Previous PageTable of ContentsNext Page

Carbon mineralization in coastal sandy tracts under semi dry rice production

Kaleeswari, R.K.1; R. Kalpana1 and P. Devasenapathy1

Keywords: Ipomea cornea composted, rice production, semi-arid climate, sandy soils

Abstract

Experiments were conducted during 2002-2004 to explore the possibility of recycling a common weed in the study area, (East costal region in Southern peninsular India) Ipomea cornea as green manure for semi dry rice. A laboratory based incubation study was conducted in year 2002. The incubation study revealed that Ipomea cornea composted with poultry manure recorded lower CO2 evolution and wider C:N ratio as compared to Ipomea cornea composted with cattle manure. Field experiments were conducted for three years (2002-2004) in coastal sandy tracts in Ramanathapuram District, Tamil Nadu State of India with rice-rice cropping sequence under semi-dry condition to study the impact of Ipomea cornea compost on rice yield and soil organic carbon status. The field study indicated that the application of Ipomea cornea composted with poultry manure recorded the highest rice grain yield and soil organic carbon status as compared to Ipomea cornea composted with cattle manure. During the crop growing period, the soil organic matter status and soil temperature were negatively correlated. With increase in soil organic matter status a decrease in soil temperature was observed.

Introduction

In general in agro-ecosystems, soils receive considerable carbon inputs from a variety of sources including leaf fall, stubbles, roots and root exudates as well as through external sources including farmyard manure and compost. The study area, Ramanathapuram District of Tamil Nadu State, India located in east coastal area of southern peninsular India at longitude (E) 78º10′-79º27′ and latitude (N) 9º05′-9º56′. This district covering a geographical area of 408,957 ha. The semi-dry system of rice cultivation is mainly confined to tracts that depend on rains and have no supplementary irrigation facilities. In this semi-dry system part of the rice crop’s life cycle passes under aerobic conditions and part under anaerobic conditions. In the conventional rice cultivation practiced in irrigated areas, rice crops’ l_fe cycle occurs completely under anaerobic condition. The amount and quality of organic carbon are crucial factors influencing soil productivity. The endemic deficiency of organic matter in tropical sandy soils particularly those under the influence of arid and semi-arid climates are a major factor contributing to their low productivity. Experiments were conducted to explore the possibility of recycling a common weed in the study area, Ipomea cornea as green manure for semi dry rice.

Materials and methods

In 2002, under laboratory conditions, 5 kg of the green leaves of Ipomea cornea was composted with cattle manure and poultry manure @ 0.625, 1.25, 1.88 and 2.50 kg anaerobically for 30 days. The matured compost was obtained at the end of composting period (30 days). The nutrient contents of the organic materials composted are furnished in Table 1. In summary, the green leaves of Ipomea cornea harvested from wastelands near the experimental site were chopped and mixed with cattle/poultry manures and wetted with deionized water to bring the mix to 60 percent moisture content. The moisture content was maintained at 60 percent. Since the composting was done under anaerobic condition, the mix was not turned. The ‘mix’ was subsequently maintained at this anaerobic condition. A total of nine treatments were replicated for five times. The CO2 C evolution was measured at weekly intervals. (Bundy and Bremner, 1972). Separate containers were kept for each of the 5 sampling intervals so that once opened for CO2 C measurement, the container could be discarded.

Field experiments were conducted for three years (2002-2004) in coastal sandy tracts with rice-rice cropping sequence under semi-dry condition. The experimental soil (Typic Tropaquept) was alkaline in soil reaction (soil: water ratio 1:2) (pH 8.7), low in N (Subbiah and Asija, 1956) (90 kg ha), P (Olsen et al., 1954) (4.2 kg ha-1) and high in available K (Stanford and English, 1949) (324 kg ha-1. The initial soil organic carbon content was 1.2 g kg-1. The Ipomea cornea compost obtained from another batch of composting was applied basally (10 kg/plot) as per the treatment schedule. The experimental plot size was 5 × 4 m2. The design of the experiment was a randomized block design with three replicates. The oxidizable soil organic carbon content was measured (Walkely and Black, 1934) in various growth stages of rice, tillering, panicle initiation, flowering and harvest stages. At harvest stage, rice grain and straw yields and soil temperature were recorded.

Table 1. Nutrient contents of manures (mg g-1 of dry matter) used in the Study (Mean values)

Nutrients

Cattle manure

Poultry manure

Ipomea cornea

N 32.5 45.0

11.6

P 7.0 16.5

3.8

K 16.0 18.5

3.1

Ca 6.5 43.0

1.2

Mg 6.5 5.5

3.8

S 3.5 5.5

2.7

Organic carbon

112 238

601

Organic matter

193 410

1,036

Result and discussion

Incubation Experiment CO2 C evolution

Rapid mineralization followed by a steady decline in the rate of mineralization with time was observed. Initially, the mineralization was faster; with increase in the period of composting, there was a steady decline in the mineralization rate. The exponential nature of carbon mineralization from soil organic matter and added plant residues was previously reported by Vanlauwe et al., (1994). At all sampling intervals, the lowest amount of C was mineralized from poultry manure and the highest from cattle manure. The pattern of C mineralization from Ipomea cornea compost was similar to that of the control soil from fourth week after incubation onwards; indicating that most of the C added through compost had been mineralized within four weeks of incubation (Figure 1). High rates of CO2 C evolution from the Ipomea cornea cattle manure compost immediately after incubation was noticed. This could be due to the presence of easily decomposable organic compounds in the cattle manure as compared to less easily decomposable organic compounds in the poultry manure. Poultry manure contains large amounts of CaCO3, struvite and other basic compounds (Bril and Solomons, 1990). Low level of decomposition in Ipomea cornea-poultry manure compost could be attributed to high con­centration of Ca and neutralization of organic acids and H+ by Ca and buffering reactions (Mahimairaja et al., 1995).

Table 2. Estimated quantity (kg ha-1) of nutrients added to the soil through the manures evaluated in this study

Treatments (t ha-1)

Amount of cattle/poultry Nutrients added through manures (kg ha-1)

 

  N P K
Cattle manure        

12.5% of RD*

0.625

20.31

4.38

10.00

25.0% of RD

1.250

40.63

8.75

20.00

37.5% of RD

1.875

60.94

13.13

30.00

50.0% of RD

2.500

81.25

17.50

40.00

Poultry manure

       

12.5% of RD*

0.625

28.13

10.31

11.56

25.0% of RD

1.250

56.25

20.63

23.13

37.5% of RD

1.875

84.38

30.94

34.69

50.0% of RD

2.500

112.50

41.25

46.25

(*RD = Recommended dose-5 t ha-1)

Mangement of Tropical Sandy Soil for Sustainable Agriculture

Figure 1. Cumulative CO2-C mineralization (mg kg-1) in the compost

Field Experiment

Oxidizable soil organic carbon content

At all stages of crop growth, significant improvements in oxidizable soil organic carbon content were observed in the Ipomea cornea-poultry manure compost treatments as compared to in the control and Ipomea cornea-cattle manure compost treatments. Highest oxidizable soil organic carbon content (4.30 g C kg1) was recorded for the Ipomea cornea-poultry manure (50% RD) compost treatment (Table 3). Many studies have revealed a direct linear relationship between soil organic carbon storage and gross annual C input to soil (Halvin et al., 1990; Paustian et al., (1992). With increase in the level of Poultry manure (50% RD) used in the compost, Oxidizable soil organic carbon content was increased.

Table 3. Oxidizable soil organic carbon in crop growing period (g kg"1 soil)

Treatments

Tillering

Panicle Initiation

Flowering

Harvest

Cattle manure

       

12.5% of RD

1.4 1.6 1.7

1.9

25.0% of RD

1.7

2.0

2.2

2.5

37.5% of RD

1.9

2.3

2.6

3.0

50.0% of RD

2.3

2.5

2.8

3.1

Poultry manure

       

12.5% of RD

1.6

2.0

2.2

2.5

25.0% of RD

2.1

2.3

2.6

3.2

37.5% of RD

2.5

2.7

2.9

3.4

50.0% of RD

2.8

3.3 3.6

4.3

Yield of rice

Application of Ipomea cornea-poultry manure compost (37.5% RD) recorded higher grain (3,550 kg ha1) and straw yields (4,260 kg ha1) which was on par with the application of Ipomea cornea-poultry manure compost (50% RD) (Table 4). This could be due to the higher amount of CaC03 in the poultry manure. Calcium in poultry manure exchange with Na in the soil exchange complex, thereby reduce the ill effects of Na on soil and plant. The experimental site was alkaline in soil reaction. Despite a higher nutrient content in the poultry manure as compared to cattle manure the presence of CaC03 in poultry manure could have favourable effect on the experimental soil. Low yield in Ipomea cornea-cattle manure compost applied plots could be due to the lesser amounts of nutrients added through cattle manure.

Soil Temperature

At harvest stage a negative linear correlation between soil temperature and soil organic matter status was observed (Figure 2). As soil organic matter status increased, decrease in soil temperature was noticed.

Table 4. Yield (Kg ha1) as influenced by the incorpora­tion of organics

Treatments

Grain

Straw

Cattle manure

   

12.5% of RD

2,320

2,784

25.0% of RD

2,574

3,063

37.5% of RD

3,265

3,918

50.0% of RD

3,097

3,685

Poultry manure

   
12.5% of RD

2,725

3,270

25.0% of RD

3,287

3,912

37.5% of RD

3,550

4,260

50.0% of RD

3,425

4,110

SEd

137

164

CD (P:0.05)

325

389

Conclusions

Ipomea cornea is one of the most rapidly spreading weeds in southern peninsular India. It is fast encroaching cultivated lands, water reservoirs and waste lands. A significant amount of time, effort and money has been used for its eradication. Recycling of this weed Ipomea cornea could serve dual purpose of its eradication and serving as a better organic material. Ipomea cornea could be composted with animal manures and used as manure for semi-dry rice cultivation. Between cattle manure and poultry manure, Ipomea cornea composted with poultry manure recorded lower C02 evolution, wider C:N ratio and higher rice yield and organic carbon status.

References

Bril and Solomons, 1990. Chemical composition of animal manure: A modeling approach. Neth. J. Agric. Sci, 38,333-351.

Bundy, L.G., and Bremner, J.M. 1972. A simple titrimetric method for the determination of inorganic carbon in soils. Soil Sci. Soc. Am. Proc. 36, 273-275.

Havlin, J.L., Kissel, D.E., Maddux, L.d., Classen, MM. and Long, J.H. 1990. Crop Rotation and tillage effects on soil organic carbon and nitrogen. Soil Sci. Soc. Am. I 54, 448-456.

Mahimairaja, S., Bolan, N.S. and Hedley. M.J. 1995. Dissolution of phosphate rock during the composting of poultry manure: An incubation experiment. Fert. Res., 40, 93-104.

Olsen, S.R., Cole, C.L., Watanabe, F.S., and Dean, D.A. 1954. Estimation of available phosphorus in soils by the extraction with sodium bicarbonate, U.S.D.A., Circ. 939.

Paustian, K., Parton, W.J. and Persson, J. 1992. Modeling soil organic matter in organic amended and N fertilized long term plots. Soil Sci. Soc. Am. J, 56, 476-478.

Stanford, S. and English L. 1949. Use of flame photo meter in rapid soil test of K and Ca. Agron J., 41: 446-447.

Subbiah, B.V. and Asija, G.L. 1956. A rapid procedure for the estimation of available N in soils. Curr. Sci., 25: 259-260.

Vanlauwe, B., Dendooven, L. and Mer_kx, R.1994. Residue fractionation and Decomposition: the significance of the active fraction. Pl. Soil, 158, 263-274.

Walkley, A and C.A. Black. 1935. An examination of methods for determining organic carbon and N in soils. J. agric. Sci, 25, 598-609.


1 Department of Agronomy, TamilNadu Agricultural University, Coimbatore, TamilNadu, India

A decision support framework for the sustainable management of sandy soils

Moody, P.W.1; N.C. Vinh2; P.T. Cong3 and J. Legrand1

Keywords: decision support, sandy soils, soil management, hazard maps

Abstract

Sustainable agricultural systems are based on managing soils according to their capabilities and environmental constraints. A soil’s productive capacity is determined by key properties – some intrinsic (such as texture and structure), and others (such as pH and organic matter content) that can be manipulated by management. Knowledge of the intrinsic properties of a soil enables inferences to be made about properties such as CEC and pH buffer capacity. From these inferences, management strategies can be developed for maximising the productive capacity of the soil.

To facilitate the interpretation of properties of upland soils for identifying soil constraints and appropriate management strategies, a decision support framework ‘Soil Constraints and Management Package’ (‘SCAMP) has been developed. Utilising a database approach, inputs of basic soil data (both field and laboratory) are processed to output soil constraints to productivity (using alpha-numeric descriptors) and to identify appropriate management strategies. Where spatially referenced soil data are available, maps of constraints can be readily produced in a GIS.

SCAMP was applied to soil data from a Land Use Evaluation and Planning Study of three communes in Binh Thuan Province, Vietnam, and to a spatially referenced soil survey of the Herbert River catchment, Queensland, Australia. For the sandy soils in the Vietnamese study, SCAMP identified constraints of limited plant available water, low nutrient holding capacity, low pH buffer capacity and generally low nutrient fertility. Suggested management strategies included trickle/drip irrigation, organic amendments, addition of high activity clays, and regular liming. From the Australian data, attributes of the representative soil types of the Herbert River catchment were used to produce a map identifying areas of low pH, high acidification risk and low nutrient holding capacity. These two applications demonstrate the usefulness of SCAMP for linking soil data to management strategies for sustainable productivity at both plot and catchment scale. This link is often not made with the information collected in soil surveys.

Introduction

Sustainable agricultural systems are based on managing soils according to their capabilities and environmental constraints. The productive capacity of a soil is determined by key soil properties – some intrinsic (such as texture and structure), and others (such as pH and organic matter content) that can be manipulated by management. Knowledge of the intrinsic properties of a soil enables inferences to be made about derived properties such as CEC and pH buffer capacity. From these inferences, management strate_ies can be developed for maximising the productive capacity of the soil.

Inferring soil management practices from soil attributes is the principle on which the Fertility Capability Classification System (FCC) of Sanchez et al. (1981) is based, and using the FCC it has been shown that:

  1. soils in one FCC unit may belong to different categories in a classification system (orders, suborders, great groups, subgroups or families);
  2. the number of FCC units in a given area is much smaller than soil classification units, thereby simplifying interpretations; and
  3. making fertilizer recommendations based on FCC units is more profitable than making generalised recommendations.

To facilitate the interpretation of upland soil properties for identifying soil constraints and appropriate management strategies, a decision support framework ‘Soil Constraints and Management Package’ (‘SCAMP’) has been developed. Utilising an Access database, inputs of basic soil morphological, chemical and physical data are firstly used to identify intrinsic soil constraints to long-term productivity, and then to indicate management practices that will minimise the impacts of these constraints on productivity. SCAMP can be applied at plot, farm or catchment scale, and where geo-referenced soil data are available, maps of constraints can be produced.

SCAMP builds on the Fertility Capability Classification of Sanchez et al. (1981, 2003) by:

  1. considering a wider range of soil properties to determine constraints to productivity;
  2. utilising surrogates to infer several key soil properties; and
  3. including a temporal assessment of the pathways of water flow for identifying the risk of off-site nutrient movement.

The SCAMP Framework

SCAMP can be applied at three ‘levels’ of complexity, depending on the availability of key soil attribute data (Table 1). Level 1 uses only observations made on a soil ‘mini-pit’ in the field. Level 2 utilises field observations and some simple field measurements. Level 3 utilises field observations and measurements and a range of diagnostic laboratory analyses. Soil management strategies that can be inferred from the SCAMP assessment become more comprehensive as the application level of SCAMP moves from Level 1 to Level 3.

Table 1. Attributes determined for each application level of SCAMP

SCAMP Level

Attributes

Level 1

Texture, colour, structure and consistence, drainage class, permeability class, slope, signs of erosion

Level 2

Level 1 plus field pH, field EC, dispersion class, infiltration rate

Level 3

Level 2 plus organic C, ECEC, P buffer capacity, pH buffer capacity, plastic limit

Briefly, Level 1 attributes are recorded for a representative ‘mini-pit_rsquo; approximately 15 cm square and 50 cm deep. Field texture, soil structure and soil consistence are described using established nomenclature (e.g., Euroconsult 1989, McDonald et al. 1990) and colour can either be described using the Munsell system, or more simply as ‘black’, ‘white’, ‘red’, ‘yellow’, ‘brown’ or ‘gleyed/grey’. Permeability class (rate of water movement into the profile) and drainage class (rate of water movement through the profile) are rated from a consideration of structure and pores (permeability) and texture and the presence and persistence of a watertable (drainage) as indicated by mottles/gleying in the ‘mini-pit’ (McDonald et al. 1990). Level 2 attributes are also determined in the field, and involve measurements using hand held pH and EC meters, with dispersion class based on the behaviour of aggregates placed in water (Emerson 1967), and infiltration rated according to the time taken for a known volume of water to enter the soil from a plastic ring inserted into the soil surface. Level 3 attributes are determined in the laboratory following standard analytical methods.

The first SCAMP descriptor of a soil is the texture class - either sandy (S), loamy (L) or clayey (C ), of the plough layer (generally 0-20 cm) and the subsurface layer (20-50 cm). If there is a change in texture class, then the descriptor uses both classes (e.g., if texture class changes from S in the plough layer to L in the subsurface layer, then the soil is classified as SL). Following the texture class descriptor, the SCAMP framework then defines a series of ‘constraint’ descriptors based on criteria that use the values of the attributes listed in Table 1 (Table 2). Constraints are grouped under the general headings of: water regime constraints, soil pH and acidity constraints, cation constraints, clay fraction constraints, landscape constraints, and soil structural constraints.

The constraint descriptors follow the texture class descriptor to give a SCAMP notation for the soil. For example, many Ferralsols would be described as C a e i k (i.e. clayey, strongly acidic, low CEC, high P-fixation by iron, low K-reserves), many Vertisols as C d v b (i.e. clayey, ustic or aridic soil moisture regime, vertic, calcareous), whereas a young Fluvisol with no constraints is simply classified as L (loamy soil). The absence of constraints suggests no major limitations to productivity, other than nitrogen deficiency.

Applications of SCAMP

Two applications of SCAMP will be described, the first based on a land use evaluation and planning study of three communes in Vietnam, and the second based on the spatially-referenced soil survey of a catchment. In the former study, SCAMP was used to identify the constraints of the major soil types to sustainable production. This information was required to enable the establishment of field experiments to develop appropriate management strategies for dealing with these constraints. In the latter study, SCAMP was used to identify areas most at risk of rapid soil acidification and leaching loss of nutrients so that an awareness program could be undertaken with landholders to improve fertilizer management practices.

Table 2. SCAMP descriptors and the attributes used to determine the descriptors

SCAMP descriptor

Soil attributes

S, L, C (texture)

Field texture or clay content

d, d^ (ustic, aridic or torric moisture regime)

Period of subsurface dryness

g, g^ (aquic moisture regime)

Period of saturation or drainage class

a, a^ (acidity, Al toxicity)

Field pH or Al saturation

ar (acidification hazard from low to high)

Pedotransfer function using organic C and clay content to calculate

 

pH buffer capacity

b (calcareous)

Field pH

e (low nutrient retention)

Effective CEC

s, s^ (salinity)

Field or laboratory EC

n, n^ (sodicity)

Dispersion class or Na saturation

k (low K reserves)

Exchangeable K, nitric acid extractable K

i (P fixation)

P buffer capacity using a single point P sorption index

v (vertic properties)

Field observation or clay content and CEC/clay ratio

om (organic C rating from low to high)

Organic C content

vc (variable charge characteristics)

Soil pH in CaCl2 and KCl

Slope

Slope

er (erosion hazard)

Field observation

p (permeability rating from 1 to 4)

Field observation

d (drainage rating from 1 to 6)

Field observation

hs (hard setting)

Field texture and CEC/clay ratio

comp (compaction layer)

Field observation

Land Use Evaluation and Planning Study

A land use evaluation and planning study was undertaken on three communes in the Bac Binh District, Binh Thuan Province, Vietnam (Vinh 2001). A soil survey (1:50,000) had previously been carried _ut for the district, and this survey was used to select sites of the major soil types of the district in the three focus communes: Phan Hoa (agricultural land: 159 ha), Hoa Thang (agricultural land: 3,817 ha), Phan Tien (agricultural land: 201 ha) and Phan Thanh (agricultural land: 2,391 ha). At each site, a pit was dug and several soil attributes described. Soil samples were collected and analysed for some parameters in the laboratory. Attributes were then used to derive SCAMP descriptors.

Spatially Referenced Soil Survey

A spatially referenced soil survey (1:8,000) was available for the Herbert River Catchment, Queensland, Australia (Wood and Bramley 1996). The soil survey covered an area of 52,200 ha. Using the soil survey to select sites, soil samples were collected from representative profiles of the 24 major soil types of the catchment, and surface (0-20 cm) and subsurface (40-60 cm) samples were analysed in the laboratory for several chemical and physical attributes.

Results and Discussion

Land Use Evaluation and Planning Study

The SCAMP attributes derived from the field and laboratory data are presented in Table 3. Unfortunately limited information was available on field texture, permeability and drainage, and no data were available for P buffer capacity or clay content. This lack of data prevented a fuller assessment of the soil constraints.

For the soils classified as S (sandy), the following constraints are common across all sites (Table 3): d (ustic or aridic soil moisture regime), e (low nutrient retention), and k (low K supply). In addition, some of the sites had either a (acidity) or a^ (high Al saturation) constraints. Across all S soils, ar (acidification risk) was high or very high, and om (organic matter content) was low or medium.

These constraints indicate that the following management strategies could be implemented in these sandy soils for sustainable productivity:

Table 3. SCAMP descriptors for soils sampled in Bac Binh District, Vietnam

Sample No.

Soil type

Crops

SCAMP constraints

PH7a alluvial rice

C g^ a ar(low) s^ n^ k om(medium) hs

PH8 ? rice/beans

C a ar(moderate) n k om(medium) hs

HT3a sand

peanut, watermelon, Eucalypt, Acacia

S d ar(very high) e k om(low) comp

HT6a sand cashew

S d ar(very high) e k om(low)

PT1a alluvial rice

L g a^ ar(moderate) e n k om(medium_ hs

PT3 ? fruit trees

C ar(low) om(medium)

PTh1 sand cashew

S d a ar(high) e k om(low) comp

PTh2 sand cashew

S d ar(high) e k om(medium)

PTh3 alluvial rice

C g^ a ar(low) s^ n^ om(medium) hs

 

Mangement of Tropical Sandy Soil for Sustainable Agriculture

Figure 1. Map of soils in the Herbert River catchment that are strongly acid [pH(water)<5.5], with low nutrient holding capacity (ECEC <4 cmolc/kg soil), and high acidification risk (pH buffer capacity <1.5 kmol H+/kg.pH unit)

d: Trickle or drip irrigation will be required to grow crops during the dry season. Adding soil conditioners to improve the water holding capacity of the soil could be investigated.

e: CEC should be increased by addition of organic residues in association with a liming program to increase soil pH and therefore variable charge (e.g., Aitken et al. 1998) and/or high activity clays could be added to increase permanent charge (e.g., Noble et al. 2004).

k: Potassium fertilizers or organic amendments having a significant content of K will need to be applied. If applying K fertilizer to a soil with the e constraint, fertilizer applications should be split and only low rates applied on each occasion.

a or a^: Acid tolerant crops should be grown as a short term response to this constraint. For long term sustainability, a liming program should be commenced with regular monitoring of soil pH.

ar(high-very high): With an acid addition rate of 3.4 kmol H+/ha.yr [which occurs with many agricultural systems (Moody and Aitken 1997)], the pH(water) of the 0-20 cm layer of these soils will decrease by 1 pH unit in a period of less than 10 years. Strategies for countering this acidification would be a regular liming program and/or using agricultural systems with low net acid addition rates.

om(low-moderate): Improving levels of organic matter in these soils would improve nutrient supply, increase CEC, increase water holding capacity and increase pH buffer capacity.

It is noteworthy that many of the C (clayey) soils were poorly drained with salinity and/or sodicity constraints and often were compacted or hard setting (Table 3). The soil with least constraints (PT3) was also the only one supporting fruit trees such as lemon.

Spatially Referenced Soil Survey

In order to identify areas of the Herbert River catchment most at risk of rapid acidification and also loss of nutrients (cations, nitrate) by leaching, it was reasoned that soils with the following constraints would be most susceptible to these processes: S (sandy) and/or a with ar(high) (strongly acidic soils with a low pH buffer capacity), and/or e (low ECEC). A map was produced of soils with these constraints (Figure 1). It can be seen that large areas of strongly acidic soils with low ECEC occur along the riverbanks. A liming program will be requ_red to maintain the long term productivity of these soils and fertilizer (particularly nitrogen) management will need to minimise the potentially high risk of off-site nutrient movement.

Conclusion

The two applications described above demon­strate the usefulness of SCAMP for identifying soil constraints at plot and catchment scale. At plot scale, management strategies for addressing these constraints can be suggested and trialled. This information also allows the landholder to move from regional or district fertilizer recommendations and land management practices to soil-specific management, thus improving productivity, profitability and sustainability.

At catchment scale, constraints can be mapped to identify ‘hot spots’ which can be targeted for remedia­tion or awareness programs for the landholders. Catchment scale maps can also be used by government and catchment management authorities for the purposes of land use planning and risk assessment for such off-site issues as nutrient movement (with impacts on water quality) and on-site land degradation issues such as soil acidification.

Thus SCAMP can be used at different scales, making use of all available soil information such as field observations and soil survey data. SCAMP is multi-purpose, transparent and flexible, making it a very useful tool for obtaining the most from soil information.

Acknowledgments

We sincerely thank Dr Rod Lefroy, Dr Narong Chinabut, Dr Sathien Phimsarn and Mr Putu Wigena for their significant input into the prototype SCAMP at the workshop funded by The Crawford Fund, Australia.

We gratefully acknowledge funding support for the work presented in this paper from the Australian Centre for International Agricultural Research.

References

Aitken, R.L., Moody, P.W., and Dickson, T. 1998. Field amelioration of acidic soils in Southeast Queensland. I. Effect of amendments on soil properties. Australian Journal of Soil Research, 49, 627-637.

Emerson, W.W. 1967. A classification of soil aggregates based on their coherence in water. Australian Journal of Soil Research, 5, 47-57.

Euroconsult. 1989. Agricultural Compendium for Rural Development in the Tropics and Subtropics. Amsterdam, Elsevier, 731 p.

McDonald, R.C., Isbell, R.F., Speight, J.G., Walker, J., and Hopkins, M.S. 1990. Australian Soil and Land Survey Field Handbook, 2nd edition. Melbourne, Inkata Press, 190 p.

Moody, P.W., and Aitken, R.L. 1997. Soil acidification under some tropical agricultural systems. 1. Rates of acidification and contributing factors. Australian Journal of Soil Research, 35, 163-173.

Noble, A.D., Ruaysoongnern, S., Penning de Vries, F.W.T., Hartmann, C., and Webb, M.J. 2004. Enhancing the agronomic productivity of degraded soils in Northeast Thailand through clay-based Interventions. In: Seng, V. , Craswell, E., Fukai, S. and Fischer, K., ed., 2004. Water and Agriculture. Canberra, ACIAR Proceedings No. 116: 147-160.

Sanchez, P.A., Couto, W., and Buol, S.W. 1981. The Fertility Capability Soil Classification System: Interpretation, applicability and modification. Geoderma, 27, 283-309.

Sanchez, P.A., Palm, C.A., and Buol, S.W. 2003. Fertility capability soil classification: a tool to help assess soil quality in the tropics. Geoderma, 114, 157-185.

Vinh, N.C. 2001. Period Report on ACIAR-World Vision Joint Project: Technology for integrated rural development in Binh Thuan Province, Vietnam, Quarter 1, 2001. Hanoi, National Institute for Soils and Fertilizers, 17 p.

Wood, A.W., and Bramley, R.G.V. 1996. Soil survey – a tool for better fertilizer management in the Australian sugar industry. In: Wilson, J.R., Hogarth, D.M., Campbell, J.A. and Garside, A.L., ed., 1996. Sugarcane: Research towards efficient and sustainable pr_duction. Brisbane, CSIRO, 189-193.


1 Natural Resource Sciences, Department of Natural Resources and Mines, 80 Meiers Road, Indooroopilly Qld 4068, Australia, Phil.Moody@nrm.qld.gov.au
2 National Institute for Soils and Fertilizers, Tu Liem, Hanoi, Vietnam.
3 Institute of Agricultural Sciences of South Vietnam, 121 Nguyen Binh Khiem St, District 1, Ho Chi Minh City, Vietnam.

Managing organic inputs for enhancing biological and physico-chemical soil health in the West African savannas

Vanlauwe, B.1 Keywords:

soil organic matter, decomposition, organic matter quality

Abstract

Numerous soils in the West African savannas contain less than 20% silt and clay. Soil organic matter (SOM) is a valuable resource in cropping systems with minimal external inputs, as it contributes to plant nutrition by supplying nutrients through mineralization and by favouring the soil cation exchange properties. The quality of the applied organic resources may affect those SOM-driven properties. The objectives of this paper were to investigate the relationships between N contained in various SOM fractions, obtained through particle size separation after soil dispersion and the soil N supply and to assess the impact of residue quality on the cation exchange capacities of such SOM fractions. In an initial microplot field experiment, a highly significant (P <0.001) relationship between the residue derived N (RDN) present in the SOM between 2 and 0.053 mm or the particulate organic matter (POM) and the uptake of RDN by maize. In an associated pot experiment indicated the relatively higher availability of RDN in the POM compared to the SOM <0.053 mm. In a second multilocational alley cropping trial, N uptake by maize was shown to be more closely related to N contained in the POM material as compared to N belonging to SOM fractions with smaller particle size. No clear relationships between the quality of organic inputs and the quality of the POM could be established. In a third long term arboretum with promising agroforestry species, the organic fractions had the highest CEC, expressed on dry matter basis, and the CEC of the fraction between 0.053 and 0.020 mm, the silt and the clay fractions was inversely related to their particle size: clay > fine silt > coarse silt. An important effect of the quality of the litter material on the charge characteristics of the fine and coarse silt fractions emerged as organic inputs with a high C/N and lignin/N ratio produced SOM with the highest CEC.

Introduction

Soil organic matter (SOM) is a valuable resource in cropping systems with minimal external inputs, as is the case for the major part of the West African savanna, where external inputs are scarce and/ or expensive. It contributes directly to plant nutrition by supplying nutrients through mineralization and indirectly by favouring the soil cation exchange properties. SOM is not a homogeneous pool, but consists of organic components with a wide range of turnover times. For a clear understanding of the contribution of SOM to the soil nutrient status and exchange properties, it is necessary to fractionate the total SOM pool into distinct fractions with similar characteristics and to determine the contribution of individual fractions to the various aspects of the overall soil fertility status.

Addition of fresh organic matter is one possible way to manage the size and quality of the SOM pool. In the short-term organic resources release nutrients, may enhance soil moisture conditions (Vanlauwe et al., 2001), or improve the soil available P status (Nziguheba et al., 2000). In the long term, continuous inputs of organic resources influence the levels of soil organic matter and the quality of some or all of its pools (Vanlauwe et al., 1998; Cadisch and Giller, 2000). Residue quality has been shown to modify the residue decomposition process (_anlauwe et al., 2005) and may be an important factor in regulating the impact of fresh organic matter on the various SOM fractions. Most studies undertaken to date on the contribution of SOM to soil fertility have concentrated on decomposability, mineralization, or nutrient release. However, SOM quality should also include charac­teristics relating to the contribution of SOM to the physico-chemical health of the soil.

The objectives of this paper are (i) to investigate the relationships between N contained in various SOM fractions, obtained through particle size separation after soil dispersion, and N supply as affected by the biochemical quality of freshly added plant materials (ii) to assess the impact of residue quality on the cation exchange capacities (CEC) of those SOM fractions. In the first part of the paper, the concept of organic resource quality is highlighted with supporting evidence from laboratory and field studies.

The organic resource quality concept

Unlike mineral fertilizers, the release dynamics of plant available nutrients from organic resources vary widely and are less predictable. Such uncertainties may hinder the most efficient use of these organic resources or even their adoption by small-scale farmers. A range of quality characteristics has been found to affect the decomposition and mineralization process of organic resources. Originally, the C/N ratio was seen as a good predictor of decomposition and N availability (Waksman and Tenney, 1928). Subsequently, Vallis and Jones (1973) reported that soluble polyphenols affect N mineralization dynamics of organic resources. Mellilo et al. (1982) showed that the N and lignin content of hardwood leaf litter residues significantly affected their decomposition; while Handayanto et al. (1994) showed that the content of soluble polyphenols that were actively binding proteins was better related to decomposition than the total soluble polyphenol content.

As a result of a Symposium in 1995 (Cadisch and Giller, 1997), efforts were made to consolidate information on residue quality – N dynamics relationships resulting in an Organic Resource Database (ORD). The ORD contains information on organic resource quality parameters and N mineralization dynamics from almost 300 species found in tropical agro-ecosystems (Palm et al., 2001). Analysis of the information in the ORD has led to the development of a Decision Support System (DSS) for organic matter (OM) management (Figure 1) (Palm et al., 2001). The DSS makes recommendations for appropriate use of organic materials, based on their N, polyphenol, and lignin contents resulting in four classes of organic resources (Palm et al., 2001).

Mangement of Tropical Sandy Soil for Sustainable Agriculture

Figure 1. The Decision Support System for organic N management, leading to 4 classes of organic resources (adapted from Palm et al., 2001)

To test the DSS, various trials with inputs of organic resources of varying resource quality were implemented in West, East and Southern Africa with maize as a test crop (Vanlauwe et al., 2002). Responses to organic inputs were expressed in field fertilizer equivalency values. Data from these trials showed the percentage fertilizer equivalencies (% FE) values for organic materials with a low polyphenol content (<4%) and a N content >2.3% were positively related to their N content (Figure 2). The critical level of N for increasing crop yield was 2.3%, confirming the initial value hypothesized by Palm et al. (2001). Organic matter with a high polyphenol content (>4%) still led to positive % FE values, but the increase with increased N content was less and the N content needed to improve maize yield was 2.8 rather than 2.3% (Figure 2). Polyphenol – N interactions seem to delay the immediate availability of N as concluded by others from data obtained under controlled laboratory or greenhouse conditions (Palm and Sanchez, 1991, Oglesby and_Fownes, 1992). While from the current data polyphenols appeared to be under certain conditions important modifiers guiding initial N release from organic materials, the lignin content was not observed to improve on the derived equations. This does, however, not exclude their importance in medium to long term N dynamics.

Mangement of Tropical Sandy Soil for Sustainable Agriculture

Figure 2. Relationship between the N fertilizer equivalent and the N content of plant residues and manure for a series of sites in West (W), East and Southern (E+S) Africa. The linear regression equations were calculated separately for the plant materials with low and high polyphenol (PP) content. Encircled values were excluded from the regression analysis. Source: Vanlauwe et al. (2002)

Fractionation of soil organic matter following particle-size classes

In all experiments, the soil organic matter pool was fractionated following particle size after chemical dispersion. The soil was dispersed by reciprocal shaking for 16 hours at 144 rpm after adding a Na-hexametaphosphate/Na-carbonate mixture. After dispersion, the soil slurry was wet-sieved to separate the fractions >2 mm, between 0.250 and 2 mm and between 0.053 and 0.250 mm. The organic components were separated from the mineral fraction for each of these particle-size classes by careful decantation. The slurry passing through the 0.053 mm sieve was manually passed through a 0.020 mm sieve to separate the coarse silt fraction (0.020-0.053 mm). The fine silt fraction (0.002-0.020 mm) was separated after four sedimentation cycles, while the clay fraction (<0.002 mm) was collected after four flocculation cycles with CaCl2, followed by dialysis in distilled water. The particulate organic matter (POM) includes the organic material larger than 0.053 mm. More details are given by Vanlauwe et al. (1998b). Samples to be used for CEC measurements were dispersed with only Na-carbonate, avoiding the use of Na-hexametaphosphate because of its high inherent charge. The methodology to measure CEC as a function of pH and at low ionic strength is based on the Silverthioureum (AgTU) method (Oorts et al., 2000). For measuring the CEC of the whole soil, a buffered AgTU-solution was used. In view of the limited amount of material available, the CEC of the fractions was measured at different pH-levels using the same sample. This was achieved by gradually acidifying the mixture sample-AgTU-solution and taking subsamples of the solution at different pH-levels. More details are given by Oorts et al. (2000).

The experiments

In a first microplot experiment, 15N-labeled high quality Leucaena leucocephala and low quality Dactyladenia barteri residues were applied in microplots installed in Leucaena and Dactyladenia alley cropping plots on a Ferric Lixisol at a rate of 128 and 79 kg of N ha-1, respectively. The fate of the leaf residue N was followed in the soil, crop, and hedgerow of the respective alley cropping systems during three maize and two cowpea seasons. At regular intervals, soil was sampled at 0-5 and 5-10 cm and the SOM fractionated. A subsample of dried soil, collected at each sampling time was used for a bioassay study with maize in the greenhouse to determine the residual 15N uptake by maize. A complete description of the field plot layout and experimental methods is given by Vanlauwe et al. (1998a). In a second multilocational experiment, alley cropping trials were established between 1989 and 1991 in Bouaké and Ferkéssedougou (Côte d'Ivoire), in Glidji, Amoutchou, and Sarakawa (Togo), and in Niaouli (Benin Republic) to assess crop productivity of the alley cropping systems relative to a no-tree control. More details are given by Aihou et al., 1999, Tossah et al., 1999, and Vanlauwe et al., 1999. Soils were collected between 1994 and 1996 in the various treatments for SOM fractionation. Multip_e regression analysis was used to express maize N uptake as a function of N additions and SOM N-content at the start of the season. In an additional pot experiment, soil was taken from a selected number of treatments per site and grown with maize to determine relationships between SOM fractions and maize N uptake. Soils from an alley cropping trial, established in 1986 in Ibadan (Nigeria) on a Ferric Lixisol were also included in the pot experiment. In a third experiment, soil was taken in 1995 from the surface 10 cm under Leucaena leucocephala, Dactyladenia barteri, Afzelia Africana, Pterocarpus santalinoides, and Treculia africana in an arboretum, established in 1979 in Ibadan, Nigeria.

Soil organic matter fractionation and soil N supply

In Experiment 1, initially, most of the residue derived N (RDN) was recovered in the fraction between 0.250 and 2 mm in both the Leucaena and Dactyladenia treatments. The proportion of the total amount of RDN recovered in the SOM fractions smaller than 2 mm shifted towards the smaller particle size classes towards the end of the experimental period. Although the total amount of RDN in the POM was larger for the Leucaena than for the Dactyladenia treatment, the turnover of RDN incorporated in the POM was similar for both the high-quality Leucaena and the low-quality Dactyladenia residues, probably because maize roots were present in both cases as a source of POM. Highly significant (P <0.001) relationships between the native N and the RDN present in the SOM between 2 and 0.053 mm or the particulate organic matter (POM) and the uptake of RDN by maize in the associated pot experiment confirmed the relatively higher availability of RDN in the POM compared to the SOM <0.053 mm. Moreover, the regression slopes were not significantly different for the Leucaena and Dactyladenia treatments, confirming that most likely maize roots masked any presumed relationships between the quality of the inputs (high quality Leucaena vs low quality Dactyladenia) and the turnover of the POM fraction. The weak relationships between the native N and the RDN in the SOM <0.053 mm and maize RDN uptake indicated the lower availability of N in the finer SOM fractions.

The pot trial, described under experiment 2, confirmed the relatively higher availability of N contained in the POM material compared to N associated with smaller particle size classes for a wider range of soils (Figure 3). Although the POM material in treatments with tree species having a higher N content (e.g. Leucaena) seemed to have a larger N concentration compared with treatments with lower quality tree species (e.g. Senna siamea), it was not possible to establish a clear relationship between the quality of the organic inputs and the quality of the POM material. This was caused most likely by the wide range of organic inputs in alley cropping systems (ranging from high quality leaves to low quality maize roots) and the different times of inputs relative to the soil sampling schedule. Although the N applied with the different prunings explained the largest part of the variation in obtained maize N uptake patterns in Experiment 2, the total amount of N in the POM fraction at the start of the growing season and the POM N concentration explained respectively about 14 and 5% of the observed variation (Table 1). This was surprisingly higher than the variation explained by N fertilizer (3%).

Mangement of Tropical Sandy Soil for Sustainable Agriculture

Figure 3. Relationships between the maize shoot N uptake and the particulate organic matter (POM) N content (a) and the total soil N content (b) for a series of West-African moist savanna soils taken under a selected number of treatments described in Experiment 2

Soil organic matter fractionation and soil exchange properties

For all treatments in Experiment 3, the organic fractio_s had the highest CEC, expressed on dry matter basis, and the CEC of the fraction between 0.053 and 0.020 mm, the silt and the clay fractions was inversely related to their particle size: clay > fine silt > coarse silt. A good correlation existed between the slope of the fitted CEC-pH relationships and the organic carbon content of the fractions. The clay and fine silt fractions were responsible for 85 to 90% of the CEC. An important effect of the quality of the litter material on the charge characteristics of the fine and coarse silt fractions emerged (Table 2). Organic inputs with a high C/N and Lignin/N ratio produced SOM with the highest CEC. More resistant organic residues thus had a combined positive effect on both quantity and the quality of SOM in terms of its charge characteristics.

Table 1. Stepwise multiple regression analysis of maize N uptake for the fields described under Experiment 2 (R2 of the regression model = 0.692)

Independent variables

Regression coefficient

Prob > F

Partial correlation

– N content of prunings 1, 2, and 3 (kg N ha-1)

+ 0.092

0.0001

0.273

– Rainfall during growing season (mm)

+ 0.066

0.0001

0.167

– POM N content (kg N ha-1)

+ 0.130

0.0018

0.143

– POM N concentration (%)

+ 30.9

0.0231

0.048

– Fertilizer N addition (kg N ha-1)

+ 0.318

0.0490

0.033

– Soil silt + clay content (%)

+ 0.848

0.0629

0.028

– Constant -106.4

Table 2. Multiple regressions for CEC of the fine (0.020-0.002 mm) and coarse (0.053-0.020 mm) silt organic matter fractions in Experiment 3

 

Regression equation

R2

Fine silt

CEC = 0.81 + 0.59* pH

0.459

CEC = -5.76 + 0.69* pH + 0.22* (C/N)

0.847

CEC = -1.58 + 0.61* pH + 0.09* (Lignin/N)

0.834

Coarse silt

CEC = 1.16 + 0.48* pH

0.368

CEC = -4.66 + 0.55* pH + 0.20* (C/N)

0.678

CEC = -0.95 + 0.50* pH + 0.07* (Lignin/N)

0.643

Conclusions

Fractionation of the SOM pool into different fractions with varying particle size yielded fractions with distinct features related to N supply and cation exchange properties. While the coarser material appeared to be more closely related to N supply, the finer fractions were more relevant for exchange properties. Although the N concentration of the POM material seemed to positively influence N uptake by maize, no clear relationships between the quality of fresh organic inputs and POM could be established, due to the wide range of fresh organic materials in alley cropping systems and due to the incorporation of residue derived N in other organic materials before entering the POM pool. Contrarily with N supply, residue quality seemed to influence the CEC characteristics of the coarse and fine silt material. This was not the case for the clay fraction because of the relatively high contribution of its mineral components to the CEC.

There is a need for a user-friendly method to determine the quality of the SOM fractions following a similar approach as for fresh organic inputs. Care should be taken of the per definition differences in particle size of the different SOM pools, as residue particle size interferes with the outcome of the ‘traditional’ residue quality procedures for plant residues (Vanlauwe et al., 1996a). Furthermore, it is not clear whether the impact of the quality of a single organic input is consistently masked by the wide range of other inputs in a realistic cropping system (roots, weeds, crop residues, etc.). Determination of the variation in POM quality and N release during the growing season could help evaluate the former point. The impact of the location of the POM material within the soil structure on its N release characteristics needs to be evaluated. Lastly, the exact contribution of each SOM fraction to maize N uptake as a function of above-mentioned parameters (quality, location in the soil matrix) should be the ultimate goal in attempting to unravel the N supply characteristics of the SOM pool.

References

Aihou, K., Sanginga, N., Vanlauwe, B., Lyasse, O., Diels, J., and Merckx, R. 1999. Alley cropping in the moist savanna of West-Africa: I. Restoration and maintenance of soil fertility on ‘terre de barre’ soils in Bénin Republic. Agroforestry Systems, 42, 213-227.

Tossah, B.K., Zamba, D.K., V_nlauwe, B., Sanginga, N., Lyasse, O., Diels, J., and Merckx, R. 1999. Alley cropping in the moist savanna of West-Africa: II. Impact on soil productivity in a North-to-South transect in Togo. Agroforestry Systems, 42, 229-244.

Cadisch, G. and Giller, K.E. 2000. Soil organic matter management: The role of residue quality in carbon sequestration and nitrogen supply. In: Rees, R.M., Ball, B., Watson, C, and Campbell, C, eds., Sustainable management of soil organic matter. CAB International, Wallingford, UK, 97-111.

Handayanto, E., Cadisch, G., and Giller, K.E. 1994. Nitrogen release from prunings of legume hedgerow trees in relation to quality of the prunings and incubation method. Plant and Soil, 160, 237-248.

Melillo, J.M., Aber, J.D., and Muratore, J.F. 1982. Nitrogen and lignin control of hardwood leaf litter decomposition dynamics. Ecology, 63, 621-626.

Nziguheba, G., Merckx, R., Palm, C.A., and Rao, M.R. 2000. Organic residues affect phosphorus availability and maize yields in a Nitisol of Western Kenya. Biology and Fertility of Soils, 32, 328-339.

Oglesby, K.A. and Fownes J.H. 1992. Effects of chemical composition on nitrogen mineralization from green manures of seven tropical leguminous tress. Plant and Soil, 143, 127-132.

Oorts, K., Vanlauwe, B., Cofie, O.O., Sanginga, N., and Merckx, R. 2000. Charge characteristics of soil organic matter fractions in a Ferric Lixisol under some multipurpose trees. Agroforestry Systems, 48, 169-188.

Palm, C.A. and Sanchez, P.A. 1991. Nitrogen release from the leaves of some tropical legumes as affected by their lignin and polyphenolic contents, Soil Biology and Biochemistry, 23, 83-88.

Palm, C.A., Gachengo, C.N., Delve, R.J., Cadisch, G., and Giller, K.E. 2001. Organic inputs for soil fertility management in tropical agro-ecosystems: application of an organic resource database. Agriculture, Ecosystems and Environment, 83, 27-42.

Vallis, I. and Jones, R.J. 1973. Net mineralization of nitrogen in the leaves and leaf litter of Desmodium intortum and Phaseolus atropurpureus mixed with soil. Soil Biology and Biochemistry, 5, 391-398.

Vanlauwe, B., Sanginga, N., and Merckx, R. 1998a. Recovery of Leucaena and Dactyladenia residue nitrogen-15 in alley cropping systems. Soil Science Society of America Journal, 62, 454-460.

Vanlauwe, B., Sanginga, N., and Merckx, R. 1998b. Soil organic matter dynamics after addition of nitrogen-15-labeled Leucaena and Dactyladenia residues. Soil Science Society of America Journal, 62, 461-466.

Vanlauwe, B., Aman, S., Aihou, K., Tossah, B.K., Adebiyi, V., Sanginga, N., Lyasse, O., Diels, J., and Merckx, R. 1999. Alley cropping in the moist savanna of West-Africa: III. Soil organic matter fractionation and soil productivity. Agroforestry Systems, 42, 245-264.

Vanlauwe, B., Aihou, K., Aman, S., Iwuafor, E.N.O., Tossah, B.K., Diels, J., Sanginga, N., Merckx, R., and Deckers, S. 2001. Maize yield as affected by organic inputs and urea in the West-African moist savanna. Agronomy Journal, 93, 1191-1199.

Vanlauwe, B., Palm, C.A., Murwira, H.K. and Merckx, R. 2002. Organic resource management in sub-Saharan Africa: validation of a residue quality-driven decision support system. Agronomie, 22, 839-846.

Vanlauwe, B., Gachengo, C., Shepherd, K., Barrios, E., Cadisch, G., and Palm, C.A. 2005. Laboratory validation of a resource quality-based conceptual framework for organic matter management. Soil Science Society of America Journal, 69, 1135-1145.

Waksman, S.A. and Tenney, F.G. 1928. Composition of natural organic materials and their decomposition in soil. III The influence of nature of plant upon the rapidity of its decomposition. Soil Science, 26, 155-171.


1 TSBF-CIAT, P.O. Box 30677, Nairobi, Kenya , E-mail: b.vanlauwe@cgiar.org

Previous PageTop of PageNext Page