**Soil Fertility Status and Its Determining Factors in Tanzania**

Shinya Funakawa1, Hiroshi Yoshida1, Tetsuhiro Watanabe1,

Soh Sugihara1, Method Kilasara2 and Takashi Kosaki3

*1Graduate School of Agriculture, Kyoto University,* 

*2Faculty of Agriculture, Sokoine Agricultural University,* 

*3Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University 1,3Japan 2Tanzania* 

## **1. Introduction**

The pedogenetic conditions in Tanzania vary widely. In particular, the country has a wide variety of parent materials of soils because of the presence of volcanic mountains, the Great Rift Valley, and several plains and mountains with different elevations (hence, different temperatures). In addition, the amount and seasonal distribution pattern of the annual precipitation vary, from less than 500 mm to more than 2500 mm. The potential land use and agricultural production differ greatly among regions, due to the presence of different soils.

There have been several reports on the distribution patterns of soils and their physicochemical and mineralogical properties. According to a review of the history of soil surveys in Tanzania by Msanya *et al*. (2002), the major soil types described in the country are Ferric, Chromic, and Eutric Cambisols (39.7%); followed by Rhodic and Haplic Ferralsols (13.4%) and Humic and Ferric Acrisols (9.6%). To obtain basic information on soil mineralogy, Araki *et al*. (1998) investigated soil samples collected from regions at different altitudes in the Southern Highland and reported that the cation exchange capacity (CEC) per unit amount of clay content showed a negative correlation with elevation, which was accompanied by clay mineralogical transformation from mica to kaolinite. The authors suggested that soil formation on different planation surfaces is mainly controlled by the geological time factor whereby the lower surfaces are formed at the expense of the higher surfaces. Szilas *et al*. (2005) analyzed the mineralogy of well-drained upland soil samples collected from important agricultural areas in different ecological zones in the sub-humid and humid areas of Tanzania. They concluded that all soils were severely weathered and had limited but variable capacities to hold and release nutrients in plant-available form and to sustain low-input subsistence agriculture. Generally, there seems to be a consensus that the soils in Tanzania and the neighboring countries are not very fertile. The relevance of soil organic carbon management and appropriate fallowing systems such as agroforestry have been pointed out since as critical for sustaining agricultural production (Kimaro *et al*., 2008; Nandwa, 2001).

In the present study, the regional trend in soil fertility with respect to the soil mineralogical and chemical properties was investigated. Soil properties were correlated with different

Soil Fertility Status and Its Determining Factors in Tanzania 5

determined by atomic absorption spectrophotometry (AAS) (Shimadzu, AA-840-01). The exchangeable Al and H were extracted using 1 mol L–1 KCl. The exchange acidity (Al + H) was determined to pH 8.3 by titration with 0.01 mol L–1 NaOH wherein phenolphthalein was used as an indicator. Then, after the addition of 4% NaF solution to liberate OH– from the Al(OH)3 precipitates, the exchangeable Al was determined by back titration to obtain the same pH (8.3) using 0.01 mol L–1 HCl. The exchangeable H content was determined as the difference between the exchange acidity and the exchangeable Al. The total C and total N content were measured with an NC analyzer (Sumigraph NC-800; Sumika Chem. Anal. Service, Ltd., Tokyo, Japan). The available phosphate was determined by the modified Bray-II method (soil:solution = 1:20; shaking time 60s; Bray & Kurz, 1945; Olsen & Sommers, 1982). The particle size distribution was determined using a combination of sieving and pipette methods, in which a complete dispersion of silt and clay particles was achieved by adjusting the pH to 9–10 and supersonication, after pretreatment with H2O2 at 80°C to remove organic matter (Gee & Bauder, 1986). The clay mineral composition was semiquantified by the relative peak areas corresponding to mica (1.0 nm), kaolin minerals (1.0 and 0.7 nm), and expandable 2:1 minerals (1.4 nm) in the X-ray diffractograms obtained by using Cu–Kα radiation (RAD–2RS; Rigaku, Tokyo, Japan). The free oxides (Fe, Al, and Si) were extracted by the following two methods: (1) extraction in the dark with acid (pH 3) 0.2 mol L–1 ammonium oxalate (McKeague & Day, 1966) to obtain Feo, Alo, and Sio and (2) extraction with a citrate-bicarbonate mixed solution buffered at pH 7.3 by the addition of sodium dithionite (DCB) at 80°C (Mehra & Jackson, 1960) to obtain Fed and Ald. The Fe, Al, and Si content in each extract were determined by multi-channel inductively coupled argon plasma atomic emission spectroscopy (ICP-AES) (SPS-1500; Seiko, Chiba, Japan) after

filtration of the extracts by 0.45 μm Millipore filters.

**3.1 Physicochemical and mineralogical properties of the soils** 

among the soil characteristics for the different regions across Tanzania.

**3. Results and discussion** 

significantly differ for different land uses.

The data analysis was performed with the software SYSTAT version 8.0 (SPSS, 1998).

Selected physicochemical and mineralogical properties for the soils studied, and the corresponding statistical analysis, are summarized in Table 1. The surface soils studied were, in general, slightly acidic, with the average values of pH(H2O) and pH(KCl) being 6.17 and 5.37, respectively. The exchangeable Al content was low and the base saturation was high, exceeding 95% on average; hence, soil acidity was not considered a serious constraint for agricultural production. Although the average soil texture was sandy clay loam to clay loam, the particle size distribution varied widely. The average C content was 20.7 g kg–1, and the dominant clay mineral was kaolinite, followed by clay mica. However, the values obtained for most of the listed properties varied significantly over the regions under study. The coefficients of variation often exceeded 100%; which indicates a significant variability

Table 2 summarizes the data obtained, categorized according to the parent materials and land use. In terms of soil parent materials, the physicochemical and mineralogical properties of the volcanic-derived soils (*n* = 12) were significantly different from the other soil groups in terms of CEC, total C content, available P, and free oxide-related properties. Moreover, the proportion of 1.4-nm minerals was significantly higher for the soils originated from Cenozoic rocks or deposits. On the other hand, these soil properties generally did not

pedogenetic factors such as geology and climate. A comprehensive understanding of the distribution of some soil properties as influenced by soil-forming factors is essential for planning an appropriate land-use strategy. Besides, this knowledge will allow developing and sustaining agricultural production, while preserving natural resources such as forest and woodland ecosystems.

## **2. Materials and methods**

#### **2.1 Soil samples**

Ninety-five topsoil samples were collected from different regions of Tanzania. All the sampling points were located on slopes or plains, covering regions with different parent materials and with a wide variety of annual precipitation (less than 250 to more than 1500 mm) (Fig. 1; prepared based on Atlas of Tanzania [1967]). Apparent lowland soils were excluded from the analysis. The parent materials of the soils were broadly classified according to the following categories: (1) volcanic rocks (mostly basic), (2) granite and other plutonic rocks, (3) sedimentary and metamorphic rocks, and (4) Cenozoic rocks and recent deposits. The sampling plots corresponded to croplands or areas covered by either seminatural vegetation (forest or woodland) or secondary vegetation that had grown after human disturbance.

#### **2.2 Analytical methods**

The soil samples collected were air-dried and passed through a 2-mm mesh sieve. Soil pH in water or 1 mol L–1 KCl solution was measured with a glass electrode with a 1:5 soil:solution ratio. The pH(NaF) was measured with a glass electrode in 1 mol L–1 NaF solution after stirring for 2 min; the soil to solution ratio was 1:50. The CEC and the amount of exchangeable bases were measured after extracting with 1 mol L–1 NH4OAc at pH 7.0 and then with a 10% NaCl solution (Thomas, 1982). The NH4+ extracted with 10% NaCl solution was distilled after the addition of concentrated NaOH solution, and collected into a 2% H3BO4 solution. Subsequently, the NH4 content was determined by HCl titration (0.01 mol L–1). The exchangeable base (Na, K, Mg, and Ca) content in the NH4OAc solution was

Fig. 1. Geological (a) and climatic (b) conditions of the sampling plots

pedogenetic factors such as geology and climate. A comprehensive understanding of the distribution of some soil properties as influenced by soil-forming factors is essential for planning an appropriate land-use strategy. Besides, this knowledge will allow developing and sustaining agricultural production, while preserving natural resources such as forest

Ninety-five topsoil samples were collected from different regions of Tanzania. All the sampling points were located on slopes or plains, covering regions with different parent materials and with a wide variety of annual precipitation (less than 250 to more than 1500 mm) (Fig. 1; prepared based on Atlas of Tanzania [1967]). Apparent lowland soils were excluded from the analysis. The parent materials of the soils were broadly classified according to the following categories: (1) volcanic rocks (mostly basic), (2) granite and other plutonic rocks, (3) sedimentary and metamorphic rocks, and (4) Cenozoic rocks and recent deposits. The sampling plots corresponded to croplands or areas covered by either seminatural vegetation (forest or woodland) or secondary vegetation that had grown after

The soil samples collected were air-dried and passed through a 2-mm mesh sieve. Soil pH in water or 1 mol L–1 KCl solution was measured with a glass electrode with a 1:5 soil:solution ratio. The pH(NaF) was measured with a glass electrode in 1 mol L–1 NaF solution after stirring for 2 min; the soil to solution ratio was 1:50. The CEC and the amount of exchangeable bases were measured after extracting with 1 mol L–1 NH4OAc at pH 7.0 and then with a 10% NaCl solution (Thomas, 1982). The NH4+ extracted with 10% NaCl solution was distilled after the addition of concentrated NaOH solution, and collected into a 2% H3BO4 solution. Subsequently, the NH4 content was determined by HCl titration (0.01 mol L–1). The exchangeable base (Na, K, Mg, and Ca) content in the NH4OAc solution was

Mwanza

(a) (b)

Mbeya

Tabora

Fig. 1. Geological (a) and climatic (b) conditions of the sampling plots

Dar Es Salaam Morogoro

< 250 mm

Dar Es Salaam Morogoro

Moshi Arusha

Dodoma

Precipitation

1250 - 1500 mm 1000 - 1250 mm 750 - 1000 mm 500 - 750 mm 250 - 500 mm

> 1500 mm

Moshi Arusha

Dodoma

and woodland ecosystems.

**2.1 Soil samples** 

human disturbance.

Volcanic rocks (mostly basic) Cenozoic rocks and deposits Sedimentary and metamorphic rocks Granite and other plutonic rocks Parent materials

**2.2 Analytical methods** 

Mwanza

Mbeya

Tabora

**2. Materials and methods** 

determined by atomic absorption spectrophotometry (AAS) (Shimadzu, AA-840-01). The exchangeable Al and H were extracted using 1 mol L–1 KCl. The exchange acidity (Al + H) was determined to pH 8.3 by titration with 0.01 mol L–1 NaOH wherein phenolphthalein was used as an indicator. Then, after the addition of 4% NaF solution to liberate OH– from the Al(OH)3 precipitates, the exchangeable Al was determined by back titration to obtain the same pH (8.3) using 0.01 mol L–1 HCl. The exchangeable H content was determined as the difference between the exchange acidity and the exchangeable Al. The total C and total N content were measured with an NC analyzer (Sumigraph NC-800; Sumika Chem. Anal. Service, Ltd., Tokyo, Japan). The available phosphate was determined by the modified Bray-II method (soil:solution = 1:20; shaking time 60s; Bray & Kurz, 1945; Olsen & Sommers, 1982). The particle size distribution was determined using a combination of sieving and pipette methods, in which a complete dispersion of silt and clay particles was achieved by adjusting the pH to 9–10 and supersonication, after pretreatment with H2O2 at 80°C to remove organic matter (Gee & Bauder, 1986). The clay mineral composition was semiquantified by the relative peak areas corresponding to mica (1.0 nm), kaolin minerals (1.0 and 0.7 nm), and expandable 2:1 minerals (1.4 nm) in the X-ray diffractograms obtained by using Cu–Kα radiation (RAD–2RS; Rigaku, Tokyo, Japan). The free oxides (Fe, Al, and Si) were extracted by the following two methods: (1) extraction in the dark with acid (pH 3) 0.2 mol L–1 ammonium oxalate (McKeague & Day, 1966) to obtain Feo, Alo, and Sio and (2) extraction with a citrate-bicarbonate mixed solution buffered at pH 7.3 by the addition of sodium dithionite (DCB) at 80°C (Mehra & Jackson, 1960) to obtain Fed and Ald. The Fe, Al, and Si content in each extract were determined by multi-channel inductively coupled argon plasma atomic emission spectroscopy (ICP-AES) (SPS-1500; Seiko, Chiba, Japan) after filtration of the extracts by 0.45 μm Millipore filters.

The data analysis was performed with the software SYSTAT version 8.0 (SPSS, 1998).

#### **3. Results and discussion**

#### **3.1 Physicochemical and mineralogical properties of the soils**

Selected physicochemical and mineralogical properties for the soils studied, and the corresponding statistical analysis, are summarized in Table 1. The surface soils studied were, in general, slightly acidic, with the average values of pH(H2O) and pH(KCl) being 6.17 and 5.37, respectively. The exchangeable Al content was low and the base saturation was high, exceeding 95% on average; hence, soil acidity was not considered a serious constraint for agricultural production. Although the average soil texture was sandy clay loam to clay loam, the particle size distribution varied widely. The average C content was 20.7 g kg–1, and the dominant clay mineral was kaolinite, followed by clay mica. However, the values obtained for most of the listed properties varied significantly over the regions under study. The coefficients of variation often exceeded 100%; which indicates a significant variability among the soil characteristics for the different regions across Tanzania.

Table 2 summarizes the data obtained, categorized according to the parent materials and land use. In terms of soil parent materials, the physicochemical and mineralogical properties of the volcanic-derived soils (*n* = 12) were significantly different from the other soil groups in terms of CEC, total C content, available P, and free oxide-related properties. Moreover, the proportion of 1.4-nm minerals was significantly higher for the soils originated from Cenozoic rocks or deposits. On the other hand, these soil properties generally did not significantly differ for different land uses.

Soil Fertility Status and Its Determining Factors in Tanzania 7

Highly positive coefficients were obtained for pH(NaF), total C and total N, Feo, Alo, Sio, and Ald for the first component (Table 3). These variables correspond to the soil properties related to the presence of organic materials that are bound to amorphous compounds, which might be originated on recent volcanic activity. Hence, the first component is referred to as the "soil organic matter (SOM) and amorphous compounds" factor. The second component presents strongly negative coefficients for sand content and highly positive coefficients for clay content, exchangeable Mg, and Fed. These soil characteristics can be related to parent materials and clay formation, i.e. soils derived from mafic and/or clayey parent materials tend to exhibit fine-textured properties with high concentrations of exchangeable Mg and Fed through rapid mineral weathering and clay formation. Hence, the second component is denominated as the "texture" factor. The coefficients corresponding to the third component have highly positive or negative values for pH(H2O), pH(KCl), and exchangeable Ca and Al, indicating that a close relationship exists between this component and soil acidity. This relationship can be denominated as the "acidity" factor. The fourth and fifth components are denominated "available P and K" and the "sodicity" factors, respectively, on the basis of the coefficients correlating each of the components and the soil variables (exchangeable K and

available P, and exchangeable Na, respectively).

Volcanic rocks

Granite and other

plutonic rocks

Variable

Number of

CEC

Exch. Na

Exch. K

Exch. Mg

Averages for soils from different parent materials1)

Sedimentary and

metamorphic rocks

samples 12(9)2) 14 50(48)2) 19 37(35)2) 16 42(39)2)

pH(H2O) 5.91 ab 5.70 a 6.28 ab 6.43 b 6.34 a 6.14 a 6.04 a pH(KCl) 5.18 a 4.86 a 5.49 a 5.56 a 5.53 a 5.32 a 5.26 a pH(NaF) 9.04 b 7.95 a 8.04 a 8.05 a 8.12 a 7.99 a 8.22 a EC (μS dm–1) 103.2 b 48.1 a 78.7 ab 63.9 a 87.2 b 35.9 a 77.6 b

(cmolc kg–1) 29.5 b 6.93 a 12.5 a 13.3 a 14.3 a 8.6 a 15.7 a

(cmolc kg–1) 0.26 ab 0.07 a 0.11 a 0.39 b 0.11 a 0.12 ab 0.27 b

(cmolc kg–1) 2.49 b 0.45 a 1.11 a 0.68 a 1.17 a 0.70 a 1.19 a

(cmolc kg–1) 4.34 b 1.25 a 2.70 ab 3.12 b 2.95 a 2.53 a 2.72 a

Cenozoic rocks and

deposits

Natural and matured

secondary vegetatio

n

Averages for soils under different land uses1)

Incipient fallow

vegetatio

Cropland

n


Table 1. Physicochemical and mineralogical properties of the soils studied

#### **3.2 Principal component analysis for summarizing soil properties**

A principal component analysis was performed to evaluate soil parameters related to soil fertility. The variables selected were pH(H2O); pH(KCl); pH(NaF); CEC; amounts of exchangeable Na+, K+, Mg2+, Ca2+, and Al3+; sand, silt, and clay content; total C and total N content; available P content; and Feo, Alo, Sio, Fed, and Ald content. Table 3 summarizes the factor pattern for the first five principal components after varimax rotation. The analysis resulted in the soil parameters categorized into five principal components, which explained 85.4% of the total variance.

pH(H2O) 95 6.17 (0.80) 4.36–8.66 13.0 pH(KCl) 95 5.37 (0.89) 3.71–7.96 16.5 pH(NaF) 95 8.15 (0.66) 7.12–11.01 8.0 EC (μS dm–1) 95 74.3 (59.4) 10.0–325 79.9 CEC (cmolc kg–1) 95 14.0 (11.0) 1.61–59.5 78.6 Exch. Na (cmolc kg–1) 95 0.18 (0.29) 0.00–1.92 161 Exch. K (cmolc kg–1) 95 1.10 (1.12) 0.10–5.62 102 Exch. Mg (cmolc kg–1) 95 2.78 (2.14) 0.18–11.4 77.0 Exch. Ca (cmolc kg–1) 95 6.98 (8.76) 0.00–49.5 126 Exch. Al (cmolc kg–1) 95 0.21 (0.51) 0.00–2.99 241 Exch. bases (cmolc kg–1) 95 11.0 (11.4) 0.43–60.7 103 Base satur. (%) 95 95.4 (10.5) 49.0–101 11.0 Sand (%) 95 63.6 (23.3) 3.4–96.7 36.7 Silt (%) 95 11.2 (11.3) 0.2–48.1 101 Clay (%) 95 25.2 (17.6) 1.5–81.4 69.8 Total C (g kg–1) 95 20.7 (24.4) 2.13–152 124 Total N (g kg–1) 95 1.49 (1.84) 0.21–13.7 129 Available P (gP2O5 kg–1) 95 0.15 (0.24) 0.01–1.0 161 Feo (g kg–1) 95 2.46 (3.28) 0.02–14.7 133 Alo (g kg–1) 95 3.61 (9.34) 0.08–64.3 259 Sio (g kg–1) 95 1.10 (3.32) 0.00–21.7 303 Fed (g kg–1) 95 23.7 (25.8) 0.19–159 109 Ald (g kg–1) 95 4.55 (7.48) 0.01–50.9 164 0.7 nm minerals (%) 90 72.5 (27.0) 5.4–100 37.3 1.0 nm minerals (%) 90 19.6 (21.4) 0.0–91.2 109 1.4 nm minerals (%) 90 7.9 (17.9) 0.0–94.6 227

Table 1. Physicochemical and mineralogical properties of the soils studied

A principal component analysis was performed to evaluate soil parameters related to soil fertility. The variables selected were pH(H2O); pH(KCl); pH(NaF); CEC; amounts of exchangeable Na+, K+, Mg2+, Ca2+, and Al3+; sand, silt, and clay content; total C and total N content; available P content; and Feo, Alo, Sio, Fed, and Ald content. Table 3 summarizes the factor pattern for the first five principal components after varimax rotation. The analysis resulted in the soil parameters categorized into five principal components, which explained

**3.2 Principal component analysis for summarizing soil properties** 

85.4% of the total variance.

samples Ave.(STD) Min. –Max. CV (%)

Variable Number of

Highly positive coefficients were obtained for pH(NaF), total C and total N, Feo, Alo, Sio, and Ald for the first component (Table 3). These variables correspond to the soil properties related to the presence of organic materials that are bound to amorphous compounds, which might be originated on recent volcanic activity. Hence, the first component is referred to as the "soil organic matter (SOM) and amorphous compounds" factor. The second component presents strongly negative coefficients for sand content and highly positive coefficients for clay content, exchangeable Mg, and Fed. These soil characteristics can be related to parent materials and clay formation, i.e. soils derived from mafic and/or clayey parent materials tend to exhibit fine-textured properties with high concentrations of exchangeable Mg and Fed through rapid mineral weathering and clay formation. Hence, the second component is denominated as the "texture" factor. The coefficients corresponding to the third component have highly positive or negative values for pH(H2O), pH(KCl), and exchangeable Ca and Al, indicating that a close relationship exists between this component and soil acidity. This relationship can be denominated as the "acidity" factor. The fourth and fifth components are denominated "available P and K" and the "sodicity" factors, respectively, on the basis of the coefficients correlating each of the components and the soil variables (exchangeable K and available P, and exchangeable Na, respectively).


Soil Fertility Status and Its Determining Factors in Tanzania 9

Variable PC1 PC2 PC3 PC4 PC5

pH(H2O) –0.19 –0.07 –0.94 0.10 0.04 pH(KCl) –0.05 –0.11 –0.95 0.10 –0.02 pH(NaF) 0.84 0.00 –0.05 0.29 0.05 CEC 0.57 0.51 –0.09 0.39 0.43 Exch. Na –0.01 –0.01 0.04 0.08 0.93 Exch. K 0.01 0.32 –0.29 0.84 0.07 Exch. Mg –0.03 0.62 –0.42 0.36 0.39 Exch. Ca 0.05 0.28 –0.64 0.38 0.47 Exch. Al 0.20 0.12 0.64 –0.08 0.07 Sand –0.30 –0.83 –0.11 –0.35 –0.17 Silt 0.45 0.29 0.05 0.65 0.21 Clay 0.11 0.91 0.11 0.04 0.09 Total C 0.89 0.20 0.08 0.02 0.01 Total N 0.88 0.19 0.14 0.03 0.01 Avail. P 0.06 0.02 –0.26 0.87 0.04 Feo 0.62 0.32 0.18 0.57 –0.01 Alo 0.97 0.00 0.13 0.05 0.01 Sio 0.94 –0.07 0.07 0.10 0.04 Fed 0.09 0.86 0.15 0.13 –0.27 Ald 0.87 0.24 0.26 –0.06 –0.08 Eigenvalue 5.98 3.43 3.14 2.92 1.60 Proportion (%) 29.9 17.2 15.7 14.6 8.0

> "SOM and amorphous compounds" factor

**each of the principal components** 

Table 3. Factor pattern for the first four principal components (*n* = 95)

"Texture" factor

**3.3 Pedogenetic conditions determining the distribution patterns of factor scores for** 

Figure 2 shows a scattergram of the factor scores of SOM and amorphous compounds and those of available P and K. Both factor scores were significantly higher in soils derived from volcanic rocks than in other soils, but no significant correlation was observed. The factor scores are plotted on the geological map, as shown in Figure 3. There are two representative volcanic areas in Tanzania, namely, Mount. Kilimanjaro and the surrounding region and the southern mountain ranging between the east of Mbeya and Lake Malawi. Generally, the scores of the factor for SOM and amorphous compounds were highest in the region of the southern volcanic mountain ranges, followed by some plots around Mt. Kilimanjaro (Fig. 3a), whereas the scores of the factor for available P and K tended to be high in both volcanic

"Acidity" factor

"Available P and K" factor "Sodicity" factor


1) The values with the same letters are not significantly different by Tukey test (*p* < 0.05).

2) Parenthesis denotes the number of samples considered for XRD analysis (i.e. the percentage of 0.7, 1.0 and 1.4 nm minerals). Some samples were excluded from the analysis because of their X-ray amorphous natures.

Table 2. Average values of measured soil variables in terms of parent materials or land uses



Averages for soils under different land uses1)

Incipient fallow

vegetatio

Cropland

n

Averages for soils from different parent materials1)

Sedimentary and

metamorphic rocks

(cmolc kg–1) 11.60 b 1.68 a 5.87 ab 10.85 b 8.02 a 4.17 a 7.13 a

(cmolc kg–1) 0.18 a 0.28 a 0.25 a 0.07 a 0.22 a 0.28 a 0.18 a

(cmolc kg–1) 18.7 b 3.4 a 9.8 ab 15.0 b 12.2 a 7.5 a 11.3 a Base satur. (%) 97.4 ab 88.5 a 95.4 ab 99.0 b 96.5 a 92.3 a 95.5 a Sand (%) 36.2 a 73.9 b 64.7 b 70.2 b 66.2 a 69.0 a 59.1 a Silt (%) 28.7 b 6.6 a 9.2 a 9.0 a 9.5 a 7.0 a 14.3 a Clay (%) 35.1 a 19.5 a 26.1 a 20.8 a 24.3 a 23.9 a 26.5 a Total C (g kg–1) 43.3 b 12.5 a 20.1 a 13.9 a 28.4 a 11.8 a 17.2 a Total N (g kg–1) 3.40 b 0.98 a 1.42 a 0.87 a 1.98 a 0.80 a 1.33 a

(gP2O5 kg–1) 0.431 b 0.044 a 0.128 a 0.112 a 0.154 a 0.067 a 0.180 a Feo (g kg–1) 8.35 b 0.73 a 2.04 a 1.12 a 2.26 a 1.11 a 3.16 a Alo (g kg–1) 13.89 b 1.50 a 2.76 a 0.91 a 4.22 a 1.11 a 4.02 a Sio (g kg–1) 4.83 b 0.16 a 0.75 a 0.34 a 1.18 a 0.29 a 1.33 a Fed (g kg–1) 40.2 b 13.2 a 26.5 ab 11.4 a 23.2 a 26.2 a 23.1 a Ald (g kg–1) 11.34 b 3.50 a 4.37 a 1.50 a 5.58 a 2.98 a 4.24 a

(%) 75.8 a 80.4 a 73.3 a 63.0 a 73.9 a 79.6 a 68.3 a

(%) 20.1 a 13.8 a 22.0 a 17.8 a 20.9 a 16.1 a 19.9 a

(%) 4.2 a 5.8 a 4.7 a 19.2 b 5.2 a 4.3 a 11.8 a

2) Parenthesis denotes the number of samples considered for XRD analysis (i.e. the percentage of 0.7, 1.0 and 1.4 nm minerals). Some samples were excluded from the analysis because of their X-ray amorphous

Table 2. Average values of measured soil variables in terms of parent materials or land uses

1) The values with the same letters are not significantly different by Tukey test (*p* < 0.05).

Cenozoic rocks and

deposits

Natural and matured

secondary vegetatio

n

Variable

Exch. Ca

Exch. Al

Exch. bases

Available P

0.7 nm minerals

1.0 nm minerals

1.4 nm minerals

natures.

Volcanic rocks

Granite and other

plutonic rocks

Table 3. Factor pattern for the first four principal components (*n* = 95)

#### **3.3 Pedogenetic conditions determining the distribution patterns of factor scores for each of the principal components**

Figure 2 shows a scattergram of the factor scores of SOM and amorphous compounds and those of available P and K. Both factor scores were significantly higher in soils derived from volcanic rocks than in other soils, but no significant correlation was observed. The factor scores are plotted on the geological map, as shown in Figure 3. There are two representative volcanic areas in Tanzania, namely, Mount. Kilimanjaro and the surrounding region and the southern mountain ranging between the east of Mbeya and Lake Malawi. Generally, the scores of the factor for SOM and amorphous compounds were highest in the region of the southern volcanic mountain ranges, followed by some plots around Mt. Kilimanjaro (Fig. 3a), whereas the scores of the factor for available P and K tended to be high in both volcanic

Soil Fertility Status and Its Determining Factors in Tanzania 11

Mwanza

Mbeya

Tabora

Volcanic rocks (mostly basic) Cenozoic rocks and deposits Sedimentary and metamorphic rocks Granite and other plutonic rocks Parent materials

> < 0 > 1 0 - 1

Moshi Arusha

Dodoma

Mwanza

Mbeya

Scores of "texture" factor

Dar Es Salaam Morogoro

Tabora

< 0 > 1 0 - 1

Moshi Arusha

Precipitation (mm)

Volcanic rocks (mostly basic) Granite and other plutonic rocks Sedimentary and metamorphic rocks Cenozoic rocks and deposits

*r* = 0.13 (*ns*; *n* = 95)

V G S D a a a a Average and standard error

0 500 1000 1500 2000

Dodoma

Scores of "available P and K" factor

Dar Es Salaam Morogoro

Fig. 3. Distribution patterns of scores of (a) "SOM and amorphous," (b) "available P and K,"

Fig. 4. Relationships between precipitation and scores of (a) "acidity" and (b) "texture"

V G S D

a a a a Average and standard error

Factor scores of "texture" factor

and (c) "texture" factors in relation to geological conditions

*r* = 0.24 (*ns*; *n* = 95)

Volcanic rocks (mostly basic) Granite and other plutonic rocks Sedimentary and metamorphic rocks Cenozoic rocks and deposits

(a) (b)

Precipitation (mm)

0 500 1000 1500 2000

Volcanic rocks (mostly basic) Cenozoic rocks and deposits Sedimentary and metamorphic rocks Granite and other plutonic rocks Parent materials

< 0 > 1 0 - 1

(a) (b)

Moshi Arusha

Dodoma

(c)

Scores of "SOM and amorphous" factor

Dar Es Salaam Morogoro

factor


Factor scores of "acidity" factor

Volcanic rocks (mostly basic) Cenozoic rocks and deposits Sedimentary and metamorphic rocks Granite and other plutonic rocks Parent materials

Mwanza

Mbeya

Tabora

regions (Fig. 3b). Msanya *et al.* (2007) indicated that the volcanic soils in the southern mountain ranges were rich in K, compared to several Japanese volcanic soils, most likely reflecting lithological differences among the parent materials. The predominantly high scores of the factor for SOM and amorphous compounds in the southern volcanic mountain ranges indicate a relatively incipient feature of soils after recent active volcanic events and potentially high soil fertility relating to SOM in these regions. In addition, soils located in those volcanic regions could be more fertile in terms of P and K nutrients supply from soils.

Figure 3c represents the distribution pattern of the factor scores of texture in terms of the geological conditions. There is a certain regional trend in these factor scores, though no statistical difference was observed in terms of the geological condition as a whole. Among the soils of volcanic origin, those in the northern volcanic regions exhibited higher scores in the texture factor, consistent with a previous report by Mizota *et al.* (1988), in which they postulated that these soils were in the advanced stages of weathering of volcanic materials. The scores were high for some soils originated from sedimentary and metamorphic rocks, which are mostly distributed in the western region around Kigoma and the hill slopes near Tanga. Otherwise, scores were in general low for soils originated from granite, except for those of the southern highland.

Fig. 2. Relationship between the scores of the "SOM and amorphous" and "available P and K" factors

Figure 4 shows the influence of the amount of precipitation on the scores of selected factors. There was no significant relationship between the amount of precipitation and the factor scores of acidity or texture. Although the positive contribution of precipitation on mineral weathering might accompany soil acidification or the formation of clays and secondary Fe oxides, there was no correlation between those processes, which indirectly suggests that the influence of parent materials on soil properties is stronger than climatic factors among the soils studied.

regions (Fig. 3b). Msanya *et al.* (2007) indicated that the volcanic soils in the southern mountain ranges were rich in K, compared to several Japanese volcanic soils, most likely reflecting lithological differences among the parent materials. The predominantly high scores of the factor for SOM and amorphous compounds in the southern volcanic mountain ranges indicate a relatively incipient feature of soils after recent active volcanic events and potentially high soil fertility relating to SOM in these regions. In addition, soils located in those volcanic regions could be more fertile in terms of P and K nutrients

Figure 3c represents the distribution pattern of the factor scores of texture in terms of the geological conditions. There is a certain regional trend in these factor scores, though no statistical difference was observed in terms of the geological condition as a whole. Among the soils of volcanic origin, those in the northern volcanic regions exhibited higher scores in the texture factor, consistent with a previous report by Mizota *et al.* (1988), in which they postulated that these soils were in the advanced stages of weathering of volcanic materials. The scores were high for some soils originated from sedimentary and metamorphic rocks, which are mostly distributed in the western region around Kigoma and the hill slopes near Tanga. Otherwise, scores were in general low for soils originated from granite, except for

Fig. 2. Relationship between the scores of the "SOM and amorphous" and "available P and

V

Volcanic rocks (mostly basic) Granite and other plutonic rocks Sedimentary and metamorphic rocks Cenozoic rocks and deposits

<sup>G</sup> <sup>S</sup> <sup>D</sup>

Average and standard error

a a a

b

Factor scores of "SOM and amorphous compounds" factor




0

1

2

3

4

<sup>V</sup> <sup>G</sup> S C

aaa b

Average and standard error

Figure 4 shows the influence of the amount of precipitation on the scores of selected factors. There was no significant relationship between the amount of precipitation and the factor scores of acidity or texture. Although the positive contribution of precipitation on mineral weathering might accompany soil acidification or the formation of clays and secondary Fe oxides, there was no correlation between those processes, which indirectly suggests that the influence of parent materials on soil properties is stronger than climatic factors among the

supply from soils.

K" factors

soils studied.

those of the southern highland.

Factor scores of "available P and K" factor

Fig. 3. Distribution patterns of scores of (a) "SOM and amorphous," (b) "available P and K," and (c) "texture" factors in relation to geological conditions

Fig. 4. Relationships between precipitation and scores of (a) "acidity" and (b) "texture" factor

Soil Fertility Status and Its Determining Factors in Tanzania 13

*r*

*r* = 0.70 (*p* < 0.01, *n* = 90)

VGS D

b a a a Average and standard error

> V G S D

0.7 nm minerals (%) = - 56.2 + 19.5 ln(Precipitation in mm) + 5.92(Acidity factor) + 4.82(Mafic/clay factor) - 11.2(Sodicity factor) - 7.70(P/K factor)

= 0.45 (*p* < 0.01, *n* = 90)

Volcanic rocks (mostly basic) Granite and other plutonic rocks Sedimentary and metamorphic rocks Cenozoic rocks and deposits

a a a a Average and standard error

1.4 nm minerals (%) = 6.38 + 13.4(Sodicity factor) - 9.78(SOM/amorphous factor) + 3.17(P/K factor)

= 0.58 (*p* < 0.01, *n* = 90)

2

Volcanic rocks (mostly basic) Granite and other plutonic rocks Sedimentary and metamorphic rocks Cenozoic rocks and deposits

Factor scores of 'sodicity' factor -2 -1 0 1 2 3 4 5 6

Fig. 6. Relationships between clay mineralogy and soil and climatic factors. Abundances of

*r* = 0.37 (*ns*; *n* = 90)

*r*

2

0 500 1000 1500 2000

Precipitation (mm)

**3.5 General discussion on the soil conditions in Tanzania with specific reference to** 

As previously stated, soils can be considered as significantly fertile in the volcanic regions and areas around, due to the high SOM contents and the high P and K nutrient status. In addition, the soils around Lake Victoria are fertile due to the strong influence of the 1.4-nm minerals, which contributes to the retention of base cations. Both regions, namely, the volcanic regions and the regions around Lake Victoria, are included in the Great Rift Valley, which is the center of intensive agricultural activities of the country. However, in other areas of Tanzania, soils are generally low in SOM-related parameters and the 1.4-nm minerals are virtually absent, presumably due to consecutive mineral weathering under ustic soil moisture regime (Watanabe *et al.*, 2006). The proportion of kaolin minerals increases with

(a) 1.4 nm and (b) 0.7 nm minerals

0

20

40

60

80

100

0.7 nm minerals (%)

(b)

(a)

1.4 nm minerals (%)

0

20

40

60

80

100 <sup>V</sup> <sup>G</sup> S D

Average and standard error aa ab b

**potential agricultural development** 

Fig. 5. Distribution patterns of clay mineralogy in relation to geological or climatic conditions. Abundances of (a) 1.4 nm and (b) 0.7 nm minerals

#### **3.4 Pedogenetic conditions determining the clay mineralogy of the soils**

Figure 5 shows the distribution patterns of the clay mineralogy in relation to the geological and climatic conditions. The relative abundance of 1.4-nm minerals was often higher in the northern region of the Great Rift Valley and around Lake Victoria. On the other hand, the abundance of 0.7-nm minerals tended to be lower in the central steppe, which has lower precipitation than other regions. These relationships are more clearly presented in Figure 6. Stepwise multiple regression indicated that the abundances of 1.4-nm minerals (mostly smectite) could be expressed by the following equation:

$$\begin{aligned} \text{1.4-nm minerals (\%)} &= 6.38 + 13.4 \text{ (sodidity factor)} - 9.78 \text{ (SOM / amorphous factor)}\\ &+ 3.17 \text{ (P / K factor)}; \quad r^2 = 0.58 \text{ ( $p < 0.01, n = 90$ )} \end{aligned} \tag{1}$$

The 1.4-nm minerals were probably formed under the strong influence of the high sodicity of the parent materials around the Great Rift Valley, and were often observed in the soils in the flat plains near Lake Victoria.

On the other hand, the abundances of the 0.7-nm minerals (kaolin minerals) can be expressed by the following equation:

$$\begin{aligned} \text{0.7 -- nm minerals (\%)} &= -56.2 + 19.5 \text{ \ln(precipitation in mm)} + 5.92 \text{(acidity factor)}\\ &+ 4.82 \text{ (texture factor)} - 11.2 \text{ (sodicity factor)} - 7.70 \text{ (P / K factor)}; \\ &r^2 = 0.45 \text{ ( $p < 0.01, n = 90$ )} \end{aligned} \tag{2}$$

From this equation, it can be stated that the kaolin formation is promoted under highly humid conditions with the positive influence of soil acidity and texture (or clayey parent materials) as well as the negative influence of sodicity. Hence, it can be inferred that the clay mineralogical properties of the soils studied herein were formed under the strong influence of the present climatic conditions as well as the parent materials on a countrywide scale in Tanzania.

Fig. 5. Distribution patterns of clay mineralogy in relation to geological or climatic

Figure 5 shows the distribution patterns of the clay mineralogy in relation to the geological and climatic conditions. The relative abundance of 1.4-nm minerals was often higher in the northern region of the Great Rift Valley and around Lake Victoria. On the other hand, the abundance of 0.7-nm minerals tended to be lower in the central steppe, which has lower precipitation than other regions. These relationships are more clearly presented in Figure 6. Stepwise multiple regression indicated that the abundances of 1.4-nm minerals (mostly

( ) ( ) ( )

( ) ( ) ( )

(2)

<sup>+</sup> = <= (1)

Volcanic rocks (mostly basic) Cenozoic rocks and deposits Sedimentary and metamorphic rocks Granite and other plutonic rocks Parent materials

Mwanza

Mbeya

Tabora

0 - 50% 80 - 100% 50 - 80%

Moshi Arusha

Dodoma

Relative abundance of 0.7 nm minerals in XRD

Dar Es Salaam Morogoro

( ) ( )

 *r p n* <sup>2</sup> 1.4 nm minerals % 6.38 13.4 sodicity factor – 9.78 SOM /amorphous factor 3.17 P /K factor ; 0.58 0.01, 90

The 1.4-nm minerals were probably formed under the strong influence of the high sodicity of the parent materials around the Great Rift Valley, and were often observed in the soils in

On the other hand, the abundances of the 0.7-nm minerals (kaolin minerals) can be

0.7 nm min erals % – 56.2 19.5 ln precipitation in mm 5.92 acidity factor 4.82 texture factor – 11.2 sodicity factor – 7.70 P /K factor ; 0.45 0.01, 90

− = + +

*r p n* 

= <=

From this equation, it can be stated that the kaolin formation is promoted under highly humid conditions with the positive influence of soil acidity and texture (or clayey parent materials) as well as the negative influence of sodicity. Hence, it can be inferred that the clay mineralogical properties of the soils studied herein were formed under the strong influence of the present climatic conditions as well as the parent materials on a countrywide scale in

( ) ( ) ( ) ( ) <sup>2</sup>

**3.4 Pedogenetic conditions determining the clay mineralogy of the soils** 

conditions. Abundances of (a) 1.4 nm and (b) 0.7 nm minerals

0 - 10% 50 - 100% 10 - 50%

Moshi Arusha

(a) (b)

Dodoma

Relative abundance of 1.4 nm minerals in XRD

Dar Es Salaam Morogoro

smectite) could be expressed by the following equation:

Volcanic rocks (mostly basic) Cenozoic rocks and deposits Sedimentary and metamorphic rocks Granite and other plutonic rocks Parent materials

Mwanza

Mbeya

Tabora

− = +

the flat plains near Lake Victoria.

+

Tanzania.

expressed by the following equation:

Fig. 6. Relationships between clay mineralogy and soil and climatic factors. Abundances of (a) 1.4 nm and (b) 0.7 nm minerals

#### **3.5 General discussion on the soil conditions in Tanzania with specific reference to potential agricultural development**

As previously stated, soils can be considered as significantly fertile in the volcanic regions and areas around, due to the high SOM contents and the high P and K nutrient status. In addition, the soils around Lake Victoria are fertile due to the strong influence of the 1.4-nm minerals, which contributes to the retention of base cations. Both regions, namely, the volcanic regions and the regions around Lake Victoria, are included in the Great Rift Valley, which is the center of intensive agricultural activities of the country. However, in other areas of Tanzania, soils are generally low in SOM-related parameters and the 1.4-nm minerals are virtually absent, presumably due to consecutive mineral weathering under ustic soil moisture regime (Watanabe *et al.*, 2006). The proportion of kaolin minerals increases with

Soil Fertility Status and Its Determining Factors in Tanzania 15

This study was supported by a Grant-in-Aid for Scientific Research (No. 17208028) from the

Araki, S., Msanya, B.M., Magoggo, J.P., Kimaro, D.N. & Kitagawa, Y. 1998. Characterization

Bray, R.H. & Kurz, L.T. 1945. Determination of total organic and available forms of

Gee, G.W. & Bauder, J.W. 1986. Particle size analysis. In: *Methods of Soil Analysis* (ed. A.

Kimaro, A.A., Timmer, V.R., Chamshama, S.A.O., Mugasha, A.G. & Kimaro, D.A. 2008.

McKeague, J.A. & Day, J.H. 1966. Dithionite- and oxalate-extractable Fe and Al as aids in differentiating various classes of soils. *Canadian Journal of Soil Science*, 46, 13–22. Mehra, O.P. & Jackson, M.L. 1960. Iron oxide removal from soils and clays by a dithionite-

Mizota, C., Kawasaki, I. & Wakatsuki, T. 1988. Clay mineralogy and chemistry of seven

Msanya, B.M., Magoggo, J.P. & Otsuka, H. 2002. Development of soil surveys in Tanzania

Msanya, B.M., Otsuka, H. Araki, S. & Fujitake, N. 2007. Characterization of volcanic ash soils

Olsen, S.R. & Sommers, L.E. 1982. 24. Phosphorus. In: *Methods of Soil Analysis*, Part 2,

Surveys and Mapping Division, Tanzania 1967. Atlas of Tanzania. Dar es Salaam, Tanzania. Szilas, C., Møberg, J.P., Borggaard, O.K. & Semoka, J.M.R. 2005. Mineralogy of characteristic

classification. *African study monographs (Supplementary issue)*, 34, 39–55. Nandwa, S.M. 2001. Soil organic carbon (SOC) management for sustainable productivity of

pedons formed in volcanic ash, Tanzania. *Geoderma*, 43, 131–141.

Klute), pp. 383–411. Soil Science Society of America, Madison, WI.

of soils on various planation surfaces in Tanzania. In: *Summaries of 16th World* 

Differential response to tree fallows in rotational woodlot systems in semi-arid Tanzania: Post-fallow maize yield, nutrient uptake, and soil nutrients. *Agriculture,* 

citrate system buffered with sodium bicarbonate. *Clays and Clay Minerals*, 7, 317–

in southwestern Tanzania: Morphology, physicochemical properties, and

cropping and agro-forestry systems in Eastern and Southern Africa. *Nutrient* 

Chemical and Microbiological Properties, Second Edition (eds. A.L. Page, R.H. Miller & D.R. Keeny), pp. 403–430. American Society of Agronomy & Soil Science

well-drained soils of sub-humid to humid Tanzania. *Acta Agriculturae Scandinavica,* 

Ministry of Education, Culture, Sports, Science and Technology, Japan.

*Congress of Soil Science*, Vol. I, pp. 310, Montpellier, France.

phosphorus in soils. *Soil Science*, 59, 39–45

*Ecosystems & Environment*, 125, 73–83.

(Review). *Pedologist*, 46, 79–88.

*Cycling in Agroecosystems*, 61, 143–158.

Society of America, Madison, WI. SPSS 1998. SYSTAT 8.0. Statistics. SPSS, Chicago.

*Section B - Plant Soil Science*, 55, 241–251.

in the future.

**6. References** 

327.

**5. Acknowledgements** 

conditions are not favorable for agricultural production and must be strongly considered when studying the feasibility of agricultural development in different areas

the precipitation; hence, soil fertility decreases in regions of high humidity. Soil fertility in terms of clay mineralogy is comparatively higher in dry regions than in humid regions because of the greater abundance of mica minerals. However, water availability decreases in such dry regions. Thus, the semiarid regions in Tanzania suffer from water scarcity, while the relatively humid areas have less fertile soil that predominantly contains kaolin minerals. In summary, high scores in SOM-related properties and the 1.4-nm minerals contribute to relatively high soil fertility in Great Lift Valley regions, whereas either water scarcity or low soil fertility are not favorable for agricultural production in the other regions of Tanzania. These conditions should be considered when studying the feasibility of agricultural development in different areas in the future.

#### **4. Conclusion**

From the principal component analysis of the collected soil samples, five individual factors—SOM and amorphous compounds, texture, acidity, available P and K, and sodicity—were determined which explained 85.4% of total variance. From the clay mineralogical composition and the relation between the geological conditions (or parent materials) and the annual precipitation and the scores of the five factors, the following conclusions can be summarized:


$$\begin{aligned} \text{1.4-nm minerals (\%)}= 6.38+13.4 \text{ (sodicity factor)}-9.78 \text{ (SOM / amorphous factor)}\\ +3.17 \text{ (P / K factor)}; \quad r^2 = 0.58 \text{ ( $p < 0.01, n = 90$ )} \end{aligned}$$

The 1.4-nm minerals were probably formed under conditions of high sodicity and were often observed in the soils near Lake Victoria.

4. The abundance of 0.7-nm minerals (kaolin minerals) can be expressed by the following equation (Equation 2):

( ) ( ) ( ) 0.7 nm min erals % – 56.2 19.5 ln precipitation in mm 5.92 acidity factor  − = + +

> ( ) ( ) ( ) 4.82 texture factor – 11.2 sodicity factor – 7.70 P /K factor ;  +

$$r^2 = 0.45 \text{ (}p < 0.01 \text{ ,}n = 90\text{)}$$

Equation 2 suggests that kaolin formation is promoted under highly humid conditions, which is also controlled by the acidity and texture of the soil (or parent materials). Hence, the results indicate that the formation of the soils studied in the present study was strongly influenced by climatic conditions and parent materials.

5. In Tanzania, the volcanic regions and the Great Rift Valley region, where soil is generally more fertile than in other regions, are favorable to modernized agriculture. The semiarid regions in Tanzania suffer from water scarcity, while the relatively humid areas have less fertile soil that predominantly contains kaolin minerals. These conditions are not favorable for agricultural production and must be strongly considered when studying the feasibility of agricultural development in different areas in the future.

#### **5. Acknowledgements**

This study was supported by a Grant-in-Aid for Scientific Research (No. 17208028) from the Ministry of Education, Culture, Sports, Science and Technology, Japan.

#### **6. References**

14 Soil Health and Land Use Management

the precipitation; hence, soil fertility decreases in regions of high humidity. Soil fertility in terms of clay mineralogy is comparatively higher in dry regions than in humid regions because of the greater abundance of mica minerals. However, water availability decreases in such dry regions. Thus, the semiarid regions in Tanzania suffer from water scarcity, while the relatively humid areas have less fertile soil that predominantly contains kaolin minerals. In summary, high scores in SOM-related properties and the 1.4-nm minerals contribute to relatively high soil fertility in Great Lift Valley regions, whereas either water scarcity or low soil fertility are not favorable for agricultural production in the other regions of Tanzania. These conditions should be considered when studying the feasibility of agricultural

From the principal component analysis of the collected soil samples, five individual factors—SOM and amorphous compounds, texture, acidity, available P and K, and sodicity—were determined which explained 85.4% of total variance. From the clay mineralogical composition and the relation between the geological conditions (or parent materials) and the annual precipitation and the scores of the five factors, the following

1. The maximum scores of "SOM and amorphous compounds" were found at the volcanic center of the southern mountain ranges from the east of Mbeya to Lake Malawi. 2. The scores of the "available P and K" were high in the volcanic regions around Mt.

3. The abundance of 1.4-nm minerals (mostly smectite) can be expressed by the following

 *r p n* <sup>2</sup> 1.4 nm minerals % 6.38 13.4 sodicity factor – 9.78 SOM /amorphous factor 3.17 P /K factor ; 0.58 0.01, 90

4. The abundance of 0.7-nm minerals (kaolin minerals) can be expressed by the following

0.7 nm min erals % – 56.2 19.5 ln precipitation in mm 5.92 acidity factor 4.82 texture factor – 11.2 sodicity factor – 7.70 P /K factor ; 0.45 0.01, 90

− = + +

was strongly influenced by climatic conditions and parent materials.

*r p n* 

= <=

5. In Tanzania, the volcanic regions and the Great Rift Valley region, where soil is generally more fertile than in other regions, are favorable to modernized agriculture. The semiarid regions in Tanzania suffer from water scarcity, while the relatively humid areas have less fertile soil that predominantly contains kaolin minerals. These

+ = <=

( ) ( )

( ) ( ) ( ) ( ) <sup>2</sup>

Equation 2 suggests that kaolin formation is promoted under highly humid conditions, which is also controlled by the acidity and texture of the soil (or parent materials). Hence, the results indicate that the formation of the soils studied in the present study

The 1.4-nm minerals were probably formed under conditions of high sodicity and were

( ) ( ) ( )

( ) ( ) ( )

Kilimanjaro and in the southern volcanic mountain ranges.

development in different areas in the future.

conclusions can be summarized:

equation (Equation 1):

equation (Equation 2):

+

− = +

often observed in the soils near Lake Victoria.

**4. Conclusion** 


**2** 

*USA* 

**The Role of Aluminum-Organo Complexes** 

The knowledge achieved during the last decades on the dynamics of organic matter (OM) and inorganic elements in soils has been essential to predict long-term effects of land management and develop sustainable practices that contribute to mitigate the decline in soil

Knowledge about soil organic matter (SOM) properties is essential to understand soil processes. The distribution and chemical speciation of organic carbon (OC) in soil have a major role on biogeochemical processes, e.g. its own chemical stability and the mobility and bioavailability of nutrient and contaminants (Eusterhues et al. 2005; von Lutzow et al. 2008). Therefore, SOM properties are directly related to essential environmental processes, e.g. plant production, carbon sequestration or water pollution. The decline in SOM quality results in land degradation, increasing flooding events or the rates of irrigation and

Organo-mineral associations and complexation of SOM with metals ions largely determines the stability and degradability of OM (Kogel-Knabner et al. 2010). The relevance of intermolecular interactions of OM with metal ions in solution on substrate degradation, e.g. complexation with aluminum (Al), has been already highlighted in the existing literature

Overall, this chapter addresses the relevance of understanding the mechanisms responsible for OC stabilization in soil. For instance, knowledge on SOM stability is essential to develop strategies for carbon sequestration in soil. Soil organic matter constitutes approximately 2/3 of the global terrestrial C pool (Batjes 1996), and OC dynamics in soils control a large part of the terrestrial carbon (C) cycle. In general, human activities cause a net release of CO2 to the atmosphere of about 800 Gt C per year (Schlesinger 1984; Schlesinger and Andrews 2000) and more concretely, forest conversion to agriculture can release up to 75% of stored soil OC as CO2 (Lal 2004). Besides, world soils have constituted a major source of enrichment of atmospheric concentration of carbon dioxide (CO2) ever since the dawn of settled

Nowadays carbon sequestration in soils is a main area of research because of the importance of soils for food production and its role in the global carbon cycle. Depending on

**1. Introduction** 

quality and the potential threats for human health.

fertilization necessary for agricultural activities.

**1.1 Stability of organic carbon in soils** 

agriculture, about 10,000 years ago.

(Sollins et al. 1996) and prompted the research presented.

 **in Soil Organic Matter Dynamics** 

*Department of Soil Science, College of Agriculture and Life Sciences* 

Maria C. Hernández-Soriano

*North Carolina State University, Raleigh NC* 


## **The Role of Aluminum-Organo Complexes in Soil Organic Matter Dynamics**

Maria C. Hernández-Soriano

*Department of Soil Science, College of Agriculture and Life Sciences North Carolina State University, Raleigh NC USA* 

#### **1. Introduction**

16 Soil Health and Land Use Management

Thomas, G.W. 1982. Exchangeable cations. In: *Methods of Soil Analysis*, Part 2, Chemical

Watanabe, T., Funakawa, S. & Kosaki, T. 2006. Clay mineralogy and its relationship to soil

Asia: Japan, Thailand and Indonesia. *Geoderma*, 136, 51–63.

Madison, WI.

and Mineralogical Properties (eds. A.L. Page, R.H. Miller & D.R. Keeney), pp. 159–165. American Society of Agronomy & Soil Science Society of America,

solution composition in soils from different weathering environment of humid

The knowledge achieved during the last decades on the dynamics of organic matter (OM) and inorganic elements in soils has been essential to predict long-term effects of land management and develop sustainable practices that contribute to mitigate the decline in soil quality and the potential threats for human health.

Knowledge about soil organic matter (SOM) properties is essential to understand soil processes. The distribution and chemical speciation of organic carbon (OC) in soil have a major role on biogeochemical processes, e.g. its own chemical stability and the mobility and bioavailability of nutrient and contaminants (Eusterhues et al. 2005; von Lutzow et al. 2008). Therefore, SOM properties are directly related to essential environmental processes, e.g. plant production, carbon sequestration or water pollution. The decline in SOM quality results in land degradation, increasing flooding events or the rates of irrigation and fertilization necessary for agricultural activities.

Organo-mineral associations and complexation of SOM with metals ions largely determines the stability and degradability of OM (Kogel-Knabner et al. 2010). The relevance of intermolecular interactions of OM with metal ions in solution on substrate degradation, e.g. complexation with aluminum (Al), has been already highlighted in the existing literature (Sollins et al. 1996) and prompted the research presented.

#### **1.1 Stability of organic carbon in soils**

Overall, this chapter addresses the relevance of understanding the mechanisms responsible for OC stabilization in soil. For instance, knowledge on SOM stability is essential to develop strategies for carbon sequestration in soil. Soil organic matter constitutes approximately 2/3 of the global terrestrial C pool (Batjes 1996), and OC dynamics in soils control a large part of the terrestrial carbon (C) cycle. In general, human activities cause a net release of CO2 to the atmosphere of about 800 Gt C per year (Schlesinger 1984; Schlesinger and Andrews 2000) and more concretely, forest conversion to agriculture can release up to 75% of stored soil OC as CO2 (Lal 2004). Besides, world soils have constituted a major source of enrichment of atmospheric concentration of carbon dioxide (CO2) ever since the dawn of settled agriculture, about 10,000 years ago.

Nowadays carbon sequestration in soils is a main area of research because of the importance of soils for food production and its role in the global carbon cycle. Depending on

The Role of Aluminum-Organo Complexes in Soil Organic Matter Dynamics 19

Chemical protection involves interactions of OM with minerals; physical protection makes OC inaccessible to microbes and enzymes; and biochemical protection results from

Chemical stabilization may result from association of OC compounds with mineral surfaces primarily in silt- and clay-sized particles (Sollins et al. 1996), but the mechanisms by which the different OM fractions adsorb onto mineral surfaces and the relationship between mineralogy and the chemistry of OM bound in organo-mineral associations are not yet fully

For the purposes of the research discussed, this chapter focuses on the mechanisms involved in chemical stabilization. The primary scope is to provide a comprehensive understanding



Aluminium is the third most abundant element in the Earth´s crust, occurring at about 8%, and is a main or secondary component of numerous minerals, especially silicates. The only

of chemical stabilization of OC in subsoil, considering the following statements:

extractable forms of Fe and Al (Kögel-Knabner et al. 2008).

stabilized before reaching saturation (Eusterhues et al. 2005).

**1.3 Complexation of aluminum by organic compounds** 

Fig. 1. Conceptual scheme of carbon cycling in soil.

differential degradability of organic structures.

**1.2 Chemical protection of organic matter** 

understood.

environmental conditions and land use, soils may act as sources or sinks for C. Therefore, understanding the mechanisms that control stabilization and release of C is essential for the prediction of the effects of global climate change and for the development of management strategies to increase carbon sequestration in soils, which constituted a major demand at the Kyoto Protocol on climate change in 1992.

In general, it can be assumed that the pool of stable SOM in the soil solid phase is in equilibrium with the soluble organic matter (dissolved organic carbon, DOC) in the soil solution (Fig. 1). The term SOM refers to all organic substances in the soil. Organic carbon in soil can originate from natural or anthropogenic inputs, i.e. plant and animal litter decomposition, substances synthesized through microbial and chemical reactions and biomass of soil micro-organisms, but also soil addition with organic amendments. The turnover of C in soils is controlled mainly by water regimes and temperature, but is modified by factors such as size and physicochemical properties of C additions in litter or root systems or distribution of C within the soil matrix and its interactions with clay surfaces (Oades 1988).

The stabilization of organic materials in soils by the soil matrix is a function of the chemical nature of the soil mineral fraction and the presence of multivalent cations in the soil solution (Fig. 1), the presence of mineral surfaces capable of adsorbing organic materials, and the architecture of the soil matrix. The degree and amount of protection offered by each mechanism depends on the chemical and physical properties of the mineral matrix and the morphology and chemical structure of the organic matter. Thus, each mineral matrix will have a unique and finite capacity to stabilize organic matter (Baldock and Skjemstad 2000).

Three types of pathways are commonly considered in the formation of stable OM in soils (Christensen 1996; Sollins et al. 1996): Selective enrichment of organic compounds, which refers to the inherent recalcitrance of specific organic molecules against degradation by microorganisms and enzymes (Fig. 1); Chemical stabilization, involving all intermolecular interactions between organic substances and inorganic substances leading to a decrease in availability of the organic substrate due to surface condensation and changes in conformation, i.e., sorption to soil minerals and precipitation; Physical stabilization, related to the decrease in the accessibility of the organic substrates to microorganisms caused by occlusion within aggregates. According to Kogel-Knabner et al. (2008), the protection against decomposition imparted to soil organic carbon (SOC) by these mechanisms decreases in the order: chemically protected > physically protected > biochemically protected > non-protected. Hence, the relationship between soil structure and the ability of soil to stabilize SOM is a key element in soil C dynamics.

The sorption of OM is assumed as a chemisorptive process that occurs concomitantly with changes in OM conformation. Organomineral interactions lead to aggregations of clay particles and organic materials, which stabilizes both soil structure and the C compounds within aggregates, but due to the heterogeneity of natural soil systems different adsorption mechanism(s) may operate. Besides, different studies have evidenced the different depth distribution of OC in soils (Kaiser and Guggenberger 2000; Gillabel et al. 2010) and the dissimilarity in controls on C dynamics and decomposition of soil OC with depth in topsoil and subsoil (Fontaine et al. 2007; Salomé et al. 2009). For instance, according to Guggenberger and Kaiser (2003) sorptive preservation by location of OM in small pores rarely occur in topsoil horizons but primarily in subsoil horizons. Furthermore, the authors indicated that Fe oxides may be the most important sorbents for the formation of organomineral associations in the subsoils, which was later corroborated by Kogel-Knabner (2008).

environmental conditions and land use, soils may act as sources or sinks for C. Therefore, understanding the mechanisms that control stabilization and release of C is essential for the prediction of the effects of global climate change and for the development of management strategies to increase carbon sequestration in soils, which constituted a major demand at the

In general, it can be assumed that the pool of stable SOM in the soil solid phase is in equilibrium with the soluble organic matter (dissolved organic carbon, DOC) in the soil solution (Fig. 1). The term SOM refers to all organic substances in the soil. Organic carbon in soil can originate from natural or anthropogenic inputs, i.e. plant and animal litter decomposition, substances synthesized through microbial and chemical reactions and biomass of soil micro-organisms, but also soil addition with organic amendments. The turnover of C in soils is controlled mainly by water regimes and temperature, but is modified by factors such as size and physicochemical properties of C additions in litter or root systems or distribution of C within the soil matrix and its interactions with clay surfaces

The stabilization of organic materials in soils by the soil matrix is a function of the chemical nature of the soil mineral fraction and the presence of multivalent cations in the soil solution (Fig. 1), the presence of mineral surfaces capable of adsorbing organic materials, and the architecture of the soil matrix. The degree and amount of protection offered by each mechanism depends on the chemical and physical properties of the mineral matrix and the morphology and chemical structure of the organic matter. Thus, each mineral matrix will have a unique and finite capacity to stabilize organic matter (Baldock and Skjemstad 2000). Three types of pathways are commonly considered in the formation of stable OM in soils (Christensen 1996; Sollins et al. 1996): Selective enrichment of organic compounds, which refers to the inherent recalcitrance of specific organic molecules against degradation by microorganisms and enzymes (Fig. 1); Chemical stabilization, involving all intermolecular interactions between organic substances and inorganic substances leading to a decrease in availability of the organic substrate due to surface condensation and changes in conformation, i.e., sorption to soil minerals and precipitation; Physical stabilization, related to the decrease in the accessibility of the organic substrates to microorganisms caused by occlusion within aggregates. According to Kogel-Knabner et al. (2008), the protection against decomposition imparted to soil organic carbon (SOC) by these mechanisms decreases in the order: chemically protected > physically protected > biochemically protected > non-protected. Hence, the relationship between soil structure and the ability of

The sorption of OM is assumed as a chemisorptive process that occurs concomitantly with changes in OM conformation. Organomineral interactions lead to aggregations of clay particles and organic materials, which stabilizes both soil structure and the C compounds within aggregates, but due to the heterogeneity of natural soil systems different adsorption mechanism(s) may operate. Besides, different studies have evidenced the different depth distribution of OC in soils (Kaiser and Guggenberger 2000; Gillabel et al. 2010) and the dissimilarity in controls on C dynamics and decomposition of soil OC with depth in topsoil and subsoil (Fontaine et al. 2007; Salomé et al. 2009). For instance, according to Guggenberger and Kaiser (2003) sorptive preservation by location of OM in small pores rarely occur in topsoil horizons but primarily in subsoil horizons. Furthermore, the authors indicated that Fe oxides may be the most important sorbents for the formation of organomineral associations in the subsoils, which was later corroborated by Kogel-Knabner (2008).

Kyoto Protocol on climate change in 1992.

soil to stabilize SOM is a key element in soil C dynamics.

(Oades 1988).

Fig. 1. Conceptual scheme of carbon cycling in soil.

Chemical protection involves interactions of OM with minerals; physical protection makes OC inaccessible to microbes and enzymes; and biochemical protection results from differential degradability of organic structures.

Chemical stabilization may result from association of OC compounds with mineral surfaces primarily in silt- and clay-sized particles (Sollins et al. 1996), but the mechanisms by which the different OM fractions adsorb onto mineral surfaces and the relationship between mineralogy and the chemistry of OM bound in organo-mineral associations are not yet fully understood.

## **1.2 Chemical protection of organic matter**

For the purposes of the research discussed, this chapter focuses on the mechanisms involved in chemical stabilization. The primary scope is to provide a comprehensive understanding of chemical stabilization of OC in subsoil, considering the following statements:


#### **1.3 Complexation of aluminum by organic compounds**

Aluminium is the third most abundant element in the Earth´s crust, occurring at about 8%, and is a main or secondary component of numerous minerals, especially silicates. The only

The Role of Aluminum-Organo Complexes in Soil Organic Matter Dynamics 21

Organic matter has been described to floculate with Al salts. Maison et al. (2000) described the existence of specific binding sites for Al for given structures or ligands within the OM composition. Those results suggested that the organic ligands present in the OM are

The chemical complexity of SOM, the heterogeneity of its distribution and the variations in size and decomposition rate create significant analytical problems and partly explain the current deficiency in our understanding of SOM chemistry and dynamics (Lehmann et al.

Spectroscopic techniques are powerful tools in environmental research and a growing field of research (Schulp et al. 2008; Scheckel et al. 2010). The momentum of synchrotron research is leading to a continuous success of synchrotron studies addressing complex environmental issues and moreover, it can be expected that regulations and policy decisions will

Fluorescence spectroscopy has the required sensitivity to characterize metal ion binding properties of organic matter and determine its micromolar complexing capacities, i.e. to allow differentiating the binding sites or the ligand types involved in the formation of metal-organo complexes (Ryan and Weber 1982). Besides, the fact that fluorescence differentiates free from bound ligand provides an excellent complement to other complexing capacity techniques which measure free metal ion, like anodic stripping voltammetry or ion selective electrode potentiometry. Thus, fluorescence spectroscopy has been probed as valuable for the analysis of complexes between humic materials and several metal ions. For instance, fulvic acid exhibits

**2. Spectroscopic analysis to determine the formation of aluminum-organo** 

**2.1 Ultraviolet spectrophotometric determination of aluminum-organic complexes**  Spectrophotometric titrations with Al(III) were carried out for gallic acid (Figure 3a) and salicylic acid (Figure 3b) to demonstrate the formation of the metal-organo complexes. UV−visible spectra were recorded for increasing concentrations of Al(III). A proportional decrease was observed for the absorbance at 220 and 270 nm for gallic acid (GA) and at 240 and 300 nm for salicylic acid (SA). The two isosbestic points (IUPAC 2007) confirmed the formation of the metal-organo complexes and are indicative of a transition between two

Several methods are available for examining aluminium interactions with natural organic ligand solutions. Spectroscopic approaches allow an accurate characterization of metalorganic complexes. Thus, ultraviolet, infrared, fluorescence and 13C NMR spectroscopy are used to evaluate the functional groups involved in binding, i.e. the aluminium-organic complexes. Fluorescence spectroscopy is well-known as a powerful technique useful for chemical characterization of humic acids while Fourier transform infrared spectroscopy (FTIR) can provide an insight into structural characteristics of complex organic macromolecules and allow typing organic molecules at the micrometer resolution. For instance, FTIR mapping have shown the location of organic C forms in relation to mineral

fluorescence that is quenched upon binding to a paramagnetic metal ion.

surfaces, and relevant information on microaggregate formation.

light absorbing species in all recorded spectra (Harrington et al. 2010).

**1.4 Methodological approaches to characterize aluminum-organic interactions** 

responsible for the distribution of metals.

increasingly rely on such techniques.

2010).

**complexes** 

stable ion, Al3+, is known to coordinate with oxygen-bearing ligands (Kabata-Pendias 2011). Metal ions in aqueous solution exist as aqua ions, where water molecules act as ligands, and coordinate to the metal ion via the oxygen donor atoms. Solution properties of Al are complex (Fig. 2), it is present as Al3+, Al(OH)2+ Al(OH2)+ at pH<5 but above pH 7.5 the dominant specie might be Al(OH)4 − (McBride 1994). Aluminum is a strongly hydrolyzing metal and relatively insoluble in the neutral pH range (6.0 to 8.0) (May et al. 1979). Under acidic (pH <6.0) or alkaline (pH >8.0) conditions, and/or in the presence of complexing ligands, the solubility of Al is enhanced, making it more available for biogeochemical transformations.

Fig. 2. Species distribution diagram (logarithmic) for Al(III) in aqueous solution.

The chemistry of Al in soils has been thoroughly evaluated (Sposito 1996) and highlighted as a major scientific problem, due to the worldwide concern about deforestation and acidic deposition and the resulting environmental impact.

The bioavailability and potential toxicity of Al in soils and waters are highly dependent on chemical interactions with natural organic matter. Solution Al (M3+, Fig. 1) is the most chemically and biologically available form, although this pool represents an extremely small fraction of total Al in the environment. Within the aqueous phase, Al may be associated with a variety of inorganic or organic ligands. The extent of complexation depends on the availability of soil/sediment Al, solution pH, concentrations of complexing ligands, ionic strength and temperature (Driscoll and Schecher 1990). Aqueous A1 may be redeposited to free soil/sediment pools, assimilated by living biomass or transported from the system (Figure 1).

Boudot et al. (1989) showed the direct protective effect of amorphous Al compounds against the mineralization of various associated organics. The results indicated that insoluble metallic hydroxides were responsible of capturing organic molecules, and therefore either preserving them from the access by soluble soil enzymes or preventing their movement to immobile enzymatic constituents associated with microbial cells, which would better account for a protective effect than chemical binding.

stable ion, Al3+, is known to coordinate with oxygen-bearing ligands (Kabata-Pendias 2011). Metal ions in aqueous solution exist as aqua ions, where water molecules act as ligands, and coordinate to the metal ion via the oxygen donor atoms. Solution properties of Al are complex (Fig. 2), it is present as Al3+, Al(OH)2+ Al(OH2)+ at pH<5 but above pH 7.5 the

metal and relatively insoluble in the neutral pH range (6.0 to 8.0) (May et al. 1979). Under acidic (pH <6.0) or alkaline (pH >8.0) conditions, and/or in the presence of complexing ligands, the solubility of Al is enhanced, making it more available for biogeochemical

(McBride 1994). Aluminum is a strongly hydrolyzing

TOT = 3.00 mM

Al(OH)3 Al(OH)4 −

OH<sup>−</sup>

Al(OH)3(cr)

−

TOT = 1.00 mM [Cl−]

Fig. 2. Species distribution diagram (logarithmic) for Al(III) in aqueous solution.

deposition and the resulting environmental impact.




Log Conc.


0

H<sup>+</sup>

account for a protective effect than chemical binding.

The chemistry of Al in soils has been thoroughly evaluated (Sposito 1996) and highlighted as a major scientific problem, due to the worldwide concern about deforestation and acidic

1234567

5+

Al(OH)2+

Al2(OH)24+

AlOH2+

Al3(OH)4

Al3+ Cl<sup>−</sup>

pH

The bioavailability and potential toxicity of Al in soils and waters are highly dependent on chemical interactions with natural organic matter. Solution Al (M3+, Fig. 1) is the most chemically and biologically available form, although this pool represents an extremely small fraction of total Al in the environment. Within the aqueous phase, Al may be associated with a variety of inorganic or organic ligands. The extent of complexation depends on the availability of soil/sediment Al, solution pH, concentrations of complexing ligands, ionic strength and temperature (Driscoll and Schecher 1990). Aqueous A1 may be redeposited to free soil/sediment pools, assimilated by living biomass or transported from the system

Boudot et al. (1989) showed the direct protective effect of amorphous Al compounds against the mineralization of various associated organics. The results indicated that insoluble metallic hydroxides were responsible of capturing organic molecules, and therefore either preserving them from the access by soluble soil enzymes or preventing their movement to immobile enzymatic constituents associated with microbial cells, which would better

dominant specie might be Al(OH)4

[Al3+]

transformations.

(Figure 1).

Organic matter has been described to floculate with Al salts. Maison et al. (2000) described the existence of specific binding sites for Al for given structures or ligands within the OM composition. Those results suggested that the organic ligands present in the OM are responsible for the distribution of metals.

## **1.4 Methodological approaches to characterize aluminum-organic interactions**

The chemical complexity of SOM, the heterogeneity of its distribution and the variations in size and decomposition rate create significant analytical problems and partly explain the current deficiency in our understanding of SOM chemistry and dynamics (Lehmann et al. 2010).

Spectroscopic techniques are powerful tools in environmental research and a growing field of research (Schulp et al. 2008; Scheckel et al. 2010). The momentum of synchrotron research is leading to a continuous success of synchrotron studies addressing complex environmental issues and moreover, it can be expected that regulations and policy decisions will increasingly rely on such techniques.

Fluorescence spectroscopy has the required sensitivity to characterize metal ion binding properties of organic matter and determine its micromolar complexing capacities, i.e. to allow differentiating the binding sites or the ligand types involved in the formation of metal-organo complexes (Ryan and Weber 1982). Besides, the fact that fluorescence differentiates free from bound ligand provides an excellent complement to other complexing capacity techniques which measure free metal ion, like anodic stripping voltammetry or ion selective electrode potentiometry. Thus, fluorescence spectroscopy has been probed as valuable for the analysis of complexes between humic materials and several metal ions. For instance, fulvic acid exhibits fluorescence that is quenched upon binding to a paramagnetic metal ion.

## **2. Spectroscopic analysis to determine the formation of aluminum-organo complexes**

Several methods are available for examining aluminium interactions with natural organic ligand solutions. Spectroscopic approaches allow an accurate characterization of metalorganic complexes. Thus, ultraviolet, infrared, fluorescence and 13C NMR spectroscopy are used to evaluate the functional groups involved in binding, i.e. the aluminium-organic complexes. Fluorescence spectroscopy is well-known as a powerful technique useful for chemical characterization of humic acids while Fourier transform infrared spectroscopy (FTIR) can provide an insight into structural characteristics of complex organic macromolecules and allow typing organic molecules at the micrometer resolution. For instance, FTIR mapping have shown the location of organic C forms in relation to mineral surfaces, and relevant information on microaggregate formation.

## **2.1 Ultraviolet spectrophotometric determination of aluminum-organic complexes**

Spectrophotometric titrations with Al(III) were carried out for gallic acid (Figure 3a) and salicylic acid (Figure 3b) to demonstrate the formation of the metal-organo complexes. UV−visible spectra were recorded for increasing concentrations of Al(III). A proportional decrease was observed for the absorbance at 220 and 270 nm for gallic acid (GA) and at 240 and 300 nm for salicylic acid (SA). The two isosbestic points (IUPAC 2007) confirmed the formation of the metal-organo complexes and are indicative of a transition between two light absorbing species in all recorded spectra (Harrington et al. 2010).

The Role of Aluminum-Organo Complexes in Soil Organic Matter Dynamics 23

decrease in absorbance can be mostly related with the formation of an inner-sphere complex. The shift of the absorbance maximum at the highest concentrations of Al(III) can be only partially explained by the pH variation and might be largely related to the

**2.2 Luminiscence spectrophotometric determination of aluminum-organic complexes**  Fluorescence excitation-emission spectra were collected to characterize the formation of aluminium:gallic acid (Al:GA) complexes. Multidimensional fluorescence spectroscopy has been previously demonstrated to provide better characterization of metal binding to organic

GA 419

(a)

Al: GA 264

42

26

79

132

185

237

84

168

293

377

250 300 350 400 450 500

**Emission (nm)**

(b)

250 300 350 400 450 500

**Emission (nm)**

Fig. 4. Excitation-Emission spectra for gallic acid 50 μM (a) and Al:GA 1:1 (b).

compounds than traditional quenching at a single excitation-emission wavelength.

formation of outer-sphere complexes.

240

240

290

**Excitation (nm)**

340

1:1

390

290

**Excitation (nm)**

340

390

Fig. 3. Spectrophotometric titration of a) gallic acid 50 μM and b) salicylic acid 50 μM with Al(III).

Titrations were carried out at a pH range 3.91–4.25, which corresponds with a fraction of GA dissociated of 86-92%, 90-94% for SA and 7–13% hydrolization of Al(III). Therefore the

(a)

200 250 300 350

**lambda (nm)**

0.0

0

1

2

**Absorbance**

3

4

0.5

1.0

1.5

**Absorbance**

2.0

2.5

(b)

200 250 300 350

**lambda (nm)**

Titrations were carried out at a pH range 3.91–4.25, which corresponds with a fraction of GA dissociated of 86-92%, 90-94% for SA and 7–13% hydrolization of Al(III). Therefore the

Fig. 3. Spectrophotometric titration of a) gallic acid 50 μM and b) salicylic acid 50 μM with

Al(III).

decrease in absorbance can be mostly related with the formation of an inner-sphere complex. The shift of the absorbance maximum at the highest concentrations of Al(III) can be only partially explained by the pH variation and might be largely related to the formation of outer-sphere complexes.

## **2.2 Luminiscence spectrophotometric determination of aluminum-organic complexes**

Fluorescence excitation-emission spectra were collected to characterize the formation of aluminium:gallic acid (Al:GA) complexes. Multidimensional fluorescence spectroscopy has been previously demonstrated to provide better characterization of metal binding to organic compounds than traditional quenching at a single excitation-emission wavelength.

Fig. 4. Excitation-Emission spectra for gallic acid 50 μM (a) and Al:GA 1:1 (b).

The Role of Aluminum-Organo Complexes in Soil Organic Matter Dynamics 25

Al:Glu 0:1 334

(a)

Al:Glu 1:1 470

37

46

140

235

329

423

100

167

234

300

250 300 350 400 450 500

**Emission (nm)**

240

240

290

**Excitation (nm)**

340

390

290

**Excitation (nm)**

340

390

(b)

250 300 350 400 450 500

**Emission (nm)**

equilibrate/stabilise the acidity. For the determination of pH a mixture of soil and 1 M KCl solution in a 1:5 ratio was used. The pH value was 6.0 ± 0.5. Subsamples of the artificial soil

Fig. 6. Excitation-Emission spectra for glucose 1mM (a) and Al:Glu 1:1 (b).

Aluminum complexation with GA varied the fluorescence fingerprinting and therefore provided information on the types of metal-organic complexes, which depended on Al(III) concentration in solution (Ohno et al. 2008). Spectral variations confirmed the formation of metal-organo complexes (Figure 4) but furthermore suggested the formation of at least two different types of complexes (Figure 4b).

Similarly, for the titration of glucose (Glu) with Al(III) a shift in the maximum of fluorescence was determined, as well as an increase in the intensity of the signal for Al:Glu ratios up to 1:1, as depicted for the excitation-emission at 240 nm (Figure 5).

Fig. 5. Excitation-Emission spectra for glucose 1mM (a) and Al:Glu 1:1 (b).

The multidimensional spectra of Glu and Al:Glu 1:1 (Figure 6) provides a better portrayal of the complexation of Al with Glu. The tendency of Al(III) ions to displace aliphatic hydroxyl protons from various ligands in which they are in positions favourable for metal ion coordination, as might be the anomeric carbon, was already described by Motekaitis and Martell (1984).

Those results are particularly relevant to explain the stability of organic matter. Bartoli and Philippy (1990) described association of exchangeable Al with organic matter rich in polysaccharides as one of two major types of organo-mineral associations responsible for aggregate stability. Moreover, they described such aggregates to be easily disrupted by Al/Na exchange, a process that might partially explain the effect of sodicity in the increase of organic matter solubility in salt-affected soils.

The turnover of soil organic matter pools is a slow process, essential for soil structure and to promote soil biodiversity and support phytoremediation (Burke et al. 1995). Thus, soil addition with organic materials might decrease water run-off and erosion potential of topsoil.

Artificial soils were created according to the OECD guidelines (2010): 20% kaolinite, 70% sand, ≤ 1% CaCO3 and 10% Pahokee peat were mixed, moistened with deionised water at field capacity and autoclaved. Soils were equilibrated for 1 week in order to

Aluminum complexation with GA varied the fluorescence fingerprinting and therefore provided information on the types of metal-organic complexes, which depended on Al(III) concentration in solution (Ohno et al. 2008). Spectral variations confirmed the formation of metal-organo complexes (Figure 4) but furthermore suggested the formation of at least two

Similarly, for the titration of glucose (Glu) with Al(III) a shift in the maximum of fluorescence was determined, as well as an increase in the intensity of the signal for Al:Glu

ratios up to 1:1, as depicted for the excitation-emission at 240 nm (Figure 5).

Fig. 5. Excitation-Emission spectra for glucose 1mM (a) and Al:Glu 1:1 (b).

of organic matter solubility in salt-affected soils.

The multidimensional spectra of Glu and Al:Glu 1:1 (Figure 6) provides a better portrayal of the complexation of Al with Glu. The tendency of Al(III) ions to displace aliphatic hydroxyl protons from various ligands in which they are in positions favourable for metal ion coordination, as might be the anomeric carbon, was already described by Motekaitis and

300 350 400 450 500 550

**Absorbance (nm)**

Those results are particularly relevant to explain the stability of organic matter. Bartoli and Philippy (1990) described association of exchangeable Al with organic matter rich in polysaccharides as one of two major types of organo-mineral associations responsible for aggregate stability. Moreover, they described such aggregates to be easily disrupted by Al/Na exchange, a process that might partially explain the effect of sodicity in the increase

The turnover of soil organic matter pools is a slow process, essential for soil structure and to promote soil biodiversity and support phytoremediation (Burke et al. 1995). Thus, soil addition with organic materials might decrease water run-off and erosion potential of

Artificial soils were created according to the OECD guidelines (2010): 20% kaolinite, 70% sand, ≤ 1% CaCO3 and 10% Pahokee peat were mixed, moistened with deionised water at field capacity and autoclaved. Soils were equilibrated for 1 week in order to

different types of complexes (Figure 4b).

0

100

200

300

**Fluorescence Intensity**

400

500

600

Martell (1984).

topsoil.

Fig. 6. Excitation-Emission spectra for glucose 1mM (a) and Al:Glu 1:1 (b).

equilibrate/stabilise the acidity. For the determination of pH a mixture of soil and 1 M KCl solution in a 1:5 ratio was used. The pH value was 6.0 ± 0.5. Subsamples of the artificial soil

The Role of Aluminum-Organo Complexes in Soil Organic Matter Dynamics 27

(a)

250 300 350 400 450 500

102

102

305

508

712

915 1017

204

408

612

815 1020

**Emission (nm)**

(b)

250 300 350 400 450 500

**Emission (nm)**

Fig. 7. Excitation-Emission spectra for pore water extractions from artificial soils added with

glucose 1mM (a) or Al(III) complexes Al:Glu 1:1 (b).

240

240

290

**Excitation (nm)**

340

390

290

**Excitation (nm)**

340

390

were added with a solution of glucose 1 mM or an Al(III) complex Al:Glu 1:1. The soil solution was normalized to a UV-Absorbance 0.2 at 254 nm by adequate dilutions and analyzed by luminescence spectroscopy. Emission spectra were recorded over the range of 250 to 500 nm at a constant excitation wavelength of 240 nm. Relative fluorescence intensity was based on a unitless reciprocal to the gain used to normalize each emission spectrum and was expressed in arbitrary units (Plaza et al. 2006).

Despite the chemical diversity of dissolved organic matter (DOM), similar steady state fluorescence spectra has been observed for DOM excitation –emission matrices (EEM), indicating the presence of common pool of fluorophores (Cory and McKnight 2005). Thus, EEM spectroscopy provides the sensitivity to examine subtle changes in dissolved organic matter (DOM) fluorescence and provide insight into alteration of DOM pool composition (Coble et al. 1998). Thus, fingerprinting of soil organic pools allows a thorough characterization of the organic matter in a given soil and provides a relevant tool to evaluate the alterations due to a particular soil addition with organic materials.

Otherwise, metal ion mobility and bioavailability in soil is extensively controlled by soil organic matter (Sposito 1996), and especially humic substances, of which humic acids (HAs) and fulvic acids (FAs) represent two major fractions. These materials are the most important soil organic ligands in terms of metal binding capacity due to their large content of oxygenated functional groups, including various carbonyl, carboxyl, phenolic, alcoholic and enolic hydroxyl groups (Tipping et al. 2002).

Soil addition with Al:Glu 1:1 resulted in a significant increase of the visible humic-like organic matter pool (Ex/Em 320-360/400-460) (Figure 7) compared to soil added with Glu.

This substantial increase in the fraction of UV and visible humic-like organic matter suggest that glucose complexation with Al(III) hampers the degradation of such labile compound, increasing the pool of highly stable, low degradation rate organic matter. Moreover, the increase in fluorescence intensity confirms the presence of a metal-organo complex in the solution Al:Glu 1:1. These results are consistent with previous results describing the preferential binding of aluminium to polysaccharides (Masion et al. 2000). The authors attempted to describe a model structure where cellulose is partially responsible for the locally ordered arrangement of Al atoms. Because of the complex chemical nature of humic and fulvic materials, which represent up to 70% of DOC and are major components of natural organic matter, these results are of major relevance for better understanding organic matter structure at a molecular level. Currently, little is known about stabilization of organic matter by formation of insoluble Al–OM complexes, which has been already described as a major pathway for the formation of stable soil OM (Scheel et al. 2007).

## **3. Future perspectives: The role of aluminum-organo complexes on carbon speciation, a health benchmark in salt-affected soils**

Soil health is the balance of inherent soil properties (physical, chemical and biological), environmental conditions and management practices. Soil health is measured in terms of individual ecosystem services provided relative to a specific benchmark: e.g. microbial activity, CO2 release, or humus level.

were added with a solution of glucose 1 mM or an Al(III) complex Al:Glu 1:1. The soil solution was normalized to a UV-Absorbance 0.2 at 254 nm by adequate dilutions and analyzed by luminescence spectroscopy. Emission spectra were recorded over the range of 250 to 500 nm at a constant excitation wavelength of 240 nm. Relative fluorescence intensity was based on a unitless reciprocal to the gain used to normalize each emission spectrum and

Despite the chemical diversity of dissolved organic matter (DOM), similar steady state fluorescence spectra has been observed for DOM excitation –emission matrices (EEM), indicating the presence of common pool of fluorophores (Cory and McKnight 2005). Thus, EEM spectroscopy provides the sensitivity to examine subtle changes in dissolved organic matter (DOM) fluorescence and provide insight into alteration of DOM pool composition (Coble et al. 1998). Thus, fingerprinting of soil organic pools allows a thorough characterization of the organic matter in a given soil and provides a relevant tool to evaluate

Otherwise, metal ion mobility and bioavailability in soil is extensively controlled by soil organic matter (Sposito 1996), and especially humic substances, of which humic acids (HAs) and fulvic acids (FAs) represent two major fractions. These materials are the most important soil organic ligands in terms of metal binding capacity due to their large content of oxygenated functional groups, including various carbonyl, carboxyl, phenolic, alcoholic and

Soil addition with Al:Glu 1:1 resulted in a significant increase of the visible humic-like organic matter pool (Ex/Em 320-360/400-460) (Figure 7) compared to soil added with

This substantial increase in the fraction of UV and visible humic-like organic matter suggest that glucose complexation with Al(III) hampers the degradation of such labile compound, increasing the pool of highly stable, low degradation rate organic matter. Moreover, the increase in fluorescence intensity confirms the presence of a metal-organo complex in the solution Al:Glu 1:1. These results are consistent with previous results describing the preferential binding of aluminium to polysaccharides (Masion et al. 2000). The authors attempted to describe a model structure where cellulose is partially responsible for the locally ordered arrangement of Al atoms. Because of the complex chemical nature of humic and fulvic materials, which represent up to 70% of DOC and are major components of natural organic matter, these results are of major relevance for better understanding organic matter structure at a molecular level. Currently, little is known about stabilization of organic matter by formation of insoluble Al–OM complexes, which has been already described as a major pathway for the formation of stable soil OM (Scheel

**3. Future perspectives: The role of aluminum-organo complexes on carbon** 

Soil health is the balance of inherent soil properties (physical, chemical and biological), environmental conditions and management practices. Soil health is measured in terms of individual ecosystem services provided relative to a specific benchmark: e.g. microbial

**speciation, a health benchmark in salt-affected soils** 

activity, CO2 release, or humus level.

was expressed in arbitrary units (Plaza et al. 2006).

enolic hydroxyl groups (Tipping et al. 2002).

Glu.

et al. 2007).

the alterations due to a particular soil addition with organic materials.

Fig. 7. Excitation-Emission spectra for pore water extractions from artificial soils added with glucose 1mM (a) or Al(III) complexes Al:Glu 1:1 (b).

The Role of Aluminum-Organo Complexes in Soil Organic Matter Dynamics 29

will be inactive. Thus, another major goal for future research is to relate soil respiration rates

Aluminium complexation with organic compounds plays a fundamental role in the dynamics of organic matter. Spectrometric analysis can help demonstrating the formation of complexes of Al (III) with organic compounds, but also identifying the types of metalorganic complexes in aqueous solution, which largely depends on metal concentration. Spectra alteration for the complexation of Al with gallic acid, salicylic acid and glucose, confirmed the formation of metal-organo complexes. Structural changes to organic molecules due to metal complexation might alter their biological transformation and similar

A comprehensive characterization of soil organic matter properties is central to soil health. The increasing concern about salt-affected soils and the necessity of developing feasible preventive and remediation strategies demand a better knowledge on carbon dynamics, particularly for the management of agricultural soils. Therefore, characterization of metalorgano complexes in the soil system constitutes a major research goal for soils scientist. Moreover, a multidisciplinary approach is required for such knowledge to truly contribute

Maria C. Hernandez-Soriano thanks the Fulbright program and the Spanish Ministry of

Baldock JA, Skjemstad JO (2000) Role of the soil matrix and minerals in protecting natural organic materials against biological attack. Organic Geochemistry 31 (7-8):697-710 Bartoli F, Philippy R (1990) Al-organic matter associations as cementing substances of

Batjes NH (1996) Total carbon and nitrogen in the soils of the world. Eur J Soil Sci 47 (2):151-

Boudot JP, Bel H, Brahim A, Steiman R, Seigle-Murandi F (1989) Biodegradation of synthetic

Burke IC, Lauenroth WK, Coffin DP (1995) Soil organic matter recovery in semiarid

Coble PG, Del Castillo CE, Avril. B (1998) Distribution and optical properties of CDOM in

Cory RM, McKnight DM (2005) Fluorescence spectroscopy reveals ubiquitous presence of

ratios. Soil Biology and Biochemistry 21 (7):961-966

Topical studies in oceanography 45:2195-2223

(21):8142-8149. doi:Doi 10.1021/Es0506962

Applications 5 (3):793-801

ochreous brown soil aggregates: Preliminary examination. Soil Science 150 (4):745-

organo-metallic complexes of iron and aluminium with selected metal to carbon

grasslands: implications for the conservation reserve program. Ecological

the Arabian Sea during the 1995 Southwest Monsoon. Deep-sea research Part 2

oxidized and reduced quinones in dissolved organic matter. Environ Sci Technol 39

and biological transformation of organic matter to organomineral associations

processes can be expected to control soil organic matter turnover.

to the preservation of organic matter equilibrium in soil.

Education for a postdoctoral fellowship (FMECD-2010).

**4. Conclusions** 

**5. Acknowledgment** 

**6. References** 

751

163

A healthy soil is productive, sustainable and profitable. In general, a healthy soil presents the following characteristics which promote the health of plants, animals and humans while also maintaining environmental quality:


Among these properties, knowledge about soil organic matter (SOM) properties is central to soil health. The optimal level of SOM for any given soil is one which supports the functional capacity of the soil to hold and supply plant available water, store plant nutrients, provide energy for soil fauna, improve crop/biomass yields, and moderate net greenhouse gas emissions. Decomposition of organic matter (OM) regulates the flow of energy and nutrients in soil. It plays a key role in C, N, S and P cycling and also acts to improve soil structure. Agricultural practices and plant inputs influence both the quantity and quality of SOM, which in turn directly impacts on soil productivity and the ability of soil to recover from stress (soil resilience). For instance, the increasing use of wastewater for irrigation purposes in areas of southern Europe introduces surfactants in the soil system. Surfactants present in wastewater can have side-effects such as the increase of soil sodicity. A study conducted for a collection of calcareous soils correlated surfactants effect with soil properties, and additionally the effect of some amendments commonly used in agriculture was evaluated. Increasing sodicity and calcium sequestration were the mechanism driving trace metal release from soil treated with anionic surfactants (Hernandez-Soriano et al. 2011).

The amount of OM in a soil is used as an indicator of the potential sustainability of a system. Salt-affected soils present low OM contents due to poor plant growth, dispersion, erosion and leaching. Altered physical, biological and chemical properties directly impact SOM dynamic, particularly the active pool (rapid turnover). Thus, disruption of soil aggregates, changes in OM distribution and increased solubility of OM in the presence of Na increase SOM mineralization (Nelson et al. 1996; Oster and Shainberg 2001), while salinity alters soil microbial biomass (Rietz and Haynes 2003; Wong et al. 2008). Moreover, the opposing saline and sodic processes and the effects of OM result on conflicting effects of OM addition to saline and sodic soils. Currently, our understanding about carbon stocks and fluxes in saline and sodic soils is still limited while data related to carbon dynamics in such soils is contradictory (Wong et al. 2010).

A better understanding of the mechanisms of chemical protection of organic matter will contribute to protect and ameliorate soils health. This knowledge can be achieved by the accomplishment of the following goals:


The organomineral associations provide an alteration of the molecular structure of organic matter (organic compounds) such that enzymes for decomposing specific functional groups will be inactive. Thus, another major goal for future research is to relate soil respiration rates and biological transformation of organic matter to organomineral associations

## **4. Conclusions**

28 Soil Health and Land Use Management

A healthy soil is productive, sustainable and profitable. In general, a healthy soil presents the following characteristics which promote the health of plants, animals and humans while

Among these properties, knowledge about soil organic matter (SOM) properties is central to soil health. The optimal level of SOM for any given soil is one which supports the functional capacity of the soil to hold and supply plant available water, store plant nutrients, provide energy for soil fauna, improve crop/biomass yields, and moderate net greenhouse gas emissions. Decomposition of organic matter (OM) regulates the flow of energy and nutrients in soil. It plays a key role in C, N, S and P cycling and also acts to improve soil structure. Agricultural practices and plant inputs influence both the quantity and quality of SOM, which in turn directly impacts on soil productivity and the ability of soil to recover from stress (soil resilience). For instance, the increasing use of wastewater for irrigation purposes in areas of southern Europe introduces surfactants in the soil system. Surfactants present in wastewater can have side-effects such as the increase of soil sodicity. A study conducted for a collection of calcareous soils correlated surfactants effect with soil properties, and additionally the effect of some amendments commonly used in agriculture was evaluated. Increasing sodicity and calcium sequestration were the mechanism driving trace metal release from soil treated with anionic surfactants

The amount of OM in a soil is used as an indicator of the potential sustainability of a system. Salt-affected soils present low OM contents due to poor plant growth, dispersion, erosion and leaching. Altered physical, biological and chemical properties directly impact SOM dynamic, particularly the active pool (rapid turnover). Thus, disruption of soil aggregates, changes in OM distribution and increased solubility of OM in the presence of Na increase SOM mineralization (Nelson et al. 1996; Oster and Shainberg 2001), while salinity alters soil microbial biomass (Rietz and Haynes 2003; Wong et al. 2008). Moreover, the opposing saline and sodic processes and the effects of OM result on conflicting effects of OM addition to saline and sodic soils. Currently, our understanding about carbon stocks and fluxes in saline and sodic soils is still limited while data related to carbon dynamics in such soils is

A better understanding of the mechanisms of chemical protection of organic matter will contribute to protect and ameliorate soils health. This knowledge can be achieved by the

• To characterize the specific binding mechanisms in organomineral associations using

• To characterize the composition of the organic matter associated with minerals and/or ions and determine molecular-level changes in soil Fe and Al species for relevant

The organomineral associations provide an alteration of the molecular structure of organic matter (organic compounds) such that enzymes for decomposing specific functional groups

also maintaining environmental quality:

4. Enhanced soil biological function 5. Supports productive land uses

(Hernandez-Soriano et al. 2011).

contradictory (Wong et al. 2010).

scenarios.

accomplishment of the following goals:

high-resolution spectroscopic techniques;

2. Soil fertility is balanced

1. Soil organic matter equilibrium maintained

6. Enhances environmental & community health and well-being

3. Water entry, storage & supply optimised

Aluminium complexation with organic compounds plays a fundamental role in the dynamics of organic matter. Spectrometric analysis can help demonstrating the formation of complexes of Al (III) with organic compounds, but also identifying the types of metalorganic complexes in aqueous solution, which largely depends on metal concentration. Spectra alteration for the complexation of Al with gallic acid, salicylic acid and glucose, confirmed the formation of metal-organo complexes. Structural changes to organic molecules due to metal complexation might alter their biological transformation and similar processes can be expected to control soil organic matter turnover.

A comprehensive characterization of soil organic matter properties is central to soil health. The increasing concern about salt-affected soils and the necessity of developing feasible preventive and remediation strategies demand a better knowledge on carbon dynamics, particularly for the management of agricultural soils. Therefore, characterization of metalorgano complexes in the soil system constitutes a major research goal for soils scientist. Moreover, a multidisciplinary approach is required for such knowledge to truly contribute to the preservation of organic matter equilibrium in soil.

## **5. Acknowledgment**

Maria C. Hernandez-Soriano thanks the Fulbright program and the Spanish Ministry of Education for a postdoctoral fellowship (FMECD-2010).

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**Part 2** 

**Land Use Impact on Soil Quality**

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