Yield Components and Biomass Partition in Soybean: Climate Change Vision

*Milton E. Pereira-Flores and Flávio B. Justino*

## **Abstract**

Long-term climate change and inter-annual climate variability are events of concern to farmers and humanity. Global warming could affect agriculture in various ways and it is anticipated that agricultural systems will face great pressure from the variability of climate factors and their extreme events, which in most cases are difficult to predict, particularly extreme events of rainfall, higher dry season, hot and cold waves and their interactions. Global warming could also have some positive effects for plants such as increasing the temperature of current cold regions and increasing carbon dioxide with its positive effect on photosynthesis, growth rates, the use of water and production. Meanwhile, there are still many questions that remain about this possible future. This chapter, brings the response of plants to future conditions through specifics alterations in its components of yield on environmental conditions with enrichment of CO2 and elevated temperature, two climatic factors, which is understood to be the factors of climatic change of greater global extent. The study of the components of yield and their alterations, can guide diverse sectors of the sciences and decision makers, in order to structure strategies of resilience in the cultivation of soybean.

**Keywords:** yield components, soybean, global climate change, elevated CO2 and temperatures, production

## **1. Introduction**

Global climate models predict increases in air temperature by up to 2–4°C, CO2 concentrations higher than 700 mmol.mol<sup>−</sup><sup>1</sup> and increase in ground O3 higher than 70 ppb by the end of the year 2100 [1, 2].

Based on these projections about the changes in the growth environment of the cultivated plants, it will be prudent to know how the current cultivars can be affected in their yield components, which are what define the productive potential.

Despite the existence of many studies simulating future scenarios made in FACE (Free-CO2 environmental), OTC (open top chamber) and Growth Chambers to know how the altered climate factors will affect the physiology and production of soybean, few studies have been directed to understand those alterations in the level of the yield components that are the intrinsic factors of the plant more sensitive to climate change, and that also depend on the management of the crop at the field

level. This anticipated knowledge may be important for the direction of policies and research lines in various areas of agricultural sciences to develop diverse resilience strategies to climate change.

The understanding of how climate influences the growth, development and production of soybean plants depends on the understanding of how the yield components respond to the variations of climate factors, which can also be elucidated if studies the plant alterations in the future atmosphere conditions. The plant production is determined by changes in yield components, in last instance. The artificial enrichment of the growth environment of soybean plants with CO2, O3 and temperatures according to the forecasts on the atmospheric composition for the year 2100, can allow to know the morphophysiological responses in several levels of the plant organization, long before environmental changes occur.

The study of the morphophysiological mechanisms of response of soybean plants to the ecological environment where they develop and produce grains, constitutes the basis of soybean ecophysiology.

The factors of the climate (temperature, radiation, rainfall, wind and atmospheric pressure, among others), plus the physicochemical properties of the soil and the cultural practices applied in the field continuously influence the performance of the community of soya plants from germination to the senescence of the plants. Throughout the different phenological stages, the expression of stage-tissue genes defines the course of the development of the plant, the formation of the biomass and its components (roots, stems, leaves, flowers, fruits and seeds) respond simultaneously and hierarchically with the objective of completing its biological cycle and producing seeds for the perpetuation of the plant, and that for humanity represents the basis of agricultural production.

The most important climatic factors for the development and production of soybean cultivars are temperature and photoperiod and their interactions, plus other favorable/limiting factors and resources such as precipitation variability, appropriate supply of nutrients and elimination of inter- and intraspecific competition, which also interact to determine the production of soybeans in a given region [3, 4].

The temperature is directly related to the speed of the metabolic rates and the chronological duration of the different phenological stages of the crop, and in the case of floral induction, in interaction with the photoperiod in plants responsive to the duration of the night to flower. The photothermal influence in the growth stages can be predicted by unit heats method. In general, the temperature determines the growth rates and the duration, in days, of each stage of the development phases. Soybeans have cardinal temperatures for most of their developmental stages [5, 6].

According to the American Society of Meteorology, cardinal temperatures correspond to the minimum (Tb) and maximum (TB) temperatures that define the limits of growth and development of an organism and an optimal temperature (Top) in which growth proceeds more rapidly (htpp://glossary.ametsoc.org/wiki/ Cardinal\_temperatures). According to the above, the rate of development increases linearly between Tb and Top; decreases from Top to TB, and after TB the development stops and the duration of the phase becomes infinite. It is possible to specify that Top, is not a thermal point, but the average of a very narrow range of temperatures, where the majority of the enzymatic reactions that participate in the growth is close to their catalytic maximums.

The soybean cardinal temperatures defined several plant processes from temperature thresholds. The lower base temperature (Tb) vary between 6 and 10°C to plant development. The lower thermal thresholds are: (Tb) of 10°C [7], 11°C [8], and 14°C [9].

**25**

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

The germination rate is close to zero at 15°C and maximum at 25°C [10]. Other

In general, vegetative and reproductive growth in soybean can reach high rates in temperatures between 25°C and 30°C during the growth season, because the maximal vegetative and reproductive development occur in 30°C and 25-29°C, respectively. In addition the optimal floral anthesis temperature is achieved in 26°C [16, 17]. Thus, the choice of the time of year considering the regime of soil and air temperatures are determinant to establish the best sowing times, in which the thermal supply of the soil-atmosphere system is satisfactory, together with the adequate availability of water to meet the consumptive use of the crop. In fact, soybean yield components are negatively correlated with temperature increase and these components are temperature-dependent [18, 19], mainly, when the temperatures on field

The main effect of the photoperiod is to induce flowering after the juvenile phase is over. Low temperatures and long days delayed the flowering time, and consequently, the anthesis and the maturation time [22, 23]. This relation is widely known, as well as, that the greater sensitivity to photoperiod and low temperatures are more obvious among the genotypes with greater sensitivity to the photoperiod; late maturation cultivars are more sensitive than early cultivars [24]. Most of the soybean cultivars have a pre-inductive or short juvenile stage, and floral induction may occur at any stage after the development of the first unifoliate leaves [25]. With the incorporation of long juvenile periods, soybeans currently produce soybeans until the 15th degree of Latitude, preventing the early induction of flowering [26]. The variation of flowering time between soybean cultivars, from a genetic point

of view is very complex, because it will probably not be so easy to identify the molecular bases of the major genes and Quantitative Trait Loci (QTLs) underlying the natural variation in flowering time of soybean, because most of those genes and QTLs exist in multiple copies in the genome, interacting more or less with one another and with the environments in which the genes are evaluated [27]. In the specific case of soybean, some cultivars must fulfill a juvenile stage before the influence of the photoperiod for the induction of flowering, and the sensitivity can occur from the expansion of the first V1-V2 vegetative stages (first and second trifoliate leaf) [28]. From then on, the taxa of growth and development of the plants will be a function of the availability of light, water, nutrients, and above all, of the temperature up to values close to the optimal Day/Night temperature. In turn, after flowering induction plus higher temperatures the duration of this inductive stage can be varied and influence the size and characteristics of the canopy, that is, the height of plants, the number and length of productive branches, effective leaf area

Rainfall is the most common form of water supply, and its intensity and variability are pointed out as determinants of the risk to the success of production in most soy producing regions in Brazil, EUA and China [29]. Precipitations between 450 and 800 mm may allow high yields depending on distribution throughout the cultivar cycle and on edaphic and climatic conditions [30]. However, this high yield potential is soil type and climate dependent, mainly of the interaction with temperature, evapotranspiration, and soil water content. The interannual variability of those climatic factors provoked by the climatic changes are

thermal threshold to highest growth was found between 29 and 31°C [11, 12], thermal threshold that is the same to maxima protein content in the grains [13]. For photosynthesis, optimum diurnal temperatures are between 30 and 35°C, and for growth, night temperatures between 21 and 27°C. Temperatures less than 22°C delay the retention of pods and at temperatures ≤14°C flower abortion may occur [14]. Temperatures close to or above 40°C have negative effects on growth

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

exceed the optimum temperatures [20, 21].

and number of flowers per cluster, among others.

rate and pod retention [15].

The germination rate is close to zero at 15°C and maximum at 25°C [10]. Other thermal threshold to highest growth was found between 29 and 31°C [11, 12], thermal threshold that is the same to maxima protein content in the grains [13].

For photosynthesis, optimum diurnal temperatures are between 30 and 35°C, and for growth, night temperatures between 21 and 27°C. Temperatures less than 22°C delay the retention of pods and at temperatures ≤14°C flower abortion may occur [14]. Temperatures close to or above 40°C have negative effects on growth rate and pod retention [15].

In general, vegetative and reproductive growth in soybean can reach high rates in temperatures between 25°C and 30°C during the growth season, because the maximal vegetative and reproductive development occur in 30°C and 25-29°C, respectively. In addition the optimal floral anthesis temperature is achieved in 26°C [16, 17]. Thus, the choice of the time of year considering the regime of soil and air temperatures are determinant to establish the best sowing times, in which the thermal supply of the soil-atmosphere system is satisfactory, together with the adequate availability of water to meet the consumptive use of the crop. In fact, soybean yield components are negatively correlated with temperature increase and these components are temperature-dependent [18, 19], mainly, when the temperatures on field exceed the optimum temperatures [20, 21].

The main effect of the photoperiod is to induce flowering after the juvenile phase is over. Low temperatures and long days delayed the flowering time, and consequently, the anthesis and the maturation time [22, 23]. This relation is widely known, as well as, that the greater sensitivity to photoperiod and low temperatures are more obvious among the genotypes with greater sensitivity to the photoperiod; late maturation cultivars are more sensitive than early cultivars [24]. Most of the soybean cultivars have a pre-inductive or short juvenile stage, and floral induction may occur at any stage after the development of the first unifoliate leaves [25]. With the incorporation of long juvenile periods, soybeans currently produce soybeans until the 15th degree of Latitude, preventing the early induction of flowering [26].

The variation of flowering time between soybean cultivars, from a genetic point of view is very complex, because it will probably not be so easy to identify the molecular bases of the major genes and Quantitative Trait Loci (QTLs) underlying the natural variation in flowering time of soybean, because most of those genes and QTLs exist in multiple copies in the genome, interacting more or less with one another and with the environments in which the genes are evaluated [27]. In the specific case of soybean, some cultivars must fulfill a juvenile stage before the influence of the photoperiod for the induction of flowering, and the sensitivity can occur from the expansion of the first V1-V2 vegetative stages (first and second trifoliate leaf) [28]. From then on, the taxa of growth and development of the plants will be a function of the availability of light, water, nutrients, and above all, of the temperature up to values close to the optimal Day/Night temperature. In turn, after flowering induction plus higher temperatures the duration of this inductive stage can be varied and influence the size and characteristics of the canopy, that is, the height of plants, the number and length of productive branches, effective leaf area and number of flowers per cluster, among others.

Rainfall is the most common form of water supply, and its intensity and variability are pointed out as determinants of the risk to the success of production in most soy producing regions in Brazil, EUA and China [29]. Precipitations between 450 and 800 mm may allow high yields depending on distribution throughout the cultivar cycle and on edaphic and climatic conditions [30]. However, this high yield potential is soil type and climate dependent, mainly of the interaction with temperature, evapotranspiration, and soil water content. The interannual variability of those climatic factors provoked by the climatic changes are

*Soybean - Biomass, Yield and Productivity*

strategies to climate change.

level. This anticipated knowledge may be important for the direction of policies and research lines in various areas of agricultural sciences to develop diverse resilience

The understanding of how climate influences the growth, development and production of soybean plants depends on the understanding of how the yield components respond to the variations of climate factors, which can also be elucidated if studies the plant alterations in the future atmosphere conditions. The plant production is determined by changes in yield components, in last instance. The artificial enrichment of the growth environment of soybean plants with CO2, O3 and temperatures according to the forecasts on the atmospheric composition for the year 2100, can allow to know the morphophysiological responses in several levels of

The study of the morphophysiological mechanisms of response of soybean plants to the ecological environment where they develop and produce grains,

The factors of the climate (temperature, radiation, rainfall, wind and atmospheric pressure, among others), plus the physicochemical properties of the soil and the cultural practices applied in the field continuously influence the performance of the community of soya plants from germination to the senescence of the plants. Throughout the different phenological stages, the expression of stage-tissue genes defines the course of the development of the plant, the formation of the biomass and its components (roots, stems, leaves, flowers, fruits and seeds) respond simultaneously and hierarchically with the objective of completing its biological cycle and producing seeds for the perpetuation of the plant, and that for humanity

The most important climatic factors for the development and production of soybean cultivars are temperature and photoperiod and their interactions, plus other favorable/limiting factors and resources such as precipitation variability, appropriate supply of nutrients and elimination of inter- and intraspecific competition, which also interact to determine the production of soybeans in a given

The temperature is directly related to the speed of the metabolic rates and the chronological duration of the different phenological stages of the crop, and in the case of floral induction, in interaction with the photoperiod in plants responsive to the duration of the night to flower. The photothermal influence in the growth stages can be predicted by unit heats method. In general, the temperature determines the growth rates and the duration, in days, of each stage of the development phases. Soybeans have cardinal temperatures for most of their

According to the American Society of Meteorology, cardinal temperatures correspond to the minimum (Tb) and maximum (TB) temperatures that define the limits of growth and development of an organism and an optimal temperature (Top) in which growth proceeds more rapidly (htpp://glossary.ametsoc.org/wiki/ Cardinal\_temperatures). According to the above, the rate of development increases linearly between Tb and Top; decreases from Top to TB, and after TB the development stops and the duration of the phase becomes infinite. It is possible to specify that Top, is not a thermal point, but the average of a very narrow range of temperatures, where the majority of the enzymatic reactions that participate in the growth

The soybean cardinal temperatures defined several plant processes from temperature thresholds. The lower base temperature (Tb) vary between 6 and 10°C to plant development. The lower thermal thresholds are: (Tb) of 10°C [7], 11°C [8],

the plant organization, long before environmental changes occur.

constitutes the basis of soybean ecophysiology.

represents the basis of agricultural production.

**24**

and 14°C [9].

region [3, 4].

developmental stages [5, 6].

is close to their catalytic maximums.

characterized by the occurrence of extreme events of excess and precipitation deficit and heat waves in relation to the normal climatological is great determinant of the soybean yield [31, 32]. The occurrence of prolonged "veranicos" (absence of rainfall for 25 continuous days or more during the summer) has been more frequent and prolonged, for example, in December and February in the central region of Brazil and pointed as the most dangerous condition for the success of soybean plantations.

## **2. Yield and yield components**

## **2.1 Yield production**

The increase in soybean production under high [CO2] has been variable, ranging from increases of about 17%, marginal increases [33, 34], and no gain in production [35]. In most cases the increases have been derived mainly from gains in the total weight of grains at harvest, the increase in the number of pods [36] and the average weight of the grains [34, 37].

In understanding the magnitude of differences in production gains over high CO2 concentrations, we should consider aspects such as the type of cultivar, production system and densities used, and the interaction with the climatic factors of each region where the plantations occurred. For example, it was verified increases in biomass and seed weight in the day/night thermal regimes 20/15°C compared with elevated thermal day/night regime like 30/25°C under 700 ppm CO2 [38]. In other similar study, a greater number of branches and productive nodes were formed in 26/20 than in 22/16°C [39]. In this case, the positive interaction between elevated [CO2] and temperatures regimes, resulting in increases in production. Thus, it can be concluded that the closer to the temperature regime of the optimum temperature, positive interaction can be expected for greater production, than when the temperatures exceed the Top. However, the meta-analysis performed on the results of several studies on the productive response of soybeans to CO2 increase shows that, despite increases in foliar absorption of CO2, soybean production is less responsive in experimental conditions and that the responses in field conditions were smaller than those performed in confinement (pot use) [37] The question, again, goes back to the point of knowing how to explain this low response at plant level.

Recently, a study conducted with 18 soybean cultivars (II, III, IV soybean groups) conducted in several years repeated with 550 ppm of CO2, found average responses of 22% increase in the aerial biomass and only 9% in the yield of the seed, when grown in the appropriate growing season, and average temperatures of the growing season varying between 20.7 and 23.3°C [40]. During 4 years of study, there was consistency from year to year among genotypes that were more and less sensitive to the elevation of [CO2], suggesting heritability of the CO2 response [40]. In addition, cultivars with the highest coefficient of partition to the seed in the current [CO2] also had the highest partition coefficient in the high [CO2] [40]. This suggests, the existence of a variation genetic in the response of soybean to a high level of [CO2], which is necessary to obtaining cultivars of soybean that adapt to future conditions.

### **2.2 Yield component basis**

The production of agricultural crops in any environment or cropping system is ultimately the result of the biomass produced and the magnitude of that partitioned

**27**

**Figure 1.**

*determine the production per plant.*

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

biomass for the harvested organ, which is measured in terms of biomass parity by

In simple terms, production is the result of the interaction between the genetic potential of a cultivar and the biotic and abiotic factors that reduce that genetic potential. At the field level, plants are continuously subjected to multiple interactions with favorable results during most of the productive cycle, due to the plant's ability to adapt quickly to variations in soil and climate conditions and to techno-

The soybean plant is organized on the main stem on which the lateral branches and internodes are formed where flower clusters are formed (**Figure 1**). The order of the branches and bunches on the main stem are listed according to their ontoge-

During the soybean cultivation cycle, five ontogenetic stages are distinguished, which are important in the determination of yield, which are: (1) The formation of organs responsible for the fixation of CO2 and the absorption of water and nutrients (leaves and roots). (2) The formation of potential harvest organs (pods racemes in lateral branch or main stem racemes). (3) The determination of the effective density of harvest organs (number of pods/raceme-plant). (4) The filling of the harvest organs (number of filling seeds/pod, weight seed/pod). (5) Loss of functionality of leaves and roots (vegetative organs senescence, mature seeds in the pods) [41].

These stages develop successively with a degree of mutual overlap that varies with

Two components of production are essential in the determination of soybean production. The number of grains per plant and the weight of the grains. The number of grains per plant is more closely associated with yield and is the most sensitive to the influence of the environment. This depends on the morphogenesis of reproductive structures on top of which are formed as are branches and clusters

Ontogenetically, the number of flowers in soy largely exceeds the potential capacity for fixation, even under restrictive environmental conditions. The fixation of the grains depends on the fixation of the pods and this characteristic is very sensitive to the availability of resources, so any physiological stress during the fixation of the pods determines the levels of pod abortion, consequently of the grain potential [41, 45–47]. However, between flowering and fully developed pod (R4) or start grain filling (R5) there may be compensation between yield components, fewer pods compensate with an increase in the number of grains per pod and/or

Thus, in studies on the plant effects of high concentrations of CO2 and O3 it will be important to define the density of plants in the experimental field that avoid

*Plant structure scheme with the branches and racemes contain pods, and the yield components in soybean which* 

the type of cultivar and the environmental conditions of growth [41–44].

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

logical support through agricultural practices.

the harvest index (HI).

netic chronology.

of the main trunk [41, 45–47].

grain weight.

### *Yield Components and Biomass Partition in Soybean: Climate Change Vision DOI: http://dx.doi.org/10.5772/intechopen.81627*

biomass for the harvested organ, which is measured in terms of biomass parity by the harvest index (HI).

In simple terms, production is the result of the interaction between the genetic potential of a cultivar and the biotic and abiotic factors that reduce that genetic potential. At the field level, plants are continuously subjected to multiple interactions with favorable results during most of the productive cycle, due to the plant's ability to adapt quickly to variations in soil and climate conditions and to technological support through agricultural practices.

The soybean plant is organized on the main stem on which the lateral branches and internodes are formed where flower clusters are formed (**Figure 1**). The order of the branches and bunches on the main stem are listed according to their ontogenetic chronology.

During the soybean cultivation cycle, five ontogenetic stages are distinguished, which are important in the determination of yield, which are: (1) The formation of organs responsible for the fixation of CO2 and the absorption of water and nutrients (leaves and roots). (2) The formation of potential harvest organs (pods racemes in lateral branch or main stem racemes). (3) The determination of the effective density of harvest organs (number of pods/raceme-plant). (4) The filling of the harvest organs (number of filling seeds/pod, weight seed/pod). (5) Loss of functionality of leaves and roots (vegetative organs senescence, mature seeds in the pods) [41].

These stages develop successively with a degree of mutual overlap that varies with the type of cultivar and the environmental conditions of growth [41–44].

Two components of production are essential in the determination of soybean production. The number of grains per plant and the weight of the grains. The number of grains per plant is more closely associated with yield and is the most sensitive to the influence of the environment. This depends on the morphogenesis of reproductive structures on top of which are formed as are branches and clusters of the main trunk [41, 45–47].

Ontogenetically, the number of flowers in soy largely exceeds the potential capacity for fixation, even under restrictive environmental conditions. The fixation of the grains depends on the fixation of the pods and this characteristic is very sensitive to the availability of resources, so any physiological stress during the fixation of the pods determines the levels of pod abortion, consequently of the grain potential [41, 45–47]. However, between flowering and fully developed pod (R4) or start grain filling (R5) there may be compensation between yield components, fewer pods compensate with an increase in the number of grains per pod and/or grain weight.

Thus, in studies on the plant effects of high concentrations of CO2 and O3 it will be important to define the density of plants in the experimental field that avoid

#### **Figure 1.**

*Plant structure scheme with the branches and racemes contain pods, and the yield components in soybean which determine the production per plant.*

*Soybean - Biomass, Yield and Productivity*

cess of soybean plantations.

weight of the grains [34, 37].

**2.1 Yield production**

**2. Yield and yield components**

characterized by the occurrence of extreme events of excess and precipitation deficit and heat waves in relation to the normal climatological is great determinant of the soybean yield [31, 32]. The occurrence of prolonged "veranicos" (absence of rainfall for 25 continuous days or more during the summer) has been more frequent and prolonged, for example, in December and February in the central region of Brazil and pointed as the most dangerous condition for the suc-

The increase in soybean production under high [CO2] has been variable, ranging from increases of about 17%, marginal increases [33, 34], and no gain in production [35]. In most cases the increases have been derived mainly from gains in the total weight of grains at harvest, the increase in the number of pods [36] and the average

In understanding the magnitude of differences in production gains over high CO2 concentrations, we should consider aspects such as the type of cultivar, production system and densities used, and the interaction with the climatic factors of each region where the plantations occurred. For example, it was verified increases in biomass and seed weight in the day/night thermal regimes 20/15°C compared with elevated thermal day/night regime like 30/25°C under 700 ppm CO2 [38]. In other similar study, a greater number of branches and productive nodes were formed in 26/20 than in 22/16°C [39]. In this case, the positive interaction between elevated [CO2] and temperatures regimes, resulting in increases in production. Thus, it can be concluded that the closer to the temperature regime of the optimum temperature, positive interaction can be expected for greater production, than when the temperatures exceed the Top. However, the meta-analysis performed on the results of several studies on the productive response of soybeans to CO2 increase shows that, despite increases in foliar absorption of CO2, soybean production is less responsive in experimental conditions and that the responses in field conditions were smaller than those performed in confinement (pot use) [37] The question, again, goes back to the point of knowing how to explain this low response at plant

Recently, a study conducted with 18 soybean cultivars (II, III, IV soybean groups) conducted in several years repeated with 550 ppm of CO2, found average responses of 22% increase in the aerial biomass and only 9% in the yield of the seed, when grown in the appropriate growing season, and average temperatures of the growing season varying between 20.7 and 23.3°C [40]. During 4 years of study, there was consistency from year to year among genotypes that were more and less sensitive to the elevation of [CO2], suggesting heritability of the CO2 response [40]. In addition, cultivars with the highest coefficient of partition to the seed in the current [CO2] also had the highest partition coefficient in the high [CO2] [40]. This suggests, the existence of a variation genetic in the response of soybean to a high level of [CO2], which is necessary to obtaining cultivars of soybean that adapt to

The production of agricultural crops in any environment or cropping system is ultimately the result of the biomass produced and the magnitude of that partitioned

**26**

future conditions.

**2.2 Yield component basis**

level.

high intraspecific competition during flowering and fixation of pods. An excessive competition for light can alter yield components such as number of branches and pods [34, 48, 49].

Adequate availability of light, temperature, water and nutrients during the period of performance determination, between the start of the pod formation (R3) and full green grain (R6) guarantees a high number of grains per plant [48, 50, 51, 52, 53]. It should be remembered that the plasticity in the number of grains per pod in soybeans is very low between 2.1–2.5 seed/pod [54, 55, 56], same with different cultural practices [57, 58, 59]. Thus, the number of grains per pod of soybeans can be less sensitive to stress compared to the number of pods.

The weight of grains, as the second component of the most sensitive yield, depends on the genotype and the environmental conditions that determine the photosynthesis capacity of the canopy, the translocation of assimilates, the duration of the filling stage and the competition between pods, and among grains on the same pod (source/sink ratio) [46].

The filling of the grain is strongly influenced by the availability and translocation of photoassimilates during the end of soybean development, before start of grain maturation (R7) [41]. Stresses by water deficit, thermal regime (below 25°C and above 35°C) can reduce the Leaf Area Index (LAI), thus like occurrence of rust and chronic exposures to O3 can reduce the availability and use of photoassimilates by causing early senescence of the foliar area, and decreasing the photosynthesis and assimilated production [60, 61]. Thus, the benefits of the increase in CO2 in the high photosynthesis and the more leaf area per plant can be decreased by foliar damage. Consequently, stresses during the start pod formation and the grain green full (stages R3-R6) affect the determination of the number of grains. Plant stresses between grain green full and start of grain maturation (stages R6–R7), decrease the weight of the grains on pods. On the other hand, a greater photosynthetic response in C3 plants such as soybeans to CO2 increase, or high rates of photosynthesis among soybean cultivars, may not necessarily mean significant increases in production due to environmental interactions in the field, the possible effects of photosynthetic acclimatization, the increase of photorespiration by the increase in temperatures [62], and mainly by harvest index variability of soybean [63].

Climate changes, in particular, the increase in temperature and the concentrations of CO2 and O3 affect the development patterns and characteristics of the canopy as leaf area index (LAI) and internal structure of canopy [63, 64]. The magnitude of the alterations will be proportional to the environmental sensitivity of the cultivars and the applied productive management. Cultivars less sensitive to the indicated factors, the re-adaptation of population densities and arrangements in plant spacing may be the most immediate strategy such as resilience to climate change.

### **2.3 Changes in plant height, branches and racemes**

Discussion on plant architecture is fundamental due to its link with the distribution of carbon allocation. Moreover, the understanding of plant shape allows for identification of plant features which are more strongly affected by environmental conditions such as CO2 and weather parameters. Plants grown with higher CO2 are taller than the plants in present conditions in the most several cultivars of soybean due to more nodes [34, 65, 66]. However, it is also possible to find no stimuli for the increase in the final height of the plant, which may be more likely in cultivars of certain growth habit [34]. Early results of [67] showed increase in height of the plant directly related with increase of more internodes and length of branches, or both.

**29**

environment.

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

The elevated temperature regime under CO2 enrichment influences the growth and development of soybean plants. The temperature in plants, mainly affecting cell division, elongation rates, metabolic rates of photosynthesis and respiration in

A mean temperature range of 29-31°C has been indicated as the optimum range for soybean vegetative growth [11, 12]. The main stem plastochron interval decreases and the final main stem node number increases in soybean with higher

22.5 and 32.5°C [72]. Thus, the temperature increase can be favorable if closed to optimal temperature to soybean growth, even in conditions of greater availability of photoassimilates under higher concentrations of CO2. Statistical analysis of correlation carried out by [34, 65] demonstrated a positive correlation between the plant height and the number of racemes, cultivar-dependent, under elevated

positive and significant increases in the number of nodes of soybean plant grown with elevated [CO2]. It can be argued that the interaction between elevated [CO2] and temperature in soybean influences the plant weight in two different ways, being through more number of internodes or internode length as also observed

important to note that changes in the plant height should induce modification in the configuration of other plant components, such as branches, pods and

The number of branches, racemes and total pods are the most important components for yield, and exhibit the highest correlation with the total yield [57, 74, 75]. A reduction by 18.5% in CO2 enrichment in sensible cultivar to high CO2 plant responses, and similar tendency happened in the number of pods/branch and grains/branch, with 35.1% and 35.2% decrease [34]. However, the number of grains/pods on branches can be remained unaltered in modern cultivars with small canopy or increase [66]. Based on previous studies one may anticipate that the increase of [CO2] and warmer conditions may not contribute to the increasing yield due to reduction in the number of pods and grains on branches, if the current spacing and plant density remain unchanged. High yields were found with increased spacing under elevated CO2 concentration [76]. In the evaluations of branch

ontogeny or length of branches, the greatest branching plasticity of the US cultivars compared with Japanese cultivars should also be considered, together the inverse relation between the total length of branches and the density of plants [77]. The number of the racemes per plant and the number of pods or grains per racemes also respond to higher CO2 depending on the cultivar. An increase in the number of the racemes/plant by 27% and 35% in grains/raceme in most sensitive of two cultivars, named Conquista [34]. In insensible modern cultivar (most ambient stability genotype) were not different in these characteristics. Additionally, there is a positive correlation between plant height and the number of racemes in sensible

A higher number of racemes lead to more pods and grains, which implies that a higher number of racemes in the main stem could partially compensate for the loss of pods and grains by the absence of lateral branches. The number of seeds per pod in soybean is very stable characteristic and can vary between 2.1 and 2.5 [54, 57, 58, 78] thus, the increase of the genetic plasticity of this characteristic can be a way for the increase of the productivity per unit of plant and area. Actually, this characteristic, perhaps, is the most limiting to increase the production in present and future

The reduction in the number of branches observed in sensible cultivars under high competition among plants promoted by the higher CO2 concentration can

) accompanied by a rise in mean temperature between

. But depends on the on the cultivar response. It is

and air temperatures, respectively. There was

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

the daily cycle [68–71].

[CO2] (660 μmolmol<sup>−</sup><sup>1</sup>

CO2 with 750 and 548 μmol.mol<sup>−</sup><sup>1</sup>

cultivar (Conquista) (r = 0.67; P ≤ 0.005) [34].

by [73] in 700 μmol.mol<sup>−</sup><sup>1</sup>

racemes.

The elevated temperature regime under CO2 enrichment influences the growth and development of soybean plants. The temperature in plants, mainly affecting cell division, elongation rates, metabolic rates of photosynthesis and respiration in the daily cycle [68–71].

A mean temperature range of 29-31°C has been indicated as the optimum range for soybean vegetative growth [11, 12]. The main stem plastochron interval decreases and the final main stem node number increases in soybean with higher [CO2] (660 μmolmol<sup>−</sup><sup>1</sup> ) accompanied by a rise in mean temperature between 22.5 and 32.5°C [72]. Thus, the temperature increase can be favorable if closed to optimal temperature to soybean growth, even in conditions of greater availability of photoassimilates under higher concentrations of CO2. Statistical analysis of correlation carried out by [34, 65] demonstrated a positive correlation between the plant height and the number of racemes, cultivar-dependent, under elevated CO2 with 750 and 548 μmol.mol<sup>−</sup><sup>1</sup> and air temperatures, respectively. There was positive and significant increases in the number of nodes of soybean plant grown with elevated [CO2]. It can be argued that the interaction between elevated [CO2] and temperature in soybean influences the plant weight in two different ways, being through more number of internodes or internode length as also observed by [73] in 700 μmol.mol<sup>−</sup><sup>1</sup> . But depends on the on the cultivar response. It is important to note that changes in the plant height should induce modification in the configuration of other plant components, such as branches, pods and racemes.

The number of branches, racemes and total pods are the most important components for yield, and exhibit the highest correlation with the total yield [57, 74, 75]. A reduction by 18.5% in CO2 enrichment in sensible cultivar to high CO2 plant responses, and similar tendency happened in the number of pods/branch and grains/branch, with 35.1% and 35.2% decrease [34]. However, the number of grains/pods on branches can be remained unaltered in modern cultivars with small canopy or increase [66]. Based on previous studies one may anticipate that the increase of [CO2] and warmer conditions may not contribute to the increasing yield due to reduction in the number of pods and grains on branches, if the current spacing and plant density remain unchanged. High yields were found with increased spacing under elevated CO2 concentration [76]. In the evaluations of branch ontogeny or length of branches, the greatest branching plasticity of the US cultivars compared with Japanese cultivars should also be considered, together the inverse relation between the total length of branches and the density of plants [77].

The number of the racemes per plant and the number of pods or grains per racemes also respond to higher CO2 depending on the cultivar. An increase in the number of the racemes/plant by 27% and 35% in grains/raceme in most sensitive of two cultivars, named Conquista [34]. In insensible modern cultivar (most ambient stability genotype) were not different in these characteristics. Additionally, there is a positive correlation between plant height and the number of racemes in sensible cultivar (Conquista) (r = 0.67; P ≤ 0.005) [34].

A higher number of racemes lead to more pods and grains, which implies that a higher number of racemes in the main stem could partially compensate for the loss of pods and grains by the absence of lateral branches. The number of seeds per pod in soybean is very stable characteristic and can vary between 2.1 and 2.5 [54, 57, 58, 78] thus, the increase of the genetic plasticity of this characteristic can be a way for the increase of the productivity per unit of plant and area. Actually, this characteristic, perhaps, is the most limiting to increase the production in present and future environment.

The reduction in the number of branches observed in sensible cultivars under high competition among plants promoted by the higher CO2 concentration can

*Soybean - Biomass, Yield and Productivity*

same pod (source/sink ratio) [46].

pods [34, 48, 49].

high intraspecific competition during flowering and fixation of pods. An excessive competition for light can alter yield components such as number of branches and

Adequate availability of light, temperature, water and nutrients during the period of performance determination, between the start of the pod formation (R3) and full green grain (R6) guarantees a high number of grains per plant [48, 50, 51, 52, 53]. It should be remembered that the plasticity in the number of grains per pod in soybeans is very low between 2.1–2.5 seed/pod [54, 55, 56], same with different cultural practices [57, 58, 59]. Thus, the number of grains per pod of soybeans can

The weight of grains, as the second component of the most sensitive yield, depends on the genotype and the environmental conditions that determine the photosynthesis capacity of the canopy, the translocation of assimilates, the duration of the filling stage and the competition between pods, and among grains on the

The filling of the grain is strongly influenced by the availability and translocation of photoassimilates during the end of soybean development, before start of grain maturation (R7) [41]. Stresses by water deficit, thermal regime (below 25°C and above 35°C) can reduce the Leaf Area Index (LAI), thus like occurrence of rust and chronic exposures to O3 can reduce the availability and use of photoassimilates by causing early senescence of the foliar area, and decreasing the photosynthesis and assimilated production [60, 61]. Thus, the benefits of the increase in CO2 in the high photosynthesis and the more leaf area per plant can be decreased by foliar damage. Consequently, stresses during the start pod formation and the grain green full (stages R3-R6) affect the determination of the number of grains. Plant stresses between grain green full and start of grain maturation (stages R6–R7), decrease the weight of the grains on pods. On the other hand, a greater photosynthetic response in C3 plants such as soybeans to CO2 increase, or high rates of photosynthesis among soybean cultivars, may not necessarily mean significant increases in production due to environmental interactions in the field, the possible effects of photosynthetic acclimatization, the increase of photorespiration by the increase in

temperatures [62], and mainly by harvest index variability of soybean [63].

**2.3 Changes in plant height, branches and racemes**

Climate changes, in particular, the increase in temperature and the concentrations of CO2 and O3 affect the development patterns and characteristics of the canopy as leaf area index (LAI) and internal structure of canopy [63, 64]. The magnitude of the alterations will be proportional to the environmental sensitivity of the cultivars and the applied productive management. Cultivars less sensitive to the indicated factors, the re-adaptation of population densities and arrangements in plant spacing may be the most immediate strategy such as resilience to climate

Discussion on plant architecture is fundamental due to its link with the distribution of carbon allocation. Moreover, the understanding of plant shape allows for identification of plant features which are more strongly affected by environmental conditions such as CO2 and weather parameters. Plants grown with higher CO2 are taller than the plants in present conditions in the most several cultivars of soybean due to more nodes [34, 65, 66]. However, it is also possible to find no stimuli for the increase in the final height of the plant, which may be more likely in cultivars of certain growth habit [34]. Early results of [67] showed increase in height of the plant directly related with increase of more internodes and length of branches, or

be less sensitive to stress compared to the number of pods.

**28**

both.

change.

inhibit the axillary buds ontogeny in early vegetative stages [34, 55]. There is a need for further studies to elucidate the mechanisms of inhibition of branch ontogeny, and how early foliar self-shading can influence the ontogeny of branches and the number of its internodes.

According to the meta-analysis performed by [37], the increase of CO2 in the growing environment results in a 35% increase in total dry matter/plant and the total leaf area/plant between 18 and 25% in soybean. This increase may result in larger dimensions of the canopy and the early occurrence of shading in the lower region of the canopy negatively affecting not only the ontogeny of the branches, but also the number of flowers and pods.

## **2.4 Changes in pods, grains and the grain weight**

The pod sets, is the most variable yield component after the branch number. The integrated changes to plant level, such as total pods and grains per plant have been shown to cause the differences among plants under CO2 enrichment.

The pod number per plant increases around 14% [37]. Previously, continuous and significant increases in the number of pods were found by [39] with increasing day/night thermal regime (18/12, 22/16 and 26/20°C) in interaction with each [CO2] ranging from 350 (control), 650 and 1000 ppm of CO2, respectively, in the cultivar Ransom cultivated under non-limiting conditions of water, nutrients and light inside a phytotron. Is evident the increase of the number of pod in all the racemes orders when the [CO2] is near of 700 ppm [34, 67], however, the intensity of response is cultivar-dependent [34]. An evaluation about the relative partition of pods and grains per plant showed a greater relative partition of pods and grains in the first (basal) branches and in the first nodes of the branches and smaller relative partition in the subsequent branches and nodes [34].

In this way the gains in the first branches and nodes are lost logically by the reduction of pods and grains in the subsequent positions. Thus, a compensatory effect is established that cancels the initial gain, which may explain the small increase in production (7%) [34]. These authors, concluded that the ontogenic changes with respect to the formation of a smaller number of branches may be the cause of the low production gains under the effect of high [CO2] due to the early self-shading.

Continuous shade between 60 and 90%, from initial bloom reduced pods per plant between 34 and 78%, respectively [79]. Several previous studies have found a reduction in the number of pods as the main factor of self-shading in soybean [80–82]. Additionally, [83] showed a greater sensitivity to shading of the number of pods per plant compared with the number of main stem nodes and the number of branches in two soybean cultivars grown with 50% of shading during soybean flowering. These authors [83] also verified increases in flower and pod abortion when the shading occurred together with lower temperatures, like 18°C day/10°C night.

The broader analysis of the grain weight in yield of the soybean points this characteristic to the low contribution to gain a significant increase in soybean production under conditions of high CO2 concentration [37], despite having shown that the increase of the weight of the grains is possible in several cultivars [34, 65, 67].

Increases in the weight of grains have also been reported in soybean plants grown in an environment with elevated CO2, independent of the changes in thermal regime even below the optimal growth temperature [38, 84]. There was strong fall in the seed weight in thermal regimens above the optimal temperature 32/22°C day/ night, and increase by up to 13.5% in the grain weight in modern and landrace types when the temperatures during grown season closed to optimal temperature of

**31**

future climates.

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

[CO2] can also change source-sink relations, and grain filling [76, 87].

soybean production [34, 46, 52, 85]. The increasing in weight of each grain is possible due to the existence of large genetic variability soybean species [86]. Besides the thermal regime influence, the long-term exposures of soybean plants to elevated

The ratios of seed mass per plant, measured as seed mass obtained in elevated CO2 compared the seed mass per plant in ambient (current CO2 concentration), found by [34], was 1.13 for two contrast cultivars in canopy structure and size, modern (small canopy) and ancient (big canopy), and these ratios was coherent with the range from 0.93 to 1.87 previously reported by [84]. It has also been verified that higher [CO2] and favorable temperature regime increase the grain weight through enhancements of sink-force of grains [34, 88]. However, the question remains whether this increase in sink-force is the same in all grains regardless of the position they occupy in the soybean plant. The variation in the number of pods and grains within their position in the branches and racemes helps explain how and where in the plant the changes occurred in relation to treatments. The number of grains per pod although it has lower variability has high heritability and greater

The increase of [CO2] in the soybean growing environment should lead to increases of among 7% [34] to 40% [37, 90, 91, 92, 93], and this maximum will depend on how the yield components are affected during growing season, which will depend on the cultivar, the density used and the interaction with temperatures close to the optimal temperature range for a particular cultivar. Temperatures that exceed the range of the optimal temperatures, cause negative alterations of the production of biomass and affect the partition for the formation of grains on the branches and clusters, reducing the yield. The elevated [CO2] (around of 750 ppm) will attenuate the negative effects of the highest air temperatures because the carboxylase activity of Rubisco (photosynthetic enzyme of C3 plants) is favored by the higher internal concentration of CO2 in the sub-stomatal chamber, resulting in photosynthetic rates higher than those obtained in the current CO2 concentration. The yield components most sensitive to the increase in atmospheric [CO2] are the number of lateral branches, number of racemes in the main stem [34, 77, 79]. The number of pods formed will depend on the number on productive nodes formed on branches and in the main stem. Thus, plants adapted to future conditions should be able to maintain a high number of productive nodes per plant. The mechanisms of inhibition of the ontogeny of branches, mainly of the basal ones, still have to be explored, to define strategies of improvement, or management of densities between plants. The number and weight of the grains appear to be the most stable, which means that the increments of the production of soy may depend

totally on the number of pods formed by the lateral branches.

Alteration in specific yield components and source-sink relationship is common in elevated CO2, mainly in warmer climate at the level of branches, pods and grains. A better understanding of the response of soybean cultivars production, or for genotype screening, requires an evaluation of yield components, mainly in the branch level. Such is necessary to improve our understanding of sensible yield components in soybean genotypes and their ability to tolerate the impacts of the

Avoid intra-specific competition in future scenario by CO2-increases, implies the need to avoid negative effects of intra-specific competition, such as self-shading [77, 79, 83], or the development of modern cultivars with narrow canopy and short branches. Thus, the current trend of the breeding soybean programs to decreasing

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

positive effect on production [89].

**2.5 Conclusions**

### *Yield Components and Biomass Partition in Soybean: Climate Change Vision DOI: http://dx.doi.org/10.5772/intechopen.81627*

soybean production [34, 46, 52, 85]. The increasing in weight of each grain is possible due to the existence of large genetic variability soybean species [86]. Besides the thermal regime influence, the long-term exposures of soybean plants to elevated [CO2] can also change source-sink relations, and grain filling [76, 87].

The ratios of seed mass per plant, measured as seed mass obtained in elevated CO2 compared the seed mass per plant in ambient (current CO2 concentration), found by [34], was 1.13 for two contrast cultivars in canopy structure and size, modern (small canopy) and ancient (big canopy), and these ratios was coherent with the range from 0.93 to 1.87 previously reported by [84]. It has also been verified that higher [CO2] and favorable temperature regime increase the grain weight through enhancements of sink-force of grains [34, 88]. However, the question remains whether this increase in sink-force is the same in all grains regardless of the position they occupy in the soybean plant. The variation in the number of pods and grains within their position in the branches and racemes helps explain how and where in the plant the changes occurred in relation to treatments. The number of grains per pod although it has lower variability has high heritability and greater positive effect on production [89].

### **2.5 Conclusions**

*Soybean - Biomass, Yield and Productivity*

also the number of flowers and pods.

**2.4 Changes in pods, grains and the grain weight**

partition in the subsequent branches and nodes [34].

number of its internodes.

inhibit the axillary buds ontogeny in early vegetative stages [34, 55]. There is a need for further studies to elucidate the mechanisms of inhibition of branch ontogeny, and how early foliar self-shading can influence the ontogeny of branches and the

According to the meta-analysis performed by [37], the increase of CO2 in the growing environment results in a 35% increase in total dry matter/plant and the total leaf area/plant between 18 and 25% in soybean. This increase may result in larger dimensions of the canopy and the early occurrence of shading in the lower region of the canopy negatively affecting not only the ontogeny of the branches, but

The pod sets, is the most variable yield component after the branch number. The integrated changes to plant level, such as total pods and grains per plant have been

The pod number per plant increases around 14% [37]. Previously, continuous and significant increases in the number of pods were found by [39] with increasing day/night thermal regime (18/12, 22/16 and 26/20°C) in interaction with each [CO2] ranging from 350 (control), 650 and 1000 ppm of CO2, respectively, in the cultivar Ransom cultivated under non-limiting conditions of water, nutrients and light inside a phytotron. Is evident the increase of the number of pod in all the racemes orders when the [CO2] is near of 700 ppm [34, 67], however, the intensity of response is cultivar-dependent [34]. An evaluation about the relative partition of pods and grains per plant showed a greater relative partition of pods and grains in the first (basal) branches and in the first nodes of the branches and smaller relative

In this way the gains in the first branches and nodes are lost logically by the reduction of pods and grains in the subsequent positions. Thus, a compensatory effect is established that cancels the initial gain, which may explain the small increase in production (7%) [34]. These authors, concluded that the ontogenic changes with respect to the formation of a smaller number of branches may be the cause of the low production gains under the effect of high [CO2] due to the early

Continuous shade between 60 and 90%, from initial bloom reduced pods per plant between 34 and 78%, respectively [79]. Several previous studies have found a reduction in the number of pods as the main factor of self-shading in soybean [80–82]. Additionally, [83] showed a greater sensitivity to shading of the number of pods per plant compared with the number of main stem nodes and the number of branches in two soybean cultivars grown with 50% of shading during soybean flowering. These authors [83] also verified increases in flower and pod abortion when the shading occurred together with lower temperatures, like 18°C day/10°C

The broader analysis of the grain weight in yield of the soybean points this characteristic to the low contribution to gain a significant increase in soybean production under conditions of high CO2 concentration [37], despite having shown that the increase of the weight of the grains is possible in several cultivars [34, 65, 67]. Increases in the weight of grains have also been reported in soybean plants grown in an environment with elevated CO2, independent of the changes in thermal regime even below the optimal growth temperature [38, 84]. There was strong fall in the seed weight in thermal regimens above the optimal temperature 32/22°C day/ night, and increase by up to 13.5% in the grain weight in modern and landrace types when the temperatures during grown season closed to optimal temperature of

shown to cause the differences among plants under CO2 enrichment.

**30**

self-shading.

night.

The increase of [CO2] in the soybean growing environment should lead to increases of among 7% [34] to 40% [37, 90, 91, 92, 93], and this maximum will depend on how the yield components are affected during growing season, which will depend on the cultivar, the density used and the interaction with temperatures close to the optimal temperature range for a particular cultivar. Temperatures that exceed the range of the optimal temperatures, cause negative alterations of the production of biomass and affect the partition for the formation of grains on the branches and clusters, reducing the yield. The elevated [CO2] (around of 750 ppm) will attenuate the negative effects of the highest air temperatures because the carboxylase activity of Rubisco (photosynthetic enzyme of C3 plants) is favored by the higher internal concentration of CO2 in the sub-stomatal chamber, resulting in photosynthetic rates higher than those obtained in the current CO2 concentration.

The yield components most sensitive to the increase in atmospheric [CO2] are the number of lateral branches, number of racemes in the main stem [34, 77, 79]. The number of pods formed will depend on the number on productive nodes formed on branches and in the main stem. Thus, plants adapted to future conditions should be able to maintain a high number of productive nodes per plant. The mechanisms of inhibition of the ontogeny of branches, mainly of the basal ones, still have to be explored, to define strategies of improvement, or management of densities between plants. The number and weight of the grains appear to be the most stable, which means that the increments of the production of soy may depend totally on the number of pods formed by the lateral branches.

Alteration in specific yield components and source-sink relationship is common in elevated CO2, mainly in warmer climate at the level of branches, pods and grains. A better understanding of the response of soybean cultivars production, or for genotype screening, requires an evaluation of yield components, mainly in the branch level. Such is necessary to improve our understanding of sensible yield components in soybean genotypes and their ability to tolerate the impacts of the future climates.

Avoid intra-specific competition in future scenario by CO2-increases, implies the need to avoid negative effects of intra-specific competition, such as self-shading [77, 79, 83], or the development of modern cultivars with narrow canopy and short branches. Thus, the current trend of the breeding soybean programs to decreasing

the size of canopy [94, 95] as strategy to improve the productivity may continue to be the best strategy, even more so if plants were considered larger number of short branches to reduce the competition effect between the proximal and distant pods of the main stem as evidenced by [34].

## **Acknowledgements**

The authors thank the National Postdoctoral Program CAPES-PROAP/BRAZIL, CiXPAG—Interaction of Climate Extremes, Air Pollution and Agro-ecosystems, coordinated by CICERO Climate Centre, UiO/MET Norway, Oslo, Norway, and by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais—FAPEMIG (PCE-00891-17).

## **Conflict of interest**

The authors declared that this chapter has no conflict of interest.

## **Author details**

Milton E. Pereira-Flores and Flávio B. Justino\* Agricultural and Environmental Engineering Department DEA/UFV, Viçosa Federal University, Viçosa, MG, Brazil

\*Address all correspondence to: fjustino@ufv.br

© 2019 The Author(s). Licensee IntechOpen. This chapter is 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.

**33**

n4p1871

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

[7] Avila AMH, Farias JRB, Pinto HS, Pilau FG. Climatic Restrictions for Maximizing Soybean Yields. In: Board JE, editor. A Comprehensive Survey of International Soybean Research - Genetics, Physiology, Agronomy and Nitrogen Relationships. Rijeka: Intech

[8] Sinclair TR, Neumaier N, Farias JRB, Nepomuceno AL. Comparison of vegetative development in soybean cultivars for low-latitude environments. Field Crops Research.

temperatura do ar no desenvolvimento de três cultivares de soja. Revista Brasileira de Agrometeorologia.

[10] Empresa Brasileira De Pesquisa Agropecuária, Centro Nacional de Pesquisa da Soja. Tecnologias de

2012/2013. Londrina; 2011. 76 p

produção de soja: região central do Brasil

[11] Setiyono TD, Cassman KG, Specht JE, Dobermann A, Weiss A, Yang H, et al. Simulation of soybean growth and yield in near-optimal growth conditions. Field Crops Research.

[12] Ziska LH, Bunce JA. Growth and photosynthetic response of three soybean cultivars to simultaneous increases in growth temperature and CO2. Physiologia Plantarum.

[13] Kumagai E, Tacarindua CP, Homma K, Shiraiwa T, Sameshima R. Effects of elevated CO2 concentration and temperature on seed production and nitrogen concentration in soybean (*Glycine max* (L.) Merr.). Journal of Agricultural Meteorology.

press; 2013. pp. 367-375

2005;**92**:53-59

[9] Schoffel ER, Volpe CA. Contribuição relativa da

2002;**10**(2):97-104

2010;**119**:161-174

1995;**94**:575-584

2012;**68**(1):1-13

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

[1] Houghton JT, Ding Y, Griggs DJ, Noguer N, Linden PJVD, Dai X. Climate Change 2001: The Scientific Basis. Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge

**References**

University Press; 2001. 83 p

[2] IPCC Intergovernmental Panel on Climate Change. Climate Change. The Physical Science Basis. Working Group I. Fifth Assessment Report. Summary for Policymakers. WMO; 2013. 27 pp

[3] Constable GA, Rose A. Variability of soybean phenology response to temperature, daylength and rate of change in daylength. Field Crops Research. 1988;**18**(1):57-69. DOI: 10.1016/0378-4290(88)90059-7

[4] Câmara GMS, Sediyama T, Dourado-Neto D, Bernardes

sa/v54nspe/17.pdf

S2095-3119(14)60856-X

[5] Wu T, Li J, Wu C, Sun S, Mao T, Jiang B, et al. Analysis of the independent- and interactive-photothermal effects on soybean flowering. Journal of Integrative Agriculture. 2015;**14**(4):622-632. DOI: 10.1016/

[6] Rockenbach AP, Otomar Caron B, Queiróz de Souza V, Elli EF, Machado de Oliveira D, Monteiro GC. Estimated length of soybean phenological stages. Semina: Ciências Agrárias. 2016;**37**:1871.

DOI: 10.5433/1679-0359.2016v37

MS. Influence of photoperiod and air temperature on the growth, flowering and maturation of soybean (*Glycine max* (L.) Merrill). In: Presented at 4th Congress of the European Society for Agronomy, 7-11 July, 1996. Veldhoven-Wageningen. The Netherlands: Publish in Sci.agric; Piracicaba54(Numero Especial); 1997. pp. 149-154. http://www.scielo.br/pdf/ *Yield Components and Biomass Partition in Soybean: Climate Change Vision DOI: http://dx.doi.org/10.5772/intechopen.81627*

## **References**

*Soybean - Biomass, Yield and Productivity*

the main stem as evidenced by [34].

**Acknowledgements**

(PCE-00891-17).

**Conflict of interest**

the size of canopy [94, 95] as strategy to improve the productivity may continue to be the best strategy, even more so if plants were considered larger number of short branches to reduce the competition effect between the proximal and distant pods of

The authors thank the National Postdoctoral Program CAPES-PROAP/BRAZIL, CiXPAG—Interaction of Climate Extremes, Air Pollution and Agro-ecosystems, coordinated by CICERO Climate Centre, UiO/MET Norway, Oslo, Norway, and by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais—FAPEMIG

The authors declared that this chapter has no conflict of interest.

**32**

**Author details**

provided the original work is properly cited.

Milton E. Pereira-Flores and Flávio B. Justino\*

\*Address all correspondence to: fjustino@ufv.br

Federal University, Viçosa, MG, Brazil

© 2019 The Author(s). Licensee IntechOpen. This chapter is 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,

Agricultural and Environmental Engineering Department DEA/UFV, Viçosa

[1] Houghton JT, Ding Y, Griggs DJ, Noguer N, Linden PJVD, Dai X. Climate Change 2001: The Scientific Basis. Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press; 2001. 83 p

[2] IPCC Intergovernmental Panel on Climate Change. Climate Change. The Physical Science Basis. Working Group I. Fifth Assessment Report. Summary for Policymakers. WMO; 2013. 27 pp

[3] Constable GA, Rose A. Variability of soybean phenology response to temperature, daylength and rate of change in daylength. Field Crops Research. 1988;**18**(1):57-69. DOI: 10.1016/0378-4290(88)90059-7

[4] Câmara GMS, Sediyama T, Dourado-Neto D, Bernardes MS. Influence of photoperiod and air temperature on the growth, flowering and maturation of soybean (*Glycine max* (L.) Merrill). In: Presented at 4th Congress of the European Society for Agronomy, 7-11 July, 1996. Veldhoven-Wageningen. The Netherlands: Publish in Sci.agric; Piracicaba54(Numero Especial); 1997. pp. 149-154. http://www.scielo.br/pdf/ sa/v54nspe/17.pdf

[5] Wu T, Li J, Wu C, Sun S, Mao T, Jiang B, et al. Analysis of the independent- and interactive-photothermal effects on soybean flowering. Journal of Integrative Agriculture. 2015;**14**(4):622-632. DOI: 10.1016/ S2095-3119(14)60856-X

[6] Rockenbach AP, Otomar Caron B, Queiróz de Souza V, Elli EF, Machado de Oliveira D, Monteiro GC. Estimated length of soybean phenological stages. Semina: Ciências Agrárias. 2016;**37**:1871. DOI: 10.5433/1679-0359.2016v37 n4p1871

[7] Avila AMH, Farias JRB, Pinto HS, Pilau FG. Climatic Restrictions for Maximizing Soybean Yields. In: Board JE, editor. A Comprehensive Survey of International Soybean Research - Genetics, Physiology, Agronomy and Nitrogen Relationships. Rijeka: Intech press; 2013. pp. 367-375

[8] Sinclair TR, Neumaier N, Farias JRB, Nepomuceno AL. Comparison of vegetative development in soybean cultivars for low-latitude environments. Field Crops Research. 2005;**92**:53-59

[9] Schoffel ER, Volpe CA. Contribuição relativa da temperatura do ar no desenvolvimento de três cultivares de soja. Revista Brasileira de Agrometeorologia. 2002;**10**(2):97-104

[10] Empresa Brasileira De Pesquisa Agropecuária, Centro Nacional de Pesquisa da Soja. Tecnologias de produção de soja: região central do Brasil 2012/2013. Londrina; 2011. 76 p

[11] Setiyono TD, Cassman KG, Specht JE, Dobermann A, Weiss A, Yang H, et al. Simulation of soybean growth and yield in near-optimal growth conditions. Field Crops Research. 2010;**119**:161-174

[12] Ziska LH, Bunce JA. Growth and photosynthetic response of three soybean cultivars to simultaneous increases in growth temperature and CO2. Physiologia Plantarum. 1995;**94**:575-584

[13] Kumagai E, Tacarindua CP, Homma K, Shiraiwa T, Sameshima R. Effects of elevated CO2 concentration and temperature on seed production and nitrogen concentration in soybean (*Glycine max* (L.) Merr.). Journal of Agricultural Meteorology. 2012;**68**(1):1-13

[14] Jones JW, Boote KJ, Jagtap SS, Mishoe JW. Soybean development. In: Hanks J, Ritchie JT, editors. Modeling Soil and Plant Systems. Madison, WI: American Society of Agronomy; 1991. pp. 71-90

[15] Avila AMH, Farias JRB, Pinto HS, Pilau FG. Climatic restrictions for maximizing soybean yields. In: Board JE, editor. A Comprehensive Survey of International Soybean Research - Genetics, Physiology, Agronomy and Nitrogen Relationships. Rijeka: Intech Press; 2013. pp. 367-375

[16] Hesketh JD, Myhre DL, Willey CR. Temperature control of time intervals between vegetative and reproductive events in soybeans. Crop Science. 1973;**15**:250-254

[17] Boote KJ, Jones JW, Hoogenboom G. Simulation of crop growth: CROPGRO model. In: Peart RM, Curry RB, editors. Agricultural Systems Modeling and Simulation. New York: M. Dekker; 1998. pp. 651-691

[18] Pandey JP, Torrie JH. Path coefficient analysis of seed yield components in soybeans (*Glycine max* (L.) Merr.). Crop Science. 1973;**13**(5):505-507

[19] Swank JC, Egli DB, Pfeiffer TW. Seed growth characteristics of soybean genotypes differing in duration of seed fill. Crop Science. 1987;**27**(1):85-89

[20] Thuzar M, Puteh AB, Abdullah NAP, Mohd. Lassim MB, Jusoff K. The effects of temperature stress on the quality and yield of soya bean [(*Glycine max* L.) Merrill.]. The Journal of Agricultural Science. 2010;**2**(1):172-179

[21] Onat B, Bakal H, Gulluoglu L, Arioglu H. The effects of high temperature at the growing period on yield and yield components of soybean [*Glycine max* (L.) Merr] varieties.

Turkish Journal of Field Crops. 2017;**22**(2):178-186. DOI: 10.17557/ tjfc.356210

[22] Kantolic AG, Slafer GA. Photoperiod sensitivity after flowering and seed number determination in indeterminate soybean cultivars. Field Crops Research. 2001;**72**:109-118

[23] Kantolic AG, Slafer GA. Development and seed number in indeterminate soybean as affected by timing and duration of exposure to long photoperiods after flowering. Annual Botany. 2007;**99**:925-933

[24] Major DJ, Johnson DR, Tanner JW, Anderson IC. Effects of daylength and temperature on soybean development. Crop Science. 1975;**15**(2):174-179. DOI: 10.2135/cropsci1975.0011183X0015000 20009x

[25] Huxley PA, Summerfield RJ, Hughes AP. The effect of photoperiod on development of soybean and cowpea cultivars grow in the U.K. in summer. Experimental Agriculture. 1974;**10**:225-239

[26] Destro D, Carpentieri-Pípolo V, Kiihl RAS, Almeida LA. Photoperiodism and genetic control of the long juvenile period in soybean: A review. Crop Breeding and Applied Biotechnology. 2001;**1**(1):72-92

[27] Watanabe S, Harada K, Abe J. Genetic and molecular bases of photoperiod responses of flowering in soybean. Breeding Science. 2012;**61**:531-543

[28] Acock MC, Acock B. Photoperiod sensitivity during soybean flower development. Biotronics. 1995;**24**:25-34

[29] Justino F, Oliveira EC, Rodrigues RA, Gonçalves PHL, Souza PJOP, Stordal F, et al. Mean and interannual variability of maize and soybean in brazil under global warming conditions.

**35**

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

enrichment during different growth periods on flowering, pod set and seed yield in soybean. Plant Production Science. 2004;**7**(1):11-15. DOI: 10.1626/

[37] Ainsworth EA, Davey PA, Bernacchi CJ, Dermody OC, Heaton EA, Moore DJ, et al. A meta-analysis of elevated [CO2] effects on soybean (*Glycine max*) physiology, growth and yield. Global Change Biology. 2002;**8**:695-709

[38] Heinemann AB, Maia AD, Dourado-Neto D, Ingram KT, Hoogenboom C. Soybean (*Glycine max* (L.) Merr.) growth and development response to CO2 enrichment under different temperature regimes. European Journal

of Agronomy. 2006;**24**:52-61

[39] Sionit N, Strain BR, Flint

pce.12443. Epub 2014 Oct 27

[41] Hall AJ. Los componentes fisiológicos del rendimiento de los cultivos. Revista de la Facultad de Agronomía. 1980;**1**(1):73-86

12 p

[42] Fehr WR, Caviness CE. Stages of soybean development. Ames: Iowa State University, (Special Report, 80); 1977.

[43] Ramesh P, Gopalaswamy N. Heat unit requirement and prediction of developmental stages in soybean. Journal of Agronomy and Crop Science. 1991;**167**:236-240. DOI: 10.1111/j.1439-

037X.1991.tb00869.x

10.4141/cjps87-007

EP. Interaction of temperature and CO2 enrichment on soybean: growth and dry matter partitioning. Canadian Journal of Plant Science. 1987;**67**(1):59-67. DOI:

[40] Bishop KA, Betzelberger AM, Long SP, Ainsworth EA. Is there potential to adapt soybean (*Glycine max* Merr.) to future [CO2]? An analysis of the yield response of 18 genotypes in free-air CO2 enrichment. Plant, Cell & Environment. 2015;**38**(9):1765-1774. DOI: 10.1111/

pps.7.11

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

American Journal of Climate Change.

[30] Embrapa Soja. Empressa Brasileira de Pesquisa Agropecuaria. Tecnologias de produção de soja região central do Brasil 2009 e 2010: relatório do ano de 2008. Londrina: Embrapa Soja; 2008. 262 p. (Embrapa Soja. Sistemas de

[31] Constable GA, Rose A. Variability of soybean phenology response to temperature, daylength and rate of change in daylength. Field Crops Research. February 1988;**18**(1):57-69. DOI: 10.1016/0378-4290(88)90059-7

[32] Penalba OC, Bettolli ML, Vargas WM. The impact of climate variability on soybean yields in Argentina.

Multivariate regression. Meteorological Applications. 2007;**14**:3-14. DOI:

[33] Morgan PB. Soybean's future: Photosynthesis sucrose transport, dry mass accumulation and yield in a changing atmosphere. PhD thesis. Urbana-Champaign, IL, USA:

[34] Pereira-Flores ME, Justino F, Ruiz-Vera UM, Stordal F, Melo AAM, Rodrigues RA. Response of soybean yield components and allocation of dry matter to increased temperature and CO2 concentration. AJCS. 2016;**10**(6):808-818. DOI: 10.21475/

[35] Ruiz-Vera UM, Siebers M, Gray SB, Drag DW, Rosenthal DM, Kimball BA, et al. Global warming can negate the expected CO2 stimulation in photosynthesis and productivity for soybean grown in the Midwestern United States. Plant Physiology.

[36] Nakamoto H, Zheng SH, Tanaka K, Yamazaki A, Furuya T, Iwaya-Inoue M, et al. Effects of carbon dioxide

University of Illinois; 2004

ajcs.2016.10.06.p7310

2013;**162**(1):410-423

2013;**2**:237-253

produção, 13)

10.1002/met.1

*Yield Components and Biomass Partition in Soybean: Climate Change Vision DOI: http://dx.doi.org/10.5772/intechopen.81627*

American Journal of Climate Change. 2013;**2**:237-253

*Soybean - Biomass, Yield and Productivity*

[14] Jones JW, Boote KJ, Jagtap SS, Mishoe JW. Soybean development. In: Hanks J, Ritchie JT, editors. Modeling Soil and Plant Systems. Madison, WI: American Society of Agronomy; 1991. Turkish Journal of Field Crops. 2017;**22**(2):178-186. DOI: 10.17557/

[22] Kantolic AG, Slafer GA. Photoperiod sensitivity after flowering and seed number determination in indeterminate soybean cultivars. Field Crops Research.

[24] Major DJ, Johnson DR, Tanner JW, Anderson IC. Effects of daylength and temperature on soybean development. Crop Science. 1975;**15**(2):174-179. DOI: 10.2135/cropsci1975.0011183X0015000

[25] Huxley PA, Summerfield RJ, Hughes AP. The effect of photoperiod on development of soybean and cowpea cultivars grow in the U.K. in summer. Experimental Agriculture.

[26] Destro D, Carpentieri-Pípolo V, Kiihl RAS, Almeida LA. Photoperiodism and genetic control of the long juvenile period in soybean: A review. Crop Breeding and Applied Biotechnology.

[27] Watanabe S, Harada K, Abe J. Genetic and molecular bases of photoperiod responses of flowering in soybean. Breeding Science.

[28] Acock MC, Acock B. Photoperiod sensitivity during soybean flower development. Biotronics. 1995;**24**:25-34

[29] Justino F, Oliveira EC, Rodrigues RA, Gonçalves PHL, Souza PJOP, Stordal F, et al. Mean and interannual variability of maize and soybean in brazil under global warming conditions.

tjfc.356210

2001;**72**:109-118

20009x

1974;**10**:225-239

2001;**1**(1):72-92

2012;**61**:531-543

[23] Kantolic AG, Slafer GA. Development and seed number in indeterminate soybean as affected by timing and duration of exposure to long photoperiods after flowering. Annual

Botany. 2007;**99**:925-933

[15] Avila AMH, Farias JRB, Pinto HS, Pilau FG. Climatic restrictions for maximizing soybean yields. In: Board JE, editor. A Comprehensive Survey of International Soybean Research - Genetics, Physiology, Agronomy and Nitrogen Relationships. Rijeka: Intech

[16] Hesketh JD, Myhre DL, Willey CR. Temperature control of time intervals between vegetative and reproductive events in soybeans. Crop

[17] Boote KJ, Jones JW, Hoogenboom G. Simulation of crop growth:

CROPGRO model. In: Peart RM, Curry RB, editors. Agricultural Systems Modeling and Simulation. New York:

Press; 2013. pp. 367-375

Science. 1973;**15**:250-254

M. Dekker; 1998. pp. 651-691

[18] Pandey JP, Torrie JH. Path coefficient analysis of seed yield components in soybeans (*Glycine max* (L.) Merr.). Crop Science.

[19] Swank JC, Egli DB, Pfeiffer TW. Seed growth characteristics of soybean genotypes differing in duration of seed fill. Crop Science.

[20] Thuzar M, Puteh AB, Abdullah NAP, Mohd. Lassim MB, Jusoff K. The effects of temperature stress on the quality and yield of soya bean [(*Glycine max* L.) Merrill.]. The Journal of Agricultural Science. 2010;**2**(1):172-179

[21] Onat B, Bakal H, Gulluoglu L, Arioglu H. The effects of high temperature at the growing period on yield and yield components of soybean [*Glycine max* (L.) Merr] varieties.

1973;**13**(5):505-507

1987;**27**(1):85-89

pp. 71-90

**34**

[30] Embrapa Soja. Empressa Brasileira de Pesquisa Agropecuaria. Tecnologias de produção de soja região central do Brasil 2009 e 2010: relatório do ano de 2008. Londrina: Embrapa Soja; 2008. 262 p. (Embrapa Soja. Sistemas de produção, 13)

[31] Constable GA, Rose A. Variability of soybean phenology response to temperature, daylength and rate of change in daylength. Field Crops Research. February 1988;**18**(1):57-69. DOI: 10.1016/0378-4290(88)90059-7

[32] Penalba OC, Bettolli ML, Vargas WM. The impact of climate variability on soybean yields in Argentina. Multivariate regression. Meteorological Applications. 2007;**14**:3-14. DOI: 10.1002/met.1

[33] Morgan PB. Soybean's future: Photosynthesis sucrose transport, dry mass accumulation and yield in a changing atmosphere. PhD thesis. Urbana-Champaign, IL, USA: University of Illinois; 2004

[34] Pereira-Flores ME, Justino F, Ruiz-Vera UM, Stordal F, Melo AAM, Rodrigues RA. Response of soybean yield components and allocation of dry matter to increased temperature and CO2 concentration. AJCS. 2016;**10**(6):808-818. DOI: 10.21475/ ajcs.2016.10.06.p7310

[35] Ruiz-Vera UM, Siebers M, Gray SB, Drag DW, Rosenthal DM, Kimball BA, et al. Global warming can negate the expected CO2 stimulation in photosynthesis and productivity for soybean grown in the Midwestern United States. Plant Physiology. 2013;**162**(1):410-423

[36] Nakamoto H, Zheng SH, Tanaka K, Yamazaki A, Furuya T, Iwaya-Inoue M, et al. Effects of carbon dioxide

enrichment during different growth periods on flowering, pod set and seed yield in soybean. Plant Production Science. 2004;**7**(1):11-15. DOI: 10.1626/ pps.7.11

[37] Ainsworth EA, Davey PA, Bernacchi CJ, Dermody OC, Heaton EA, Moore DJ, et al. A meta-analysis of elevated [CO2] effects on soybean (*Glycine max*) physiology, growth and yield. Global Change Biology. 2002;**8**:695-709

[38] Heinemann AB, Maia AD, Dourado-Neto D, Ingram KT, Hoogenboom C. Soybean (*Glycine max* (L.) Merr.) growth and development response to CO2 enrichment under different temperature regimes. European Journal of Agronomy. 2006;**24**:52-61

[39] Sionit N, Strain BR, Flint EP. Interaction of temperature and CO2 enrichment on soybean: growth and dry matter partitioning. Canadian Journal of Plant Science. 1987;**67**(1):59-67. DOI: 10.4141/cjps87-007

[40] Bishop KA, Betzelberger AM, Long SP, Ainsworth EA. Is there potential to adapt soybean (*Glycine max* Merr.) to future [CO2]? An analysis of the yield response of 18 genotypes in free-air CO2 enrichment. Plant, Cell & Environment. 2015;**38**(9):1765-1774. DOI: 10.1111/ pce.12443. Epub 2014 Oct 27

[41] Hall AJ. Los componentes fisiológicos del rendimiento de los cultivos. Revista de la Facultad de Agronomía. 1980;**1**(1):73-86

[42] Fehr WR, Caviness CE. Stages of soybean development. Ames: Iowa State University, (Special Report, 80); 1977. 12 p

[43] Ramesh P, Gopalaswamy N. Heat unit requirement and prediction of developmental stages in soybean. Journal of Agronomy and Crop Science. 1991;**167**:236-240. DOI: 10.1111/j.1439- 037X.1991.tb00869.x

[44] Aykuz FA, Kandel H, Morlock D. Developing a growing degree day model for North Dakota and Northern Minnesota soybean. Agricultural and Forest Meteorology. 2017;**239**:134-140

[45] Pedersen P. Soybean Growth and Development. Department of Agronomy. Iowa, USA: Iowa State University Extension and Outreach; 2007. 28 p

[46] Liu B, Liu XB, Wang C, Li YS, Jin J, Herbert SJ. Soybean yield and yield component distribution across the main axis in response to light enrichment and shading under different densities. Plant, Soil and Environment. 2010;**56**(8):384-392

[47] Kato S, Fujii K, Yumoto S, Ishimoto M, Shiraiwa T, Sayama T, et al. Seed yield and its components of indeterminate and determinate lines in recombinant inbred lines of soybean. Breeding Science. 2015;**65**(2):154-160. DOI: 10.1270/jsbbs.65.154

[48] Mathew JP, Herbert SJ, Zhang S, Rautenkranz AAF, Litchfield GV. Differential response of soybean yield components to the timing of light enrichment. Agronomy Journal. 2000;**92**:1156-1161

[49] Kokubun M. Physiological Mechanisms Regulating Flower Abortion in Soybean. In: Ng T-B, editor. ISBN: 978-953-307-219-7. Soybean - Biochemistry, Chemistry and Physiology. Rijeka: InTech; 2011, Available from: http://www.intechopen. com/books/soybean-biochemistrychemistry-and-physiology/ physiologicalmechanisms-regulatingflower-abortion-in-soybean

[50] Kumar A, Pandey V, Shekh AM, Kumar M. Growth and yield response of soybean (*Glycine max* L.) in relation to temperature, photoperiod and sunshine duration at Anand, Gujarat, India. American-Eurasian Journal of Agronomy. 2008;**1**(2):45-50

[51] Liu X, Herbert SJ, Hashemi AM, Litchfield GV, Zhang Q, Barzegar AR. Yield and yield components responses of old and new soybean cultivars to source-sink manipulation under light enrichment. Plant, Soil and Environment. 2006;**52**(4):150-158

[52] Appiah AK, Helget R, Xu Y, Jixiang W. Response of soybean yield and yield components to phosphorus fertilization in South Dakota. Conference on Applied Statistics in Agriculture; 2014. DOI: 10.4148/2475-7772.1001

[53] Rodrigues TR, Casaroli D, Evangelista AWP, Júnior JA. Water availability to soybean crop as a function of the least limiting water range and evapotranspiration. Pesquisa Agropecuária Tropical Goiânia. 2017;**47**(2):161-167. DOI: 10.1590/1983-40632016v4743746

[54] Peluzio JM, Vaz-de-Melo A, Afférri FS, Silva RR, Barros HB, Nascimento IR, et al. Variabilidade genética entre cultivares de soja, sob diferentes condições edafoclimáticas. Pesquisa Aplicada & Agrotecnologia. 2009;**2**(3):21-29

[55] Soares MM, Oliveira GL, Soriano PE, Sekita MC, Sediyama T. Performance of soybean plants as function of seed size: II. Nutritional stress. Journal of Seed Science. 2013;**35**(4):419-427. DOI: 10.1590/ S2317-15372013000400002

[56] Nico M, Mantese AI, Miralles DJ, Kantolic AG. Soybean fruit development and set at the node level under combined photoperiod and radiation conditions. Journal of Experimental Botany. 2016;**67**(1):365-377. DOI: 10.1093/jxb/erv475

[57] Pires JLF. Variabilidade espacial dos componentes de produção de plantas de soja em comunidade. Tese (Doutorado em Fitotecnia). Porto Alegre: Faculdade

**37**

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

development of soybean under Free-Air Concentration Enrichment (FACE). Journal of Experimental Botany.

[66] Jin J, Li Y, Liu X, Wang G, Tang C, Yu Z, et al. Elevated CO2 alters distribution of nodal leaf area and enhances nitrogen uptake contributing to yield increase of soybean cultivars grown in Mollisols. PLoS One. 2017;**12**(5):e0176688. DOI: 10.1371/

[67] Rogers HH, Cure JD, Thomas JF, Smith JM. Influence of elevated CO2 on growth of soybean plants. Crop Science.

[68] Bruhn D. Plant respiration and climate change effects. Ph.D. thesis Plant Research Department Botanical Institute University of Copenhagen. Risø National Laboratory, Roskilde. Dannmark April; 2002. 139 p

[69] Francis D, Barlow PW. Temperature and the cell cycle. Symposia of the Society for Experimental Biology.

[70] Tardieu F, Granier C. Quatitative analysis of cell division in leaves: methods, developmental patterns and effects of environmental conditions. Plant Molecular Biology.

[71] Tardieu F, Reymond M, Hamard P, Granier C, Muller B. Spatial distributions of expansion rate, cell division rate and cell size in maize leaves: a synthesis of the effects of soil water status,

evaporative demand and temperature. Journal of Experimental Botany.

soybean to air temperature and carbon dioxide concentration. Crop Science.

[72] Baker JT, Allen LH, Boote KJ, Jones P, Jones JW. Response of

2000;**51**(350):1505-1514

1989;**29**(1):98-105

2009;**60**(10):2945-2951

journal.pone.0176688

1984;**24**:361-366

1988;**42**:181-201

2000;**43**:555-567

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

de Agronomia, Universidade Federal do

[58] Dalchiavon FC, Passos e Carvalho M. Correlação linear e espacial dos componentes de produção e

produtividade da soja linear and spatial correlation of the yield components and soybean yield. Londrina,

Semina: Ciências Agrárias, Londrina.

[59] Fageria NK, Moreira A, Cardoso M, Moraes M. Influence of lime and gypsum on yield and yield components of soybean and changes in soil chemical properties. Communications in Soil Science and Plant Analysis. 2014;**45**. DOI: 10.1080/00103624.2013.861906

[60] Moreira EN, Vale FXR, Paul PA, Rodrigues FA, Jesus WC. Temporal index in soybean cultivars of different maturity groups. Plant Disease.

[61] Dermody O, Long SP, DeLucia EH. How does elevated CO2 or ozone affect the leaf-area index of soybean when applied independently? New Phytologist. 2006;**169**:145-155

[62] Bloom AJ. As carbon dioxide rises, food quality will decline without careful nitrogen management. California Agriculture. 2009;**63**(2):67-72

[63] Krisnawatia A, Adie MM. Variability of biomass and harvest index from several soybean genotypes as renewable

energy source. Energy Procedia.

[64] Gray SB, Dermody O, DeLucia EH. Spectral reflectance from a soybean canopy exposed to elevated CO2 and O3. Journal of Experimental Botany. 2010;**61**(15):4413-4422. DOI: 10.1093/

[65] Castro JC, Dohleman FG, Bernacchi CJ, Long SP. Elevated CO2 significantly delays reproductive

2015;**65**:14-21

jxb/erq244

2012;**33**(2):541-552

2015;**99**:1216-1226

Rio Grande do Sul; 2002. 139 p

*Yield Components and Biomass Partition in Soybean: Climate Change Vision DOI: http://dx.doi.org/10.5772/intechopen.81627*

de Agronomia, Universidade Federal do Rio Grande do Sul; 2002. 139 p

*Soybean - Biomass, Yield and Productivity*

[44] Aykuz FA, Kandel H, Morlock D. Developing a growing degree day model for North Dakota and Northern Minnesota soybean. Agricultural and Forest Meteorology. 2017;**239**:134-140

[51] Liu X, Herbert SJ, Hashemi AM, Litchfield GV, Zhang Q, Barzegar AR. Yield and yield components responses of old and new soybean cultivars to source-sink manipulation under light enrichment. Plant, Soil and Environment. 2006;**52**(4):150-158

[52] Appiah AK, Helget R, Xu Y, Jixiang W. Response of soybean yield and yield components to phosphorus fertilization in South Dakota. Conference on Applied Statistics in Agriculture; 2014. DOI: 10.4148/2475-7772.1001

[53] Rodrigues TR, Casaroli D, Evangelista AWP, Júnior JA. Water availability to soybean crop as a function of the least limiting water range and evapotranspiration. Pesquisa Agropecuária Tropical Goiânia. 2017;**47**(2):161-167. DOI: 10.1590/1983-40632016v4743746

[54] Peluzio JM, Vaz-de-Melo A, Afférri FS, Silva RR, Barros HB, Nascimento IR, et al. Variabilidade genética entre cultivares de soja, sob diferentes condições edafoclimáticas. Pesquisa Aplicada & Agrotecnologia.

[55] Soares MM, Oliveira GL, Soriano PE, Sekita MC, Sediyama T. Performance of soybean plants as function of seed size: II. Nutritional stress. Journal of Seed Science. 2013;**35**(4):419-427. DOI: 10.1590/ S2317-15372013000400002

[56] Nico M, Mantese AI, Miralles DJ, Kantolic AG. Soybean fruit development

[57] Pires JLF. Variabilidade espacial dos componentes de produção de plantas de soja em comunidade. Tese (Doutorado em Fitotecnia). Porto Alegre: Faculdade

and set at the node level under combined photoperiod and radiation conditions. Journal of Experimental Botany. 2016;**67**(1):365-377. DOI:

10.1093/jxb/erv475

2009;**2**(3):21-29

[45] Pedersen P. Soybean Growth and Development. Department of Agronomy.

Iowa, USA: Iowa State University Extension and Outreach; 2007. 28 p

[46] Liu B, Liu XB, Wang C, Li YS, Jin J, Herbert SJ. Soybean yield and yield component distribution across the main axis in response to light

2010;**56**(8):384-392

[47] Kato S, Fujii K, Yumoto S, Ishimoto M, Shiraiwa T, Sayama T, et al. Seed yield and its components of indeterminate and determinate lines in recombinant inbred lines of soybean. Breeding Science. 2015;**65**(2):154-160.

DOI: 10.1270/jsbbs.65.154

2000;**92**:1156-1161

[48] Mathew JP, Herbert SJ, Zhang S, Rautenkranz AAF, Litchfield GV. Differential response of soybean yield components to the timing of light enrichment. Agronomy Journal.

[49] Kokubun M. Physiological Mechanisms Regulating Flower Abortion in Soybean. In: Ng T-B, editor. ISBN: 978-953-307-219-7. Soybean - Biochemistry, Chemistry and Physiology. Rijeka: InTech; 2011, Available from: http://www.intechopen. com/books/soybean-biochemistry-

chemistry-and-physiology/

flower-abortion-in-soybean

Agronomy. 2008;**1**(2):45-50

physiologicalmechanisms-regulating-

[50] Kumar A, Pandey V, Shekh AM, Kumar M. Growth and yield response of soybean (*Glycine max* L.) in relation to temperature, photoperiod and sunshine duration at Anand, Gujarat, India. American-Eurasian Journal of

enrichment and shading under different densities. Plant, Soil and Environment.

**36**

[58] Dalchiavon FC, Passos e Carvalho M. Correlação linear e espacial dos componentes de produção e produtividade da soja linear and spatial correlation of the yield components and soybean yield. Londrina, Semina: Ciências Agrárias, Londrina. 2012;**33**(2):541-552

[59] Fageria NK, Moreira A, Cardoso M, Moraes M. Influence of lime and gypsum on yield and yield components of soybean and changes in soil chemical properties. Communications in Soil Science and Plant Analysis. 2014;**45**. DOI: 10.1080/00103624.2013.861906

[60] Moreira EN, Vale FXR, Paul PA, Rodrigues FA, Jesus WC. Temporal index in soybean cultivars of different maturity groups. Plant Disease. 2015;**99**:1216-1226

[61] Dermody O, Long SP, DeLucia EH. How does elevated CO2 or ozone affect the leaf-area index of soybean when applied independently? New Phytologist. 2006;**169**:145-155

[62] Bloom AJ. As carbon dioxide rises, food quality will decline without careful nitrogen management. California Agriculture. 2009;**63**(2):67-72

[63] Krisnawatia A, Adie MM. Variability of biomass and harvest index from several soybean genotypes as renewable energy source. Energy Procedia. 2015;**65**:14-21

[64] Gray SB, Dermody O, DeLucia EH. Spectral reflectance from a soybean canopy exposed to elevated CO2 and O3. Journal of Experimental Botany. 2010;**61**(15):4413-4422. DOI: 10.1093/ jxb/erq244

[65] Castro JC, Dohleman FG, Bernacchi CJ, Long SP. Elevated CO2 significantly delays reproductive

development of soybean under Free-Air Concentration Enrichment (FACE). Journal of Experimental Botany. 2009;**60**(10):2945-2951

[66] Jin J, Li Y, Liu X, Wang G, Tang C, Yu Z, et al. Elevated CO2 alters distribution of nodal leaf area and enhances nitrogen uptake contributing to yield increase of soybean cultivars grown in Mollisols. PLoS One. 2017;**12**(5):e0176688. DOI: 10.1371/ journal.pone.0176688

[67] Rogers HH, Cure JD, Thomas JF, Smith JM. Influence of elevated CO2 on growth of soybean plants. Crop Science. 1984;**24**:361-366

[68] Bruhn D. Plant respiration and climate change effects. Ph.D. thesis Plant Research Department Botanical Institute University of Copenhagen. Risø National Laboratory, Roskilde. Dannmark April; 2002. 139 p

[69] Francis D, Barlow PW. Temperature and the cell cycle. Symposia of the Society for Experimental Biology. 1988;**42**:181-201

[70] Tardieu F, Granier C. Quatitative analysis of cell division in leaves: methods, developmental patterns and effects of environmental conditions. Plant Molecular Biology. 2000;**43**:555-567

[71] Tardieu F, Reymond M, Hamard P, Granier C, Muller B. Spatial distributions of expansion rate, cell division rate and cell size in maize leaves: a synthesis of the effects of soil water status, evaporative demand and temperature. Journal of Experimental Botany. 2000;**51**(350):1505-1514

[72] Baker JT, Allen LH, Boote KJ, Jones P, Jones JW. Response of soybean to air temperature and carbon dioxide concentration. Crop Science. 1989;**29**(1):98-105

[73] Allen LH, Zhang L, Boote KJ, Hauser B. Elevated temperature intensity, timing, and duration of exposure affect soybean internode elongation, mainstem node number, and pod number per plant. The Crop Journal. 2018;**6**:148-161. DOI: 10.1016/j. cj.2017.10.005 2214-5141

[74] Perini LJ, Júnior NSF, Destro D, Prete CEC. Componentes da produção em cultivares de soja com crescimento determinado e indeterminado. Semina: Ciências Agrárias, Londrina. 2012;**33**(1):2531-2544

[75] Egli DB. The relationship between the number of nodes and pods in soybean communities. Crop Science. 2013;**53**:1668-1676. DOI: 10.2135/ cropsci2012.11.0663

[76] Kumagai E, Tacarindua CP, Homma K, Shiraiwa T, Sameshima R. Effects of elevated CO2 concentration and temperature on seed production and nitrogen concentration in soybean (*Glycine max* (L.) Merr.). Journal of Agricultural Meteorology. 2012;**68**(1):1-13

[77] Yoshihira AT, Tatsuhiko Shiraiwa T. Branch development responses to planting density and yield stability in soybean cultivars. Plant Production Science. 2016;**19**(3):331-339. DOI: 10.1080/1343943X.2016.1157443

[78] OSU Ohio State University. 2012. Worksheet to Estimate Soybean Yield. Aug 21. http://cornandsoybeandigest. com/soybean/4-componentsestimating-soybean-yield

[79] Egli DB. Flowering, pod set and reproductive success in soya bean. Journal of Agronomy and Crop Science. 2005;**191**:283-291

[80] Tanaka A, Fujita K, Tanaka Y. Effects of shading on nitrogen fixation and combined nitrogen absorption in soybean. Japanese Journal of

Soil Science and Plant Nutrition. 1980;**51**(4):281-284

[81] Ishikawa T, Nakaseko K, Goto K. Effects of shading on various growth stage to determinate and indeterminate soybeans. Report of the Hokkaido Branch, the Japanese Society of Breeding and Hokkaido Branch, the Crop Science Society of Japan. 1984;**24**:21

[82] Jiang H, Egli DB. Shade induced changes in flower and pod number and flower and fruit abscission in soybean. Agronomy Journal. 1993;**85**:221-225

[83] Kurosaki H, Yumoto S. Effects of low temperature and shading during flowering on the yield components in soybeans. Plant Production Science;**6**(1):17-23. DOI: 10.1626/ pps.6.17

[84] Hikosaka K, Kinugasa T, Oikawa S, Onoda Y, Hirose T. Effects of elevated CO2 concentration on seed production in C3 annual especies. Journal of Experimental Botany. 2011 Feb;**62**(4):1523-1530. DOI: 10.1093/jxb/ erq401

[85] Thomas JMG, Boote K, Allen JLH Jr, Gallo-Meagher M, Davis JM. Elevated temperature and carbon dioxide effects on soybean seed composition and transcript abundance. Crop Science. 2003;**43**:1548-1557

[86] Mulato BM, Möller M, Zucchi MI, Quecini V, Pinheiro JB. Genetic diversity in soybean germplasm. Pesquisa Agropecuária Brasileira. 2010, 2010;**45**(3):276-283

[87] Isopp H, Frenher M, Long SP, Nösberger J. Sucrose-phosphate synthase responds differently to sourcesink relations and to photosynthetic rates: *Lolium perenne* L. growing at elevated pCO2 in the field. Plant, Cell & Environment (Oxford). 2000;**23**(6):597-607

**39**

erq401

*Yield Components and Biomass Partition in Soybean: Climate Change Vision*

contribution no. 001482. Agronomy Journal. 2000;**92**:780-784. DOI: 10.2134/

[95] Jin J, Liu X, Wang G, Mi L, Shen Z, Chen X, et al. Agronomic and physiological contributions to the yield improvement of soybean cultivars released from 1950 to 2006 in Northeast China. Field Crops Research.

agronj2000.924780x

2010;**115**:116-123

*DOI: http://dx.doi.org/10.5772/intechopen.81627*

[88] Lemoine R, Camera SL, Atanassova

[89] Sudarić A, Vratarić M, Duvnjak T. Quantitative genetic analysis of yield components and grain yield for soybean cultivars. Agricultural Institute – Croatia. In: Kauffman HE editor. Proceedings of the World Soybean Conference VI, Chicago, USA. 479; 2002. 28 p. Vratarić, M., Sudarić, A. (2000.): [1] Soja. Book. Poljoprivredniinstitut Osijek, Osijek.

[90] Ziska LH, Bunce JA, Caulfield FA. Rising atmospheric carbon dioxide and seed yield of soybean genotypes. Crop Science. 2001;**41**:385-391

[91] Li D, Liuc H, Qiaoa Y, Wang Y, Cai Z, Donga B, et al. Effects of elevated CO2 on the growth, seed yield, and water use efficiency of soybean (*Glycine max* (L.) Merr.) under drought stress. Agricultural Water Management.

[92] Li D, Liuc H, Qiaoa Y, Wang Y, Cai Z, Donga B, et al. Effects of elevated CO2 on the growth, seed yield, and water use efficiency of soybean (*Glycine max* (L.) Merr.) under drought stress. Agricultural Water Management.

[93] Hikosaka K, Kinugasa T, Oikawa S, Onoda Y, Hirose T. Effects of Elevated CO2 Concentration on Seed Production in C3 Annual Species. Journal of Experimental Botany. Feb 2011;**62**(4):1523-30. DOI: 10.1093/jxb/

[94] Morrison MJ, Voldeng HD, Cober ER. Agronomic changes from 58 years of genetic improvement of shortseason soybean cultivars in Canada ECORC

R, Dédaldéchamp F, Allario T, Pourtau N, et al. Source-to-sink transport of sugar and regulation by environmental factors. Frontiers in Plant Science. 2013;**4**:272. DOI: 10.3389/

fpls.2013.00272

pp. 25-58

2013;**129**:105-112

2013;**129**:105-112

*Yield Components and Biomass Partition in Soybean: Climate Change Vision DOI: http://dx.doi.org/10.5772/intechopen.81627*

[88] Lemoine R, Camera SL, Atanassova R, Dédaldéchamp F, Allario T, Pourtau N, et al. Source-to-sink transport of sugar and regulation by environmental factors. Frontiers in Plant Science. 2013;**4**:272. DOI: 10.3389/ fpls.2013.00272

*Soybean - Biomass, Yield and Productivity*

[73] Allen LH, Zhang L, Boote KJ, Hauser B. Elevated temperature intensity, timing, and duration of exposure affect soybean internode elongation, mainstem node number, and pod number per plant. The Crop Journal. 2018;**6**:148-161. DOI: 10.1016/j. Soil Science and Plant Nutrition.

[81] Ishikawa T, Nakaseko K, Goto K. Effects of shading on various growth stage to determinate and indeterminate soybeans. Report of the Hokkaido Branch, the Japanese Society of Breeding and Hokkaido Branch, the Crop Science Society of Japan.

[82] Jiang H, Egli DB. Shade induced changes in flower and pod number and flower and fruit abscission in soybean. Agronomy Journal. 1993;**85**:221-225

[83] Kurosaki H, Yumoto S. Effects of low temperature and shading during flowering on the yield components in soybeans. Plant Production Science;**6**(1):17-23. DOI: 10.1626/

[84] Hikosaka K, Kinugasa T, Oikawa S, Onoda Y, Hirose T. Effects of elevated CO2 concentration on seed production in C3 annual especies. Journal of Experimental Botany. 2011 Feb;**62**(4):1523-1530. DOI: 10.1093/jxb/

[85] Thomas JMG, Boote K, Allen JLH Jr, Gallo-Meagher M, Davis JM. Elevated temperature and carbon dioxide effects on soybean seed composition and transcript abundance. Crop Science.

[86] Mulato BM, Möller M, Zucchi MI, Quecini V, Pinheiro JB. Genetic diversity in soybean germplasm. Pesquisa Agropecuária Brasileira. 2010,

[87] Isopp H, Frenher M, Long SP, Nösberger J. Sucrose-phosphate

synthase responds differently to sourcesink relations and to photosynthetic rates: *Lolium perenne* L. growing at elevated pCO2 in the field. Plant, Cell & Environment (Oxford).

1980;**51**(4):281-284

1984;**24**:21

pps.6.17

erq401

2003;**43**:1548-1557

2010;**45**(3):276-283

2000;**23**(6):597-607

[74] Perini LJ, Júnior NSF, Destro D, Prete CEC. Componentes da produção em cultivares de soja com crescimento

[75] Egli DB. The relationship between the number of nodes and pods in soybean communities. Crop Science. 2013;**53**:1668-1676. DOI: 10.2135/

[76] Kumagai E, Tacarindua CP, Homma K, Shiraiwa T, Sameshima R. Effects of elevated CO2 concentration and temperature on seed production and nitrogen concentration in soybean (*Glycine max* (L.) Merr.). Journal of Agricultural Meteorology.

[77] Yoshihira AT, Tatsuhiko Shiraiwa T. Branch development responses to planting density and yield stability in soybean cultivars. Plant Production Science. 2016;**19**(3):331-339. DOI: 10.1080/1343943X.2016.1157443

[78] OSU Ohio State University. 2012. Worksheet to Estimate Soybean Yield. Aug 21. http://cornandsoybeandigest.

[79] Egli DB. Flowering, pod set and reproductive success in soya bean. Journal of Agronomy and Crop Science.

[80] Tanaka A, Fujita K, Tanaka Y. Effects of shading on nitrogen fixation and combined nitrogen absorption in soybean. Japanese Journal of

com/soybean/4-componentsestimating-soybean-yield

2005;**191**:283-291

determinado e indeterminado. Semina: Ciências Agrárias, Londrina.

cj.2017.10.005 2214-5141

2012;**33**(1):2531-2544

cropsci2012.11.0663

2012;**68**(1):1-13

**38**

[89] Sudarić A, Vratarić M, Duvnjak T. Quantitative genetic analysis of yield components and grain yield for soybean cultivars. Agricultural Institute – Croatia. In: Kauffman HE editor. Proceedings of the World Soybean Conference VI, Chicago, USA. 479; 2002. 28 p. Vratarić, M., Sudarić, A. (2000.): [1] Soja. Book. Poljoprivredniinstitut Osijek, Osijek. pp. 25-58

[90] Ziska LH, Bunce JA, Caulfield FA. Rising atmospheric carbon dioxide and seed yield of soybean genotypes. Crop Science. 2001;**41**:385-391

[91] Li D, Liuc H, Qiaoa Y, Wang Y, Cai Z, Donga B, et al. Effects of elevated CO2 on the growth, seed yield, and water use efficiency of soybean (*Glycine max* (L.) Merr.) under drought stress. Agricultural Water Management. 2013;**129**:105-112

[92] Li D, Liuc H, Qiaoa Y, Wang Y, Cai Z, Donga B, et al. Effects of elevated CO2 on the growth, seed yield, and water use efficiency of soybean (*Glycine max* (L.) Merr.) under drought stress. Agricultural Water Management. 2013;**129**:105-112

[93] Hikosaka K, Kinugasa T, Oikawa S, Onoda Y, Hirose T. Effects of Elevated CO2 Concentration on Seed Production in C3 Annual Species. Journal of Experimental Botany. Feb 2011;**62**(4):1523-30. DOI: 10.1093/jxb/ erq401

[94] Morrison MJ, Voldeng HD, Cober ER. Agronomic changes from 58 years of genetic improvement of shortseason soybean cultivars in Canada ECORC

contribution no. 001482. Agronomy Journal. 2000;**92**:780-784. DOI: 10.2134/ agronj2000.924780x

[95] Jin J, Liu X, Wang G, Mi L, Shen Z, Chen X, et al. Agronomic and physiological contributions to the yield improvement of soybean cultivars released from 1950 to 2006 in Northeast China. Field Crops Research. 2010;**115**:116-123

**41**

**Chapter 3**

**Abstract**

Cultivation

*Kiyoshi Nagasuga*

the climate in each area.

**1. Introduction**

interception, lodging, pod, seed production

Soybean Seed Production and

The mechanism of soybean seed production is very complicated. Soybean yield is strongly associated with pod number and seed number; these are prompted by light interception and growth during the period between beginning blooming and beginning seed. But vigorous shoot growth during the vegetative stage does not contribute to pod growth and harvesting. In humid regions of Asia, soybean cultivation is incorporated into the rotation cropping in converted paddy fields, and wet soil often causes poor germination. Soybean leaves, trifoliate wide flat leaves, are easy to concentrate to the upper layer of the canopy. This suppresses light penetration to the lower layer and, as a result, produces imperfect seed yield in spite of enough biomass. Daytime leaf movement is useful for light penetration and photoinhibition in leaf photosynthesis. Leaf photosynthesis is generally associated with high yield; however, the relationship between them is not clear. It is necessary for high soybean yield not only to elucidate the mechanisms that these factors suppress soybean seed production more clearly but also to select the cultivars and cultivation suitable for

**Keywords:** biomass, canopy photosynthesis, cultivation, germination, light

Soybean is one of the important crops for oil and protein resources. Soybean production in 2016 is 336 million tons, and about 80% of the world production depends on a few major producers, the United States, Brazil and Argentina [1]. World soybean production continuously increases at a remarkable rate for the last several decades; it reached ca. 265 million tons in 2010 from ca. 30 million tons in 1970 [2]. This increase is associated with the improvement of soybean production; yield gain of the United States is 22.6 kg/ha/year from 1924 to 1997 and 12.1 kg/ha/year from 1950 to 1991 in China [3]. High soybean yield is also an important agricultural strategy not only in the major producers but also in the minor producers such as India, Japan and other Asian countries. Many researches about soybean production were actively made to achieve high yielding; for example, more than 60 years of researches have produced various types of soybean cultivars in Japan because soybean is the fundamental material of Japanese foods. However, these trials cannot find the breakthrough that improves soybean production in this country; Japanese

Canopy Photosynthesis in

## **Chapter 3**
