strong herbi‐ cidal activities should be a priority. The synthesis of compounds derived from allelochemicals, attached with further functional groups and possessing herbicidal activities, is indispensable

Dihydro-5,6-dhydrokawain (DDK) (Figure 1) is a major compound in all parts of Alpinia (*Alpinia zerumbet*), a plant distributed widely in the subtropics and tropics. Besides many promising pharmaceutical efficacies, DDK exerts herbicidal and antifungal activities in

are plant and fungal growth inhibitors [63].

**7.2. Syntheses of novel compounds**

to developing novel bioactive herbicides.

#### **6.3. Methods of application**

The ability of allelopathic plants to reduce weeds in paddy fields depends on the treatment method. The plants with strong weed suppressing ability in the screening should be exploited for paddy weed control [51, 53-54]. The leaves of the screened plants are commonly used to provide a large biomass; however, their nutrient contents should be monitored before conducting field trials. Spreading plant materials evenly on the surface of paddy field, 1-5 days after saturating with water at 1 ton ha-1 causes greatest weed biomass reduction. Application of allelopathic materials in fields, 7 days after adding water did not influence paddy weed emergence. Major paddy weeds (*E. crus-galli* and *R. indica*) re-emerged in treatments with alfalfa pellets, alfalfa plants, rice hulls and rice bran [52, 55]. A sequential application of biomass was also studied. In the first application, 1 ton ha-1 allelopathic material was added 1-2 days after irrigating the paddy soils. In the second and third applications, the same doses were added at 10 days intervals. Each application caused an additional 10-15% inhibition of weeds. However, a greater amount of plant material was needed, which requires more fieldwork, hence, becomes costly [48, 53, 56-57].

### **7. Developing allelochemicals and their derivatives to control weeds in rice**

#### **7.1. Role of allelochemicals in paddy fields**

The allelochemicals released from the plants incorporated into paddy soil play a crucial role in inhibiting the paddy weed growth. Many weed growth inhibitors identified from *M. sativa, Piper methysticum, A. indica* (neem), *A. conyzoides*, *O. sativa*, and *B. pilosa* belong to phenolic acids [52,56, 58-63], fatty acids [56], lactones [62-63], and amino acids [64]. These compounds inhibit the paddy weed growth at low concentrations in bioassays. However, the evidence of how these growth inhibitors act in paddy field conditions has remained unclear. We also examined the correlation of inhibitory potential of plant materials [alfalfa (*M. sativa*) and kava (*P. methysticum*)] incorporated in paddy soil against weeds [60]. Both alfalfa and kava strongly inhibited barnyardgrass and monochoria (*M. vaginalis*) growth up to 10 days after incorpora‐ tion (80-100% weed control) and suppression persisted for 20-25 days (50% weed control). Many phenolic acids were found in the soil even after 50 days in low concentration, but their concentrations was maximized at 10-15 days and were efficacious until 20-25 days after incorporation. Some growth inhibitors found in the kava treatment showed strong inhibition until 25 days after application, these may be lactones (major constituents in kava roots) and are plant and fungal growth inhibitors [63].

Observations from laboratory, greenhouse and field trials showed that the effects of plant materials on weed species are selective [48]. Different plant materials may possess different quantities and types of toxins, of which the amount released into soil after incorporation, is also species dependent. Despite the identification of many growth inhibitors, their fates after penetrating the soil, how they accumulate at phytotoxic levels and influence the weed growth, the interaction of these compounds with soil factors such as nutrients, pH, minerals and soil microbes, have not yet been fully understood. Even though these issues are complex, we need to understand the actual mode of action of allelochemicals in the environment, so that their efficacies can be increased and become more helpful to develop novel bioactive herbicides.

#### **7.2. Syntheses of novel compounds**

**6.2. Dose of application**

82 Herbicides - Current Research and Case Studies in Use

fields increased the rice yields.

hence, becomes costly [48, 53, 56-57].

**7.1. Role of allelochemicals in paddy fields**

**6.3. Methods of application**

The application of 1-2 tons ha-1 biomass of alfalfa (*Medicago sativa*), buckwheat (*Fagopyrum esculentum*), kava (*Piper methysticum*), neem (*Azadirachta indica*), leucaena (*Leucaena glauca*), billy goat weed (*Ageratum conyzoides*), galactia (*Galactia pendula*), chinaberry (*Melia azedarach*), frangrant thoroughwort (*Eupatorium canabium*) and passion fruit (*Passiflora edulis*), strongly reduced the growth of major paddy weeds including *E. crus-galli, M. vaginalis, Rotala indica, Cyperus difformis, Digitaria ciliaris* [50-54]. Plant species exhibiting suppression > 20% were selected for weed control. Plant materials applied < 1 ton ha-1 suppresses only weed emergence. The application of alfalfa plants and its pellets or buckwheat pellets at 1-2 tons ha-1 caused significant reduction in weeds. The magnitude of weed reduction in rice fields was propor‐ tional to the applied dose of plant materials. However, it should not exceed 2 tons ha-1, because application of higher rates causes practical problems for its application, etc. [48]. Despite drastic suppression of paddy weed biomass, the allelopathic plants did not injure the rice plants, rather enhanced their yields by 20% (Table 2). The magnitude of weed inhibition depended on applied plant species. The nutrients released from the plants applied to paddy

The ability of allelopathic plants to reduce weeds in paddy fields depends on the treatment method. The plants with strong weed suppressing ability in the screening should be exploited for paddy weed control [51, 53-54]. The leaves of the screened plants are commonly used to provide a large biomass; however, their nutrient contents should be monitored before conducting field trials. Spreading plant materials evenly on the surface of paddy field, 1-5 days after saturating with water at 1 ton ha-1 causes greatest weed biomass reduction. Application of allelopathic materials in fields, 7 days after adding water did not influence paddy weed emergence. Major paddy weeds (*E. crus-galli* and *R. indica*) re-emerged in treatments with alfalfa pellets, alfalfa plants, rice hulls and rice bran [52, 55]. A sequential application of biomass was also studied. In the first application, 1 ton ha-1 allelopathic material was added 1-2 days after irrigating the paddy soils. In the second and third applications, the same doses were added at 10 days intervals. Each application caused an additional 10-15% inhibition of weeds. However, a greater amount of plant material was needed, which requires more fieldwork,

**7. Developing allelochemicals and their derivatives to control weeds in rice**

The allelochemicals released from the plants incorporated into paddy soil play a crucial role in inhibiting the paddy weed growth. Many weed growth inhibitors identified from *M. sativa, Piper methysticum, A. indica* (neem), *A. conyzoides*, *O. sativa*, and *B. pilosa* belong to phenolic acids [52,56, 58-63], fatty acids [56], lactones [62-63], and amino acids [64]. These compounds Searching the growth inhibitors from plants and testing their efficacies against weeds in the laboratory, greenhouse and fields are just the initial steps to developing bioactive herbicides. However, it is necessary to develop bioactive herbicides, because: (i) direct use of allelochem‐ icals as herbicides is not successful as these compounds are degraded in nature, before reaching the targets, (ii) to isolate allelochemicals from plants is complex, promising compounds for weed suppression exist in low quantities in plants, hence, it is too costly to use as herbicides and (iii) despite the promising weed reduction by direct application of plant materials to paddy soils, it requires a very high amount of plant biomass, therefore, does not meet the current requirements of trend in agricultural production in many countries. However, despite obtaining numerous compounds with herbicidal activities, very few constituents from plants have been marketed as herbicides than from bacteria and fungi [65]. Further, most reported secondary metabolites with strong herbicidal activity have complex chemical structures, hence, may not be processed as novel herbicides, because of difficulties in their synthesis and thus become costly. Thus searching for compounds having a simple form with strong herbi‐ cidal activities should be a priority. The synthesis of compounds derived from allelochemicals, attached with further functional groups and possessing herbicidal activities, is indispensable to developing novel bioactive herbicides.

Dihydro-5,6-dhydrokawain (DDK) (Figure 1) is a major compound in all parts of Alpinia (*Alpinia zerumbet*), a plant distributed widely in the subtropics and tropics. Besides many promising pharmaceutical efficacies, DDK exerts herbicidal and antifungal activities in bioassay trials. Our team has synthesized numerous DDK derivatives (Figure 1) [66] and tested for their influences against indicator plant and plant fungi. The derivative dimethyl phos‐ phorothionate exhibited maximum antifungal activity of 91% and 72% against *Corticium rolfsii* and *Pythium* spp., respectively [67]. Twenty-four kinds of esters were made from cinnamic acid, p-coumaric acid and ferulic acid, alcohols and the components of Alpinia [68]. Among these derivatives, isopropyl 4-hydroxycinnamate and butyl 4-hydroxy-cinnamate were fungitoxic to *Pythium* spp. at 10 ppm. Further syntheses of DDK derivatives are being carried out in our laboratory.

Extensive efforts of researchers worldwide to clarify allelopathic activities among rice cultivars have been made. They provided important information for further work such as genetic analyses, gene mapping of allelopathic characteristics and breeding new rice cultivars with

Integration of Allelopathy to Control Weeds in Rice

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85

Utilization of rice residues in paddy fields has long been recognised as an important source to improve the organic matter status of soil and was also reported to reduce the emergence of weeds. In Asia, farmers are often left with a large amount of rice residues, leaves, stubble and straw in the paddy fields after harvest. Incorporating the residues of rice with high allelopathic activity minimised rice flatsedge (*Cyperus iria* L.) growth to a similar degree as achieved by the application of propanil and bentazon herbicides [69]. Furthermore, another trial showed residues of rice (var. Sarjoo 52) blended into the soil (5–6 cm in depth, 5 tons ha-1) suppressed jungle rice [*Echinochloa colona* (L.) Link], monarch redstem (*Ammania baccifera* L.), Ammania multiflora Roxb., and gulf leaf flower (*Phyllanthus fraternus Webster*) [70]. Other experiments reported that rice straw suppressed the germination of oat (*Avena sativa*) and wheat (*Triticum aestivum*), Lens sp., *Convolvulus arvensis* L., *Avena ludoviciana* and *Phalaris minor Retz* [71-72].

To date, decomposition of rice straw and stubble has reduced the occurrence of both broad‐ leaved and grassy weeds [73]. Leaf plus straw and hulls of some rice cultivars with strong allelopathic property dramatically inhibited weed interference about 60–95% [74]. A pot study of soil incorporation of a mixture of stubble and straw in 15 cm of soil in the pots (7.4 tons ha-1 of blended stubble and straw) revealed inhibition on growth of weed density and decrease of the dry biomass of weeds [73]. Straw, leaves and hulls of some rice cultivars suppressed the germination of field bind weed (*Convolvulus arvensis*) and little seed canary grass (*Phalaris minor*) [71-72, 75-76]. Similarly, Pheng et al (2010) [77] suggested that if the rice residue incorporation was suspended for 2 weeks or only a proportion of the residue was incorporated, the rice crop could withstand the growth-suppressive effect. This research suggests that rice possessing high allelopathy can control some weeds in rice and can be integrated with existing weed manage‐ ment practice. Residues of rice allelopathy may be helpful for weed control, but they some‐ times cause trouble with rice autotoxicity. From the residual effects of decomposing rice plant materials, the rice plant may obtain adaptive mechanisms to prevent a severe autotoxic effect. Forinstance,Chou,(1980)[78]reportedinTaiwanthatdecomposedriceresiduesleftonthepaddy fieldsoilpersistedintothenextcropseasonandcouldreducethericeyieldbyupto25%compared with that of the first crop. Such a reduction was suggested to be primarily attributable to the phytotoxins produced, which inhibited paddy weed growth and minimised rice yield. Singh et al.(1999)[79]reportedthatautotoxicityinricecouldprovideanadaptivestrategytoplantsbecause theyaregrowninadequatelywater-loggedsoils sufficientinoxygenandthusdevelopanegative redox potential in soil because of decomposing rice residues. This induced the inhibition of root growth of rice plants accompanied by swelling of root cells in order to capture more oxygen [80]. Rice hulls and bran were reported to suppress paddy weeds and could be exploited for weed management [81]. Xuan et al. (2003) [52] noted that rice hulls and bran each at 1 ton ha-1 re‐ duced paddy weed biomass by about 25% and 50%, respectively. The combination of rice by-

strengthened weed suppression ability [10].

**8.1. Rice residue**

**Figure 1.** Structures of DDK, HMP and the Pyranyl - substituted Cinnamates. [11, 66]

### **8. Effort to utilize rice allelopathy for rice weed control**

Reducing weed infestation by exploiting the allelopathic properties of rice may be the most important goal of research involved in rice allelopathy and has been a hope of many agrono‐ mists. The direct use of rice residues and genetic control of rice allelopathy via breeding programmes to enhance weed suppression may be the most feasible strategy.

Allelopathic activity has been shown to be variety-dependent and origin-dependent, where Japonica rice shows greater allelopathic activity than Indica and Japonica-Indica hybrid. Extensive efforts of researchers worldwide to clarify allelopathic activities among rice cultivars have been made. They provided important information for further work such as genetic analyses, gene mapping of allelopathic characteristics and breeding new rice cultivars with strengthened weed suppression ability [10].

#### **8.1. Rice residue**

bioassay trials. Our team has synthesized numerous DDK derivatives (Figure 1) [66] and tested for their influences against indicator plant and plant fungi. The derivative dimethyl phos‐ phorothionate exhibited maximum antifungal activity of 91% and 72% against *Corticium rolfsii* and *Pythium* spp., respectively [67]. Twenty-four kinds of esters were made from cinnamic acid, p-coumaric acid and ferulic acid, alcohols and the components of Alpinia [68]. Among these derivatives, isopropyl 4-hydroxycinnamate and butyl 4-hydroxy-cinnamate were fungitoxic to *Pythium* spp. at 10 ppm. Further syntheses of DDK derivatives are being

O

HMP (5-Hydroxy-6-methyl-2H-pyran-2-one)

> O O

O O

O

HO

Compounds H1-H11 H1: R=H H2: R=*o*-Me H3: R=*m*-Me H4: R=*p*-Me H5 R=*p-iso*-Pro H6: R=*o*-Cl H7: R=*m*-Cl H8: R=*p*-Cl H9: R=*o*-F H10: R=*m*-F H11: R=*p*-F

R

carried out in our laboratory.

R

H3CO

84 Herbicides - Current Research and Case Studies in Use

O

DDK (Dihydro-5,6-dehydrokawain)

O

O

**Figure 1.** Structures of DDK, HMP and the Pyranyl - substituted Cinnamates. [11, 66]

**8. Effort to utilize rice allelopathy for rice weed control**

programmes to enhance weed suppression may be the most feasible strategy.

Reducing weed infestation by exploiting the allelopathic properties of rice may be the most important goal of research involved in rice allelopathy and has been a hope of many agrono‐ mists. The direct use of rice residues and genetic control of rice allelopathy via breeding

Allelopathic activity has been shown to be variety-dependent and origin-dependent, where Japonica rice shows greater allelopathic activity than Indica and Japonica-Indica hybrid.

O

O

O

Compounds D1-D11 D1: R=H D2: R=*o*-Me D3: R=*m*-Me D4: R=*p*-Me D5: R=*p-iso*-Pro D6: R=*o*-Cl D7: R=*m*-Cl D8: R=*p*-Cl D9: R=*o*-F D10: R=*m*-F D11:R=*p*-F

Utilization of rice residues in paddy fields has long been recognised as an important source to improve the organic matter status of soil and was also reported to reduce the emergence of weeds. In Asia, farmers are often left with a large amount of rice residues, leaves, stubble and straw in the paddy fields after harvest. Incorporating the residues of rice with high allelopathic activity minimised rice flatsedge (*Cyperus iria* L.) growth to a similar degree as achieved by the application of propanil and bentazon herbicides [69]. Furthermore, another trial showed residues of rice (var. Sarjoo 52) blended into the soil (5–6 cm in depth, 5 tons ha-1) suppressed jungle rice [*Echinochloa colona* (L.) Link], monarch redstem (*Ammania baccifera* L.), Ammania multiflora Roxb., and gulf leaf flower (*Phyllanthus fraternus Webster*) [70]. Other experiments reported that rice straw suppressed the germination of oat (*Avena sativa*) and wheat (*Triticum aestivum*), Lens sp., *Convolvulus arvensis* L., *Avena ludoviciana* and *Phalaris minor Retz* [71-72].

To date, decomposition of rice straw and stubble has reduced the occurrence of both broad‐ leaved and grassy weeds [73]. Leaf plus straw and hulls of some rice cultivars with strong allelopathic property dramatically inhibited weed interference about 60–95% [74]. A pot study of soil incorporation of a mixture of stubble and straw in 15 cm of soil in the pots (7.4 tons ha-1 of blended stubble and straw) revealed inhibition on growth of weed density and decrease of the dry biomass of weeds [73]. Straw, leaves and hulls of some rice cultivars suppressed the germination of field bind weed (*Convolvulus arvensis*) and little seed canary grass (*Phalaris minor*) [71-72, 75-76]. Similarly, Pheng et al (2010) [77] suggested that if the rice residue incorporation was suspended for 2 weeks or only a proportion of the residue was incorporated, the rice crop could withstand the growth-suppressive effect. This research suggests that rice possessing high allelopathy can control some weeds in rice and can be integrated with existing weed manage‐ ment practice. Residues of rice allelopathy may be helpful for weed control, but they some‐ times cause trouble with rice autotoxicity. From the residual effects of decomposing rice plant materials, the rice plant may obtain adaptive mechanisms to prevent a severe autotoxic effect. Forinstance,Chou,(1980)[78]reportedinTaiwanthatdecomposedriceresiduesleftonthepaddy fieldsoilpersistedintothenextcropseasonandcouldreducethericeyieldbyupto25%compared with that of the first crop. Such a reduction was suggested to be primarily attributable to the phytotoxins produced, which inhibited paddy weed growth and minimised rice yield. Singh et al.(1999)[79]reportedthatautotoxicityinricecouldprovideanadaptivestrategytoplantsbecause theyaregrowninadequatelywater-loggedsoils sufficientinoxygenandthusdevelopanegative redox potential in soil because of decomposing rice residues. This induced the inhibition of root growth of rice plants accompanied by swelling of root cells in order to capture more oxygen [80]. Rice hulls and bran were reported to suppress paddy weeds and could be exploited for weed management [81]. Xuan et al. (2003) [52] noted that rice hulls and bran each at 1 ton ha-1 re‐ duced paddy weed biomass by about 25% and 50%, respectively. The combination of rice byproducts and alfalfa strengthened weed suppression by 70–80% and controlled more weed species and increased rice yield more than the incorporation of single rice by-products.

a genetic distance of 1336.2 cM. The total number of probes ranged from 12.7% to 76.4% among 12 chromosomes. With RFLP markerloci to the allelopathic QTLs at all pinpoints, the PI312777 alleles were more suppressive against lettuce than the Rexmont alleles. The positive allelo‐ pathic effect was shown by QTL located on chromosome 7 that suppressed root growth and necrosis on lettuce [92]. Zeng et al. (2003) [93] used a double-haploid population derived from ZYQ8/JX17, a typical Indica and Japonica hybrid. Four QTLs correlated to allelopathy belonging to chromosomes 3, 9, 10 and 12 were detected and their logarithm of odds scores were 3.40, 2.68, 2.75 and 3.08, respectively. Among them, additive effects of the QTLs on chromosomes 3 and 10 were 1.65 and 1.43 and on chromosomes 9 and 12 were –1.44 and – 1.58, respectively. Recently, Lee et al. (2005) [94] identified nine QTLs controlling allelopath‐ ic effects of rice on *E. crusgalli* on chromosomes 1, 2, 3, 4, 5, 8, 9 and 12. Of these, QTLs on chromosomes 1 and 5 were the most allelopathic and explained 36.5% of total phenotypic variation. Lin et al. (2005) [95] used the inter-simple sequence repeat approach to detect the genetic diversity of allelopathic potential in 57 rice cultivars. Thirty-four polymorphic bands were generated, and the percentage of polymorphic bands was 53.0%. Rice from the same geographical location and those cultivars with higher allelopathic potential could be clustered into each group, implying that the genes conferring allelopathy in rice might be isolocus. However, some cultivars of rice with markedly different allelopathic potential clustered into a group with a lower level of genetic polymorphism, and this might be attributed to selec‐ tion oriented for high-yielding traits in breeding. More recent advances in rice genome research have provided a powerful tool for the genetic analysis of quantitative traits. The use of high density genetic linkage maps and DNA markers mapped onto rice chromosomes may enable the identification of the QTLs controlling the allelopathic effect of rice on weeds [96]. QTL analysis is the initial step in rice genetic analysis. Identification of QTLs from close linkage of a DNA marker to the QTL would be useful for producing near-isogenic lines. Applica‐ tion of DNA marker-assisted selection, map based cloning of allelopathic QTLs and a nearisogenic line may help to determine allelopathy-correlated genes in rice. Nine possible differently expressed genes 1, 4, 5, 7, 8 and 9 involved in allelopathic potential of Indica type rice variety, namely Sathoi, capable of producing nicotianamine against growth of barnyard‐ grass indicated higher while three differentially expressed genes 2, 3 and 6 showed low expression. It implies that these genes were found to be homologous to other genes [96-98]. To date, under low-nitrogen stress, rice cultivar PI exhibited increased allelopathic activity. Nine genes involved in phenylpropanoid metabolism, including phenylalanine ammonialyase (PAL), became up regulated and the content of phenolic compounds in rice was enhanced [98-99]. Song et al. (2008) [101] reported that the intensification of allelochemical biosynthesis in rice grown under stress nutrition (i.e., low levels of nitrogen) disclosed the overexpression of genes that encode for PAL (phenylalanine ammonia-lyase), O-methyltrans‐ ferase, triosephosphate isomerise and P450-all related to the synthesis of phenolic com‐ pounds and detoxification. Furthermore, a proteomic analysis of rice growing with barnyardgrass revealed the induction of the following proteins: PAL, a thioredoxin and 3 hydroxy-3-methilglutaril-coenzyme a reductase 3 (HMGR) [102]. On the other hand, the differential proteomic analyses have validated that enhanced allelopathic potential in rice exposed to stress is due to increased expression of enzyme genes involved in the biosynthe‐

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87

#### **8.2. Molecular research in rice allelopathy and breeding**

Allelopathy is one of the last areas of plant science to use molecular biology as a tool in understanding the phenomena. Allelopathic competition, which may be defined as the unequal sharing of resources such as nutrition, light and water, is dependent on several physiological and phenological traits, and its allelopathy is polygenic and quantitatively inherited [82-84]. To be able to breed a more competitive crop with strong allelopathic potential, it is crucial to know which genes are involved in crop competitiveness and allelopathic potential. Molecular marker-aided genetics is presently the best tool for identifying quantitative traits, mapping the genes involved onto the chromosomes with a reasonable level of precision and analysing the relationship between the traits of interest and other important agronomic traits [82]. Allelopathic activity in rice has demonstrated to be a polygenic trait that is only slightly correlated with yield or other agronomic features. The quantitative inheritance of rice allel‐ opathy curbed the breeding of allelopathic rice cultivars against paddy weeds under varying environmental condition [84, 86-87]. Recent research of Xu et al 2012 [85] has provided the evidence that diterpenoid momilactones (allelochemical) isolated from a rice cultivar plays a novel genetic for natural product-mediated allelopathy and furnished a molecular target for breeding and metabolic engineering of a rice cultivar. The selection of rice cultivars with strong weed suppression ability through transgenic and breeding programmes may successfully utilise rice allelopathy for weed control. Allelopathic activity of rice varies among cultivars and origins and correlates with some growth characteristics; therefore, the existence of genes determining rice allelopathy is presumed and should be detected. It was proposed that allelopathic activity may be a polygenic trait slightly correlated with yield or other agronomic features. Allelopathic potential in rice was demonstrated to be quantitatively inherited, but the allelopathic traits were not identified [83].

#### **8.3. Genomic analysis and gene mapping**

Despite research on rice allelopathy beginning in the early 1970s, the genetic allelopathy control programme started only in 1996 [88]. Dilday et al. (1998) [89] crossed the allelopath‐ ic rice cultivar PI312777 (PI) with another non-allelopathic rice cultivar Lemont and noted that the F2 was allelopathic against *Heteranthera limosa* and was quantitatively inherited. Jensen et al. (2001) [90] studied quantitative trait loci (QTLs) mapping using a population of 142 recombinant inbred lines (RILs) derived from a cross between IAC 165 (Japonica upland cultivar) and CO 39 (Indica irrigated cultivar). Four main QTLs located on three chromo‐ somes, 2, 3 and 8, were identified and claimed 35% of the total phenotypic variation of the allelopathic activity against barnyardgrass. Okuno & Ebana (2003) [91] identified seven QTLs controlling rice allelopathy on chromosomes 1, 3, 5, 6, 7, 11 and 12. Digenic interactions in five pairs among the seven QTLs were detected. This study showed 125 out of 215 restric‐ tion fragment length polymorphism (RFLP) generated polymorphic bands between PI312777 and Rexmont under QTL analysis. A map of 12 linkage groups was constructed and covered

a genetic distance of 1336.2 cM. The total number of probes ranged from 12.7% to 76.4% among 12 chromosomes. With RFLP markerloci to the allelopathic QTLs at all pinpoints, the PI312777 alleles were more suppressive against lettuce than the Rexmont alleles. The positive allelo‐ pathic effect was shown by QTL located on chromosome 7 that suppressed root growth and necrosis on lettuce [92]. Zeng et al. (2003) [93] used a double-haploid population derived from ZYQ8/JX17, a typical Indica and Japonica hybrid. Four QTLs correlated to allelopathy belonging to chromosomes 3, 9, 10 and 12 were detected and their logarithm of odds scores were 3.40, 2.68, 2.75 and 3.08, respectively. Among them, additive effects of the QTLs on chromosomes 3 and 10 were 1.65 and 1.43 and on chromosomes 9 and 12 were –1.44 and – 1.58, respectively. Recently, Lee et al. (2005) [94] identified nine QTLs controlling allelopath‐ ic effects of rice on *E. crusgalli* on chromosomes 1, 2, 3, 4, 5, 8, 9 and 12. Of these, QTLs on chromosomes 1 and 5 were the most allelopathic and explained 36.5% of total phenotypic variation. Lin et al. (2005) [95] used the inter-simple sequence repeat approach to detect the genetic diversity of allelopathic potential in 57 rice cultivars. Thirty-four polymorphic bands were generated, and the percentage of polymorphic bands was 53.0%. Rice from the same geographical location and those cultivars with higher allelopathic potential could be clustered into each group, implying that the genes conferring allelopathy in rice might be isolocus. However, some cultivars of rice with markedly different allelopathic potential clustered into a group with a lower level of genetic polymorphism, and this might be attributed to selec‐ tion oriented for high-yielding traits in breeding. More recent advances in rice genome research have provided a powerful tool for the genetic analysis of quantitative traits. The use of high density genetic linkage maps and DNA markers mapped onto rice chromosomes may enable the identification of the QTLs controlling the allelopathic effect of rice on weeds [96]. QTL analysis is the initial step in rice genetic analysis. Identification of QTLs from close linkage of a DNA marker to the QTL would be useful for producing near-isogenic lines. Applica‐ tion of DNA marker-assisted selection, map based cloning of allelopathic QTLs and a nearisogenic line may help to determine allelopathy-correlated genes in rice. Nine possible differently expressed genes 1, 4, 5, 7, 8 and 9 involved in allelopathic potential of Indica type rice variety, namely Sathoi, capable of producing nicotianamine against growth of barnyard‐ grass indicated higher while three differentially expressed genes 2, 3 and 6 showed low expression. It implies that these genes were found to be homologous to other genes [96-98]. To date, under low-nitrogen stress, rice cultivar PI exhibited increased allelopathic activity. Nine genes involved in phenylpropanoid metabolism, including phenylalanine ammonialyase (PAL), became up regulated and the content of phenolic compounds in rice was enhanced [98-99]. Song et al. (2008) [101] reported that the intensification of allelochemical biosynthesis in rice grown under stress nutrition (i.e., low levels of nitrogen) disclosed the overexpression of genes that encode for PAL (phenylalanine ammonia-lyase), O-methyltrans‐ ferase, triosephosphate isomerise and P450-all related to the synthesis of phenolic com‐ pounds and detoxification. Furthermore, a proteomic analysis of rice growing with barnyardgrass revealed the induction of the following proteins: PAL, a thioredoxin and 3 hydroxy-3-methilglutaril-coenzyme a reductase 3 (HMGR) [102]. On the other hand, the differential proteomic analyses have validated that enhanced allelopathic potential in rice exposed to stress is due to increased expression of enzyme genes involved in the biosynthe‐

products and alfalfa strengthened weed suppression by 70–80% and controlled more weed

Allelopathy is one of the last areas of plant science to use molecular biology as a tool in understanding the phenomena. Allelopathic competition, which may be defined as the unequal sharing of resources such as nutrition, light and water, is dependent on several physiological and phenological traits, and its allelopathy is polygenic and quantitatively inherited [82-84]. To be able to breed a more competitive crop with strong allelopathic potential, it is crucial to know which genes are involved in crop competitiveness and allelopathic potential. Molecular marker-aided genetics is presently the best tool for identifying quantitative traits, mapping the genes involved onto the chromosomes with a reasonable level of precision and analysing the relationship between the traits of interest and other important agronomic traits [82]. Allelopathic activity in rice has demonstrated to be a polygenic trait that is only slightly correlated with yield or other agronomic features. The quantitative inheritance of rice allel‐ opathy curbed the breeding of allelopathic rice cultivars against paddy weeds under varying environmental condition [84, 86-87]. Recent research of Xu et al 2012 [85] has provided the evidence that diterpenoid momilactones (allelochemical) isolated from a rice cultivar plays a novel genetic for natural product-mediated allelopathy and furnished a molecular target for breeding and metabolic engineering of a rice cultivar. The selection of rice cultivars with strong weed suppression ability through transgenic and breeding programmes may successfully utilise rice allelopathy for weed control. Allelopathic activity of rice varies among cultivars and origins and correlates with some growth characteristics; therefore, the existence of genes determining rice allelopathy is presumed and should be detected. It was proposed that allelopathic activity may be a polygenic trait slightly correlated with yield or other agronomic features. Allelopathic potential in rice was demonstrated to be quantitatively inherited, but

Despite research on rice allelopathy beginning in the early 1970s, the genetic allelopathy control programme started only in 1996 [88]. Dilday et al. (1998) [89] crossed the allelopath‐ ic rice cultivar PI312777 (PI) with another non-allelopathic rice cultivar Lemont and noted that the F2 was allelopathic against *Heteranthera limosa* and was quantitatively inherited. Jensen et al. (2001) [90] studied quantitative trait loci (QTLs) mapping using a population of 142 recombinant inbred lines (RILs) derived from a cross between IAC 165 (Japonica upland cultivar) and CO 39 (Indica irrigated cultivar). Four main QTLs located on three chromo‐ somes, 2, 3 and 8, were identified and claimed 35% of the total phenotypic variation of the allelopathic activity against barnyardgrass. Okuno & Ebana (2003) [91] identified seven QTLs controlling rice allelopathy on chromosomes 1, 3, 5, 6, 7, 11 and 12. Digenic interactions in five pairs among the seven QTLs were detected. This study showed 125 out of 215 restric‐ tion fragment length polymorphism (RFLP) generated polymorphic bands between PI312777 and Rexmont under QTL analysis. A map of 12 linkage groups was constructed and covered

species and increased rice yield more than the incorporation of single rice by-products.

**8.2. Molecular research in rice allelopathy and breeding**

86 Herbicides - Current Research and Case Studies in Use

the allelopathic traits were not identified [83].

**8.3. Genomic analysis and gene mapping**

sis of phenolic compounds and reduced expression of enzyme genes associated with terpenoid biosynthesis [103]. The identification of these genes and proteins shows different signs, plantenvironment interactions or plant-plant communication triggering the biosynthesis of phenolic compounds that are also known to be related with plant defence processes [102,104]. Moreover, allelopathic enhancement of allelopathic rice cultivars in the vicinity of barnyard‐ grass was due to improvement in carbon assimilation deriving from the regulation of photosynthesis genes and the activation of the enzyme system [103, 105].

commercialcultivars.ThebredHuagan-3showed80%inhibitiononnoxiousbarnyardgrassand 30-50% of a total reduction in paddy weeds. However, it should be noted that developing allelopathic rice cultivars must therefore be accompanied with an evaluation of the cultural practices required for consistent suppression under variable environmental conditions [84, 86]. On the other hand, before starting any plant breeding program to enhance allelopathic activi‐ ty, it is important to utilize a practical effective screening method in both controlled and natural conditions for measurement of allelopathic potential. It is hoped that with assistance of modern genetic techniques, new rice cultivars with strong weed suppression ability and acceptable for

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89

**9. Benefits from allelopathy integrated into sustainable agriculture**

If allelopathy can be integrated into sustainable agriculture appropriately, the heavy depend‐ ence on synthetic pesticides and other agrochemicals can be significantly minimized. Mono culture has caused imbalances in agricultural production, and this would be replaced by a more ecological and sustainable cropping system. In modern agriculture with its shortage of labour, it is difficult to completely alter the use of agrochemicals, but the biological character‐ istics of crops including allelopathy and strength of competition should be exploited to reduce the amount of pesticides and agrochemicals used. Furthermore, unsafe pesticides and agrochemicals must be replaced by safer bioactive products, which are derived from living organisms such as plants, fungi, bacteria, and micro-organisms. The detrimental effects from allelopathy integration into agricultural production should also be noted, as only their benefits have been detailed [37]. The competition and chemical interaction of crops can effectively inhibit weeds and other pests, but they may also have harmful effects for crops in the next cropping seasons. Allelochemicals released from living plants and decomposition includes many toxins, which may suppress growth of useful bacteria, fungi, and micro-organisms, but they may cause problems to mineralization and nitrification in soils. This issue can be excluded with common crops, but should be examined when plant (other than common crops and legumes) materials are incorporated into soils. This style of application is still useful in many developing countries, in which a major proportion of the population is still involved in agricultural production. The modes of action of allelochemicals need further research to exploit novel allelochemicals and their derivatives in the development of bioactive pesticides. However, in addition, the extent to which they cause detrimental effects to crops and soils needs careful examination. Despite the fact that many hypotheses have been developed and discussed, and many experiments have been carried out to test them, the actual modes of action of allelopathy in nature are still somewhat unclear, unlike the allelopathic phenomena that we could easily observe. The allelopathic characteristics of plants have been known for centuries, and extensive research worldwide has been conducted for more than 40 years to elucidate the mode of allelopathy as well as efforts to utilize allelopathy more effectively in agricultural production. However, it can be said that farmers have not yet received much efficacy from what has been observed and reported. Much knowledge on plant allelopathy has been documented, but few approaches have already been successfully applied in agricultural

cultivation by farmers will hopefully appear very soon.

#### **8.4. Breeding new rice allelopathic cultivars**

To breed new rice cultivars having strong competitiveness against weeds may bring impor‐ tant benefits to farmers in rice-cultivating nations.In the breedingprogramme, both traditional‐ ly bred and hybrid rice with allelopathy may be feasible. Courtois & Olofsdotter (1998) [88] indicated that if a high number of QTLs with low effect are involved, a traditional breeding method can be a reasonable alternative, in which two parents with contrasting behaviour are crossedandRILsarederivedthroughthesingleseededdescentmethod(SSD).Kim&Shin(2003) [106] crossed Donginbyeo (a non-allelopathic cultivar, but a high yielding rice of good quali‐ ty) and Kouketsumochi (an allelopathic cultivar, close to a wild type) and advanced by SSD breeding method. The F5 of this cross exhibited allelopathic potential in bioassays and was continuously examined under field conditions. The three-line hybrid rice widely cultivated in China may be a good source because of its rapid and profuse vegetative growth in comparison with an inbred line [106]. Lin et al. (2000) [107] applied a simultaneous backcrossing and selfbreeding method to develop a hybrid rice with allelopathic activity and, its counter-part, an isogenic hybrid rice with no allelopathic effect on weeds. Three lines of rice Kouketsumochi, Rexmont and IR24 were used as the allelopathic donors, non-allelopathic and restoring genes, respectively. The selected restorer lines were crossed with cytoplasm-sterile lines and tested for the outcross rate. This work illustrated a scheme for developing hybrid rice having allelopath‐ ic potential. On the other hand, the heterotic effect on rice allelopathy was positively significant, showing higher heterosis over the mid-parent. This specific hybrid rice showed a suppressive effect on barnyardgrass, exhibiting a large deviation from the resource competition curve [107]. Hybrid rice with stronger weed suppression ability could be bred, but the quality factors associated with rice allelopathy should be carefully considered in the breeding programme as an important standard for the new cultivars. A newly bred rice, namely K21 showed highly allelopathicandagronomicallyfit.This cultivarinheriteditsgoodagronomicperformance from the female parents (Dongjibyeo) and attained its potent allelopathic potential from male parent (Koutetsumochi) [108-109]. Moreover, Kim and Shin, 2008 [108] suggested that identified allelochemicals and genes which responsible for allelopathic activity can further be incorporat‐ edinto the cultivarsvia breeding or genetic engineering. Forinstance,thediterpenoidmomilac‐ tones and phenolics in rice work as the major inhibitor substances to suppress weeds, which are able to be produced in a conventional rice cultivar by inserting the genes CA4H and OsDTS2 for *p*-coumaticacidandmomilactone,respectivelythroughgeneticengineeringorevenconvention‐ al breeding [108, 85, 103]. Also, Kong et al. 2011 [84] has successfully developed commercially acceptable allelopathic rice cultivars via crosses between allelopathic rice variety PI12777 and commercialcultivars.ThebredHuagan-3showed80%inhibitiononnoxiousbarnyardgrassand 30-50% of a total reduction in paddy weeds. However, it should be noted that developing allelopathic rice cultivars must therefore be accompanied with an evaluation of the cultural practices required for consistent suppression under variable environmental conditions [84, 86]. On the other hand, before starting any plant breeding program to enhance allelopathic activi‐ ty, it is important to utilize a practical effective screening method in both controlled and natural conditions for measurement of allelopathic potential. It is hoped that with assistance of modern genetic techniques, new rice cultivars with strong weed suppression ability and acceptable for cultivation by farmers will hopefully appear very soon.

sis of phenolic compounds and reduced expression of enzyme genes associated with terpenoid biosynthesis [103]. The identification of these genes and proteins shows different signs, plantenvironment interactions or plant-plant communication triggering the biosynthesis of phenolic compounds that are also known to be related with plant defence processes [102,104]. Moreover, allelopathic enhancement of allelopathic rice cultivars in the vicinity of barnyard‐ grass was due to improvement in carbon assimilation deriving from the regulation of

To breed new rice cultivars having strong competitiveness against weeds may bring impor‐ tant benefits to farmers in rice-cultivating nations.In the breedingprogramme, both traditional‐ ly bred and hybrid rice with allelopathy may be feasible. Courtois & Olofsdotter (1998) [88] indicated that if a high number of QTLs with low effect are involved, a traditional breeding method can be a reasonable alternative, in which two parents with contrasting behaviour are crossedandRILsarederivedthroughthesingleseededdescentmethod(SSD).Kim&Shin(2003) [106] crossed Donginbyeo (a non-allelopathic cultivar, but a high yielding rice of good quali‐ ty) and Kouketsumochi (an allelopathic cultivar, close to a wild type) and advanced by SSD breeding method. The F5 of this cross exhibited allelopathic potential in bioassays and was continuously examined under field conditions. The three-line hybrid rice widely cultivated in China may be a good source because of its rapid and profuse vegetative growth in comparison with an inbred line [106]. Lin et al. (2000) [107] applied a simultaneous backcrossing and selfbreeding method to develop a hybrid rice with allelopathic activity and, its counter-part, an isogenic hybrid rice with no allelopathic effect on weeds. Three lines of rice Kouketsumochi, Rexmont and IR24 were used as the allelopathic donors, non-allelopathic and restoring genes, respectively. The selected restorer lines were crossed with cytoplasm-sterile lines and tested for the outcross rate. This work illustrated a scheme for developing hybrid rice having allelopath‐ ic potential. On the other hand, the heterotic effect on rice allelopathy was positively significant, showing higher heterosis over the mid-parent. This specific hybrid rice showed a suppressive effect on barnyardgrass, exhibiting a large deviation from the resource competition curve [107]. Hybrid rice with stronger weed suppression ability could be bred, but the quality factors associated with rice allelopathy should be carefully considered in the breeding programme as an important standard for the new cultivars. A newly bred rice, namely K21 showed highly allelopathicandagronomicallyfit.This cultivarinheriteditsgoodagronomicperformance from the female parents (Dongjibyeo) and attained its potent allelopathic potential from male parent (Koutetsumochi) [108-109]. Moreover, Kim and Shin, 2008 [108] suggested that identified allelochemicals and genes which responsible for allelopathic activity can further be incorporat‐ edinto the cultivarsvia breeding or genetic engineering. Forinstance,thediterpenoidmomilac‐ tones and phenolics in rice work as the major inhibitor substances to suppress weeds, which are able to be produced in a conventional rice cultivar by inserting the genes CA4H and OsDTS2 for *p*-coumaticacidandmomilactone,respectivelythroughgeneticengineeringorevenconvention‐ al breeding [108, 85, 103]. Also, Kong et al. 2011 [84] has successfully developed commercially acceptable allelopathic rice cultivars via crosses between allelopathic rice variety PI12777 and

photosynthesis genes and the activation of the enzyme system [103, 105].

**8.4. Breeding new rice allelopathic cultivars**

88 Herbicides - Current Research and Case Studies in Use

### **9. Benefits from allelopathy integrated into sustainable agriculture**

If allelopathy can be integrated into sustainable agriculture appropriately, the heavy depend‐ ence on synthetic pesticides and other agrochemicals can be significantly minimized. Mono culture has caused imbalances in agricultural production, and this would be replaced by a more ecological and sustainable cropping system. In modern agriculture with its shortage of labour, it is difficult to completely alter the use of agrochemicals, but the biological character‐ istics of crops including allelopathy and strength of competition should be exploited to reduce the amount of pesticides and agrochemicals used. Furthermore, unsafe pesticides and agrochemicals must be replaced by safer bioactive products, which are derived from living organisms such as plants, fungi, bacteria, and micro-organisms. The detrimental effects from allelopathy integration into agricultural production should also be noted, as only their benefits have been detailed [37]. The competition and chemical interaction of crops can effectively inhibit weeds and other pests, but they may also have harmful effects for crops in the next cropping seasons. Allelochemicals released from living plants and decomposition includes many toxins, which may suppress growth of useful bacteria, fungi, and micro-organisms, but they may cause problems to mineralization and nitrification in soils. This issue can be excluded with common crops, but should be examined when plant (other than common crops and legumes) materials are incorporated into soils. This style of application is still useful in many developing countries, in which a major proportion of the population is still involved in agricultural production. The modes of action of allelochemicals need further research to exploit novel allelochemicals and their derivatives in the development of bioactive pesticides. However, in addition, the extent to which they cause detrimental effects to crops and soils needs careful examination. Despite the fact that many hypotheses have been developed and discussed, and many experiments have been carried out to test them, the actual modes of action of allelopathy in nature are still somewhat unclear, unlike the allelopathic phenomena that we could easily observe. The allelopathic characteristics of plants have been known for centuries, and extensive research worldwide has been conducted for more than 40 years to elucidate the mode of allelopathy as well as efforts to utilize allelopathy more effectively in agricultural production. However, it can be said that farmers have not yet received much efficacy from what has been observed and reported. Much knowledge on plant allelopathy has been documented, but few approaches have already been successfully applied in agricultural

practice. There is no doubt that organic and sustainable agricultural practices are indispensable forms of resource management, with the source of knowledge being traditional agriculture throughout the world [37,110]. What we have researched and discussed about multiple cropping, the use of cover crops, organic compost, and biological controls of pests has been traditionally conducted by farmers without knowledge of allelopathy. Therefore, our ach‐ ievements on allelopathy should be carefully incorporated with the traditional practices of farmers to create sustainable agriculture integrated with allelopathy. Otherwise, this system will never be feasible for farmers to adopt for economic reasons and in the complex ecological conditions of the tropics, these practices would be inappropriate [110]. In our modern agri‐ culture, ecological and sustainable factors are indispensable. Therefore, what crop species are used and how they are applied in the cropping system are important. Of which, both crop allelopathy and nutrient cycle should be further studied to enhance biological characteristics of crops in the agricultural production. The establishment of allelopathy-integrated sustaina‐ ble agriculture is obviously varied among cultivating regions, of which opinions of farmers regarding traditional cropping system should be referred, and should be carefully examined and repeated before introducing to farmers for agricultural practices. An agricultural produc‐ tion that is sustainable, economical, less labour-intensive, can be easily implemented by farmers, and supported by local authorities could be helpful for farmers in developing countries to eliminate poverty. To date, a number of phytotoxins involved in the allelopathic activities of worldwide rice cultivars have been identified and isolated, and the fate of these compounds in the environment has been gradually understood, and mode of allelopathy is therefore much clearer. Many novel secondary metabolites have been synthesized and marketed as bioactive pesticides, which effectively aid the integration of sustainable agricul‐ ture with allelopathy. The use of allelopathy as a tool for a more bio-rational management of natural resources is not a simple panacea for the solution of ecological problems in agroecosystems or in natural ecosystems. It is necessary to develop a scientific approach based on the disciplines of botany, ecology, chemistry, microbiology, agronomy, entomology, and biochemistry, and to work together to clarify these bio-chemical interactions from a holistic point of view, as well as utilize them for beneficial purposes in the management of natural resources in agro-ecosystems [37, 110]. The application of crop rotation, cover crop, mulch, green manure, and incorporation of plant materials with strong allelopathic potential may be more effective in the agricultural practice. The integration of allelopathy via breeding and/or genetic manipulation in rice cultivars may clearly provide specific opportunities for successful implementation of alternative weed management systems [111]. However, knowledge about allelopathy for weed and pest management and establishment of sustainable agriculture integrated with allelopathy should be further introduced to local extension workers and farmers. The modification of allelopathy-integrated sustainable agriculture is needed to allow it to be suitable for different regions. Undoubtedly, the integration of allelopathy in rice will benefit from worldwide collaboration with ecologists, plant breeders, and molecular biologists leading to the successful utilization of new tools for selection of rice cultivars with weedsuppressive traits.

**Author details**

, L.H. Linh1

and T.D. Xuan2\*

, T.H. Linh1

, N.T. Quan1

1 Department of Molecular Biology, Agricultural Genetics Institute, Vietnam

germplasm. Annals of Applied Biology 1995; 127 543–560.

\*Address all correspondence to: tdxuan@hiroshima-u.ac.jp; khanhkonkuk@gmail.com

2 Graduate School for International Development and Cooperation (IDEC), Hiroshima Uni‐

[1] Khanh TD, Chung IM, Xuan TD, Tawata S. The exploitation of crop allelopathy in sustainable agricultural production. Journal of Agronomy and Crop Science 2005;

[2] Olofsdotter M, Navarez D, Moody K. Allelopathy potential in rice (*Oryza sativa* L.)

[3] Molisch H. Der Einfluss einer Pflanze auf die andere—Allelopathie. Jena, Germany:

[4] Rice EL. Allelopathy. Physiological Ecology. New York, NY: Academic Press; 1974.

[6] Rice EL. Allelopathy. Physiological Ecology. Orlando, FL: Academic Press; 1984

[5] Romeo JT, Weidenhamer JD. Bioassays for allelopathy in terrestrial plants. In: Eds. Haynes KF and Millar JG. (eds.) Methods in Chemical Ecology. MA: Kluwer Aca‐

[7] An M, Pratley JE, Haig T, Jellett P. Genotypic variation of plant species to the allelo‐ pathic effect of vulpia residues. Australian Journal of Experimental Agriculture 1997;

[8] Shibayama H. Weeds and weed management in rice production in Japan. Weed Biol‐

[9] Olofsdotter M, Navarez D, Rebulanan M, Streibig JC. Weed suppressing rice culti‐

[10] Khanh TD, Xuan TD, Chung IM. Rice allelopathy and the possibility for weed man‐

[11] Khanh TD, Elzaawely AA, Chung IM, Ahn JK, Tawata S, Xuan TD. Role of allelo‐ chemicals for weed management in rice. Allelopathy Journal 2007; 19 85-96.

vars—does allelopathy play a role? Weed Research 1999; 39 441–454.

agement. Annals of Applied Biology 2007; 151 324-339.

, D.M. Cuong1

, V.T.T. Hien1

Integration of Allelopathy to Control Weeds in Rice

, L.H. Ham1

http://dx.doi.org/10.5772/56035

,

91

T.D. Khanh1

K.H. Trung1

versity, Japan

**References**

191 172–184.

37 647–660.

Gustav Fischer; 1937.

demic Publishing; 1999. p179–211.

ogy and Management 2001 1 53–60.

### **Author details**

practice. There is no doubt that organic and sustainable agricultural practices are indispensable forms of resource management, with the source of knowledge being traditional agriculture throughout the world [37,110]. What we have researched and discussed about multiple cropping, the use of cover crops, organic compost, and biological controls of pests has been traditionally conducted by farmers without knowledge of allelopathy. Therefore, our ach‐ ievements on allelopathy should be carefully incorporated with the traditional practices of farmers to create sustainable agriculture integrated with allelopathy. Otherwise, this system will never be feasible for farmers to adopt for economic reasons and in the complex ecological conditions of the tropics, these practices would be inappropriate [110]. In our modern agri‐ culture, ecological and sustainable factors are indispensable. Therefore, what crop species are used and how they are applied in the cropping system are important. Of which, both crop allelopathy and nutrient cycle should be further studied to enhance biological characteristics of crops in the agricultural production. The establishment of allelopathy-integrated sustaina‐ ble agriculture is obviously varied among cultivating regions, of which opinions of farmers regarding traditional cropping system should be referred, and should be carefully examined and repeated before introducing to farmers for agricultural practices. An agricultural produc‐ tion that is sustainable, economical, less labour-intensive, can be easily implemented by farmers, and supported by local authorities could be helpful for farmers in developing countries to eliminate poverty. To date, a number of phytotoxins involved in the allelopathic activities of worldwide rice cultivars have been identified and isolated, and the fate of these compounds in the environment has been gradually understood, and mode of allelopathy is therefore much clearer. Many novel secondary metabolites have been synthesized and marketed as bioactive pesticides, which effectively aid the integration of sustainable agricul‐ ture with allelopathy. The use of allelopathy as a tool for a more bio-rational management of natural resources is not a simple panacea for the solution of ecological problems in agroecosystems or in natural ecosystems. It is necessary to develop a scientific approach based on the disciplines of botany, ecology, chemistry, microbiology, agronomy, entomology, and biochemistry, and to work together to clarify these bio-chemical interactions from a holistic point of view, as well as utilize them for beneficial purposes in the management of natural resources in agro-ecosystems [37, 110]. The application of crop rotation, cover crop, mulch, green manure, and incorporation of plant materials with strong allelopathic potential may be more effective in the agricultural practice. The integration of allelopathy via breeding and/or genetic manipulation in rice cultivars may clearly provide specific opportunities for successful implementation of alternative weed management systems [111]. However, knowledge about allelopathy for weed and pest management and establishment of sustainable agriculture integrated with allelopathy should be further introduced to local extension workers and farmers. The modification of allelopathy-integrated sustainable agriculture is needed to allow it to be suitable for different regions. Undoubtedly, the integration of allelopathy in rice will benefit from worldwide collaboration with ecologists, plant breeders, and molecular biologists leading to the successful utilization of new tools for selection of rice cultivars with weed-

90 Herbicides - Current Research and Case Studies in Use

suppressive traits.

T.D. Khanh1 , L.H. Linh1 , T.H. Linh1 , N.T. Quan1 , D.M. Cuong1 , V.T.T. Hien1 , L.H. Ham1 , K.H. Trung1 and T.D. Xuan2\*

\*Address all correspondence to: tdxuan@hiroshima-u.ac.jp; khanhkonkuk@gmail.com

1 Department of Molecular Biology, Agricultural Genetics Institute, Vietnam

2 Graduate School for International Development and Cooperation (IDEC), Hiroshima Uni‐ versity, Japan

### **References**


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**Chapter 5**

**Weed and Disease Control and Peanut**

**Response Following Post—Emergence**

**Herbicide and Fungicide Combinations**

Peanut, or groundnut (*Arachis hypogaea* L.), is a species in the legume or "bean" family (Faba‐ ceae). Hypogaea means "under the earth" [1]. Peanuts are known by many other local names such as earthnuts, goober peas, monkey nuts, pygmy nuts and pig nuts [2,3]. Peanut was

The domesticated peanut is an amphidiploid or allotetraploid, meaning that it has two sets of chromosomes from two different species, thought to be *A*. *duranensis* and *A. ipaensis*. These likely combined in the wild to form the tetraploid species, *A*. *monticola*, which gave rise to the domesticated peanut [4,5]. This domestication might have taken place in Paraguay or Bolivia, where the wildest strains are found today. Archeologists have dated the oldest specimens to about 7,600 years, found in Peru [3,4]. Cultivation spread as far as Mesoamerica where the Spanish conquistadors found the tlalcacahuatl (Nahuatl = "peanut", whence Mexican Spanish, cacahuate and French, cacahuète) being offered for sale in the marketplace of Tenochtitlan

Peanuts grow best in light, sandy loam soil. They require 120 to 150 days of warm weather, and an annual rainfall of 380 to 650 mm or the equivalent in irrigation water [6]. It is an annual herbaceous plant growing 30 to 50 cm tall. The leaves are opposite, pinnate with four leaflets (two opposite pairs; no terminal leaflet), each leaflet 1 to 7 cm long and 1 to 3 cm wide. The orange-veined, yellow-petaled, pea-like flower (2 to 4 cm across) of *A*. *hypogaea* is borne in axillary clusters above ground. Following self-pollination, the flowers fade and wither. The stalk at the base of the ovary, called the pedicel, elongates rapidly, and turns downward.

> © 2013 Grichar et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

Santín-Montanyá et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 Grichar et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

probably first domesticated and cultivated in the valleys of Paraguay [3].

(Mexico City). The plant was later spread worldwide by European traders [3].

W. James Grichar, Peter A. Dotray and

Additional information is available at the end of the chapter

Jason E. Woodward

**1. Introduction**

http://dx.doi.org/10.5772/55949
