Soil Organic Matter Dynamics and Crop Productivity as Affected. by Organic Resource Quality and Management Practices on.







Full text


by Organic Resource Quality and Management Practices on

Smallholder Farms


Florence Mtambanengwe

A thesis submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Department of Soil Science & Agricultural Engineering Faculty of Agriculture

University of Zimbabwe June 2006


To my boys,

I have done this for you. Thanks for the unwavering support and for believing in me. You are my inspiration. This is just the beginning of many more challenges to come.



Crop productivity in low-input agricultural systems is largely a function of the soil’s capacity to hold and release nutrients in soil organic matter (SOM). Although sandy soils on most Zimbabwean smallholder farms inherently contain a small amount of SOM, large variability in soil productivity (fertility gradients) exists between adjacent fields or field sections within the same farm. Farmer management of such variability remains a challenge and sustainable option for soil productivity are required. This study was based on the hypothesis that SOM, a renewable resource, is the driving force behind sustainable crop productivity on depleted sandy soils. Relationships between maize yields and SOM contents, nitrogen (N) release patterns, and their links with organic matter management practices by farmers differing in resource endowment were evaluated under different Natural Regions (NR) in the smallholder farming areas of Chikwaka (NR II: >750 mm yr-1), Chinyika (NR III: 650-750 mm yr-1) and Zimuto (NR IV: 450-650 mm yr-1). The cumulative effect of applying known quantities of different quality organic resources on SOM formation and maize productivity was also evaluated on-station at Domboshawa (NR II) and Makoholi (NR IV) Experimental Stations following incorporation of sunnhemp (Crotalaria juncea) green manure, calliandra (Calliandra calothyrsus) prunings, cattle manure, maize (Zea mays) stover and pine (Pinus patula) sawdust into soil.

Farmers’ perception of soil productivity was consistent with laboratory indices across the different rainfall zones. Criteria for ranking the most productive ‘rich’ and least productive ‘poor’ fields ranged from colour through elements of soil structure to crop response following external nutrient inputs. Laboratory analysis showed that rich fields contained significantly more soil organic carbon (SOC) ranging between 5 - 8 g kg-1, compared with between 3 - 6 g kg-1 for designated poor fields. Differences in SOC contents between rich and poor fields were wider in the old communal areas of Chikwaka and Zimuto with >70 years of smallholder farming than in Chinyika (<25 years), suggesting that the observed fertility gradients are a cumulative effect of years of differential management practices by the different farmer classes. Overall, rich fields received between 0.3 - 13 t C ha-1 compared to 0.1 - 6 t C ha-1 for poor fields with resource endowment apparently dictating the intensity of use.

Organic inputs with a C:N ratio >25 (the bulk of available resources on-farm) contributed significantly to overall particulate organic matter (POM) size in sandy soils. The intensity of C management was reflected more in meso- POM (53-250 µm diameter) compared to the macro-POM (250-2000 µm diameter) fraction suggesting that the larger POM fraction has a high turnover and is not protected from degradation. However, early season (within five weeks of incorporation) N availability from these materials was low (<5% of added N) resulting in poor maize performance during the vegetative phase. This may justify the high organic matter loading strategy of up to 50 t ha-1 employed by those farmers who often achieve yields of >3 t ha-1 on coarse sands. Practical management options for smallholder farmers who usually access low quality resources may include pre-application treatments such as composting or organic/mineral N fertilizer combinations to enhance N availability. The overall size of the organo-mineral fraction (<53 µm diameter) in these soils was small (<250 g kg-1 soil) and stable, and was not influenced by quality and quantity of C inputs and time over which they had been applied. High quality organic materials (e.g. sunnhemp) apparently enhanced the N-supply capacity of the organo-mineral fraction without necessarily increasing its size. However, such materials (C:N <25) released between 15-25% of added N within five weeks of incorporation, suggesting that a significant proportion of N is lost before uptake. The challenge is to enhance the efficiency with which N release from high quality materials can be managed.

Maize productivity, and most likely that of other cereals, on depleted sandy soils was related to within-season mineral N fluxes and labile POM fraction. Both factors were


primarily a function of differential capacity to manage organic matter by different farmer classes. Sustenance of optimal maize yields on sandy soils may only be possible through regular supply of both high and low quality materials in combination with mineral fertilizers, particularly N. High quality C inputs are likely to enhance short-term nutrient supply capacity of a small organo-mineral fraction present, while slow decomposing materials would contribute towards the long-term maintenance of critical SOM pools.



The study is an output of the Nutrient Use Efficiency and Soil Organic Matter (NUESOM) project (Grant 2002 FS 189) funded by the Rockefeller Foundation (RF). I am particularly indebted to my supervisor, Dr Paul Mapfumo for awarding me the PhD Fellowship, a rare opportunity to express my potential. Funds to kick start on-farm work were received from the RF’s African Careers Award Grant to Dr Mapfumo while initial establishment of the Domboshawa and Makoholi on-station experiment was through seed money from TSBF-CIAT’s African Network (AfNet). Work reported in Chapter 7 of this thesis was largely through a grant to Dr Paul Mapfumo from International Foundation for Science, Stockholm. I thank Dr Mapfumo for his unwavering support, invaluable scientific and professional guidance and cooperation throughout the study. Thanks Paul, I can now face the world. I gratefully acknowledge the high level of cooperation received from farmers in Chikwaka, Chinyika and Zimuto smallholder areas, and officers from the Department of Research and Extension (AREX) of the Ministry of Agriculture, Zimbabwe, who were key facilitators in the communal study sites and provided technical services at Domboshawa and Makoholi Research Stations.

Many thanks to Dr Bernard Vanlauwe of TSBF-CIAT, who was instrumental in the design of the on-station experiment and for keeping me focussed throughout the study. To Dr Alain Albrecht, thank you for the push. I am grateful to the World Agroforestry Centre (ICRAF) for allowing us to prune Calliandra from their site and to TSBF-CIAT for the lignin and polyphenol analyses. I also gratefully acknowledge financial support from the W.K. Kellogg Foundation under the WKKF Dissertation Awards Program and for identifying the potential of my study in contributing to the Foundation’s mission in support of the development of healthy and sustainable rural communities in Southern Africa. A very special thank you to Academy for Educational Development (AED) and African Intellectual Resources (AIR) for intelligent ideas on how to write a “winning” thesis. Finally, I would want to thank Joyce Ushe, Timothy Mapfumo and Eliah Mbizah for their technical assistance with the thousands of samples destined for laboratory analysis, and my fellow student on the NUESOM Project, Josphat Chisora, for assistance with the socio-economic surveys and data handling.







CHAPTER 1 ... 1


1.1 Background ... 1

1.2 Variability and soil fertility gradients on smallholder farms ... 3

1.3 Study rationale ... 5

1.4 Hypotheses ... 8

1.5 Objectives of the study... 8

1.6 Thesis structure ... 9

CHAPTER 2 ... 11


2.1 The soil fertility management paradigm and soil organic matter ... 11

2.2 Quantification of SOM ... 12


2.3.1 Coarse light fraction ... 14

2.3.2 Microbial biomass fraction ... 14

2.3.3 Heavy fraction ... 15

2.4 Causes of SOM decline ... 16

2.4.1 Tillage ... 16

2.4.2 Erosion ... 17

2.5 Building SOM? ... 18

2.6 SOM and Nutrient management strategies by smallholder farmers ... 19

2.6.1 Livestock manure... 21

2.6.2 Green manures ... 21

2.6.3 Intercrops and rotations ... 22

2.6.4 Crop residues ... 23

2.6.5 Woodland litter ... 24

2.6.6 Household waste and compost ... 24

2.6.7 Termitarium soil ... 25

2.6.8 Mineral fertilizers... 26

2.6.9 Ash ... 26

CHAPTER 3 ... 27


3.1 Introduction ... 27

3.2 On-station experimental sites ... 27

3.2.1 Domboshawa ... 27

3.2.2 Makoholi ... 29

3.3 On-farm experimental sites ... 29


3.3.2 Chinyika ... 30

3.3.3 Zimuto ... 31

3.4 Overview of the farming systems ... 31

3.5 Overview of the methodological approach used ... 33

CHAPTER 4 ... 37


4.1 Abstract ... 37

4.2 Introduction ... 38

4.3 Materials and methods... 41

4.3.1 Selection of field sites and soil sampling ... 41

4.3.2 Biomass quantification and analyses ... 42

4.3.3 Carbon and nitrogen mineralization of field surface organic biomass 43 4.3.4 Data analyses ... 44

4.4 Results ... 45

4.4.1 Characteristics of rich and poor fields – A farmer criteria ... 45

Zimuto ... 49

4.4.2 In situ biomass available for incorporation ... 50 Early dry season period ... 50 Late dry season period ... 52

4.4.3 Potential C and N contributions from in situ biomass... 53

4.4.4 C and N release patterns from in situ biomass ... 55

4.5 Discussion ... 60


4.5.2 Quantities of in situ biomass available for incorporation ... 62

4.5.3 Carbon contributions and nutrient release from in situ biomass ... 64

4.6 Conclusions ... 66

CHAPTER 5 ... 67


5.1 Abstract ... 67

5.2 Introduction ... 68

5.3 Materials and methods... 70

5.3.1 Organic resource selection and characterization ... 70

5.3.2 Generation of organic resources ... 71

5.3.3 Field layout and experimental treatments ... 72

5.3.4 Mineral N dynamics ... 74

5.3.5 Data analysis ... 74

5.4 Results ... 75

5.4.1 Influence of organic resource quality and quantity on maize productivity ... 75

5.4.2 Relative contributions of different nutrient sources on grain yield .... 78

5.4.3 Nitrogen uptake patterns ... 83

5.4 Discussion ... 86

5.5 Conclusions ... 90



... 92

6.1 Abstract ... 92

6.2 Introduction ... 93

6.3 Materials and Methods... 95

6.3.1 Experimental treatments and management on-station ... 95

6.3.2 On-farm experimental treatments and management ... 97

6.3.3 Sampling for mineral N dynamics ... 99

6.3.4 Ammonium-N and Nitrate-N analyses ... 101

6.3.5 Data analyses ... 102

6.4 Results ... 102

6.4.1 Influence of organic quality and C application rate on soil NH4+-N 102 6.4.2 Influence of organic quality and C application rate on soil NO3--N . 107 6.4.3 Maize productivity in response to organic resource application on-station (Makoholi) ... 111

6.4.4 Soil N changes and maize productivity under smallholder farmer management ... 113

6.5 Discussion ... 119

6.6 Conclusions ... 124

CHAPTER 7 ... 126



7.2 Introduction ... 127

7.3 Materials and Methods... 129

7.3.1 Study sites ... 129

7.3.2 Soil sampling and fractionation ... 132

7.3.3 Mineral N analysis ... 134

7.3.4 Quantifying the N mineralization potential and C contributions in fractions 134 7.3.5 Data analyses ... 135

7.4 Results ... 135

7.4.1 Effect of organic resource quality on the size of POM fractions ... 135

7.4.2 POM size fractions on sandy soils under smallholder farmer management ... 138

7.4.3 Distribution of POM down contrasting soil profiles ... 140

7.4.4 Potential mineral N contributions from different POM fractions ... 142

7.4.5 Relationships between POM fraction size and maize productivity . 143 7.5 Discussion ... 148

7.5.1 Build-up of POM fractions in soil ... 148

7.5.2 Effect of organic resource quality on POM enrichment ... 149

7.5.3 Effect of soil texture on POM enrichment ... 151

7.6 Conclusions ... 153

CHAPTER 8 ... 155


8.1 Abstract ... 155


8.3 Materials and Methods... 158

8.3.1 Selection and monitoring of farm and field sites ... 158

8.3.2 Soil sampling and fractionation ... 162

8.3.3 Measurement of labile C fractions ... 163

8.3.4 Data analyses ... 164

8.4 Results ... 164

8.4.1 C and N in inputs allocated to different field types ... 164

8.4.2 Impact of short-term organic matter management on POM size fractions 165 8.4.3 Effect of organic matter management history on POM enrichment in farmers’ fields ... 167

8.4.4 Soil fertility management strategies by smallholder farmers: The Zimuto case study ... 170

8.4.5 C lability and maize productivity ... 175

8.5 Discussion ... 179

8.5.1 Implications of organic matter management on fertility gradients on smallholder farms ... 179

8.5.2 Enrichment of POM fractions in farmers’ fields ... 180

8.5.3 Significance of annual organic inputs on labile C fractions ... 181

8.5.4 Quality of applied organic resource and C lability ... 182

8.6 Conclusions ... 184

CHAPTER 9 ... 185



9.2 Matching farmers’ perception of soil productivity with conventional

science to enhance sustainability ... 185

9.3 Resource endowment as an organic matter management factor ... 186

9.4 Fate of different quality organic resources in cropping systems ... 189

9.5 Optimizing organic nutrient sources for improved maize productivity ... 191

9.6 Options for improving soil productivity for resource-poor farmers ... 193

9.6 Areas of further research ... 195




Table 3.1 Major characteristics of farming systems prevalent in the different agro-ecological regions of Zimbabwe ... 28 Table 3.2 Descriptive criteria for classification of farmers in Chikwaka, Chinyika

and Zimuto smallholder farming areas ... 34 Table 4.1 Smallholder farmer indicators for highly productive (rich) and poorly

productive (poor) fields or field sections in Zimbabwe (ranked in order of importance) ... 46 Table 4.2 Soil characteristics of smallholder farmers’ rich and poor fields in

three agroecological regions of Zimbabwe ... 49 Table 4.3 Potential C and N contributions from maize- and non-stover biomass

at different periods of incorporation under smallholder farmer management in high (Chikwaka) and medium (Chinyika) rainfall areas ... 54 Table 4.4 Potential C and N contributions from maize- and non-stover biomass at

different periods of incorporation under smallholder farmer management under semi-arid conditions in Zimuto (450 - 650 mm year-1) ... 55 Table 4.5.Quality parameters of in situ biomass* on rich and poor fields of

smallholder farms in three agroecological regions of Zimbabwe ... 57 Table 5.1 Quality of organic resources at time of field incorporation at

Domboshawa and Makoholi experimental sites ... 72 Table 5.2 Maize grain yield and harvest index as influenced by organic resource

quality and application rate under contrasting environments ... 79 Table 5.3 Relative contribution of mineral fertilizer and organic x mineral fertilizer

interaction effects to maize grain yield as influenced by organic resource quality under different environments ... 82


Table 5.4 Statistical significance of organic and mineral nutrient sources on maize and stover N quality at Domboshawa ... 83 Table 5.5 The effect of organic resource quality and quantity of application (carbon

basis) on maize grain and stover N concentration at Domboshawa in Zimbabwe ... 84 Table 6.1 Organic and mineral nutrient sources used as soil amendments by

farmers in Chikwaka, Chinyika and Zimuto smallholder farming areas ... 98 Table 6.2 Effect of organic resources quality on maize productivity for different

application rates at Makoholi Experimental Station during 2003-04 cropping season ... 112 Table 6.3 Maize biomass production and grain yields from different quality nutrient

sources used in experiments designed and managed by farmers in three smallholder areas of Zimbabwe during the 2003-04 season ... 115 Table 7.1 Quality of organic resources used under two contrasting soil types at

Domboshawa and Makoholi field experiments ... 130 Table 7.2 Organic and mineral nutrient sources used by smallholder farmers in

Chikwaka and Zimuto communal areas... 131 Table 7.3 R2 values of relationship between maize yields and total C, POM- and

organo-mineral- size fractions (0-30 cm depth) under different organic matter management at four sites in Zimbabwe ... 144 Table 7.4 R2 values and level of significance for relationships between maize

yields and particulate organic matter size fractions at different depths from two on-farm sites (Chikwaka and Zimuto) and two on-station sites (Domboshawa and Makoholi) ... 145


Table 8.1 Mean quantities (ranges in parentheses) of organic and mineral nutrient sources used by smallholder farmers on rich and poor fields during the 2002/03 and 2003/04 seasons in Chikwaka, Chinyika and Zimuto ... 160 Table 8.2 Quantity and quality of different organic and mineral nutrient sources

used in farmer-managed field experiments in Chikwaka, Chinyika and Zimuto ... 161 Table 8.3 Soil properties and total C applied on the most productive (rich) and

least productive (poor) fields on selected farms in Zimuto Communal Area ... 173 Table 8.4 Relationships between maize grain yield and different soil C and N

fractions under different organic and nutrient resource management in sub-humid Chikwaka and semi-arid Zimuto ... 177



Figure 3.1 Schematic diagram of the methodological approach adopted for the study. Solid arrows indicated direction of flow of events while dotted arrows represent key outputs necessary for each entry point. ... 36 Figure 4.1 Soil organic C content of rich and poor fields belonging to Resource-endowed, Intermediate and Resource-constrained farmers in Chikwaka, Chinyika and Zimuto. Bars represent SEDs ... 48 Figure 4.2 In situ biomass in rich and poor fields of three farmer categories from

Chikwaka (a), Chinyika (b) and Zimuto (c). ‘Early’ denotes early dry season biomass and ‘Late’ is late dry season biomass ... 51 Figure 4.3 CO2-C release by different organic resources found on farmers’ fields

following 150 days of incubation with soil. Bars indicate least significant differences at p < 0.05 ... 58 Figure 4.4 Total mineralizable N (NH4+-N + NO3--N) from different quality organic

resources found on farmers fields following 150 days of incubation with soil. Ratio of non-maize stover: maize stover biomass was ~2:1. ... 59 Figure 5.1 Relationship between soil mineral N availability (before mineral N

fertilizer application) and a 2 week-old maize crop biomass at Makoholi (a) and Domboshawa (b) under different quantities and quality organic resources ... 76 Figure 5.2 Relationship between maize productivity at two weeks after emergence

and final grain yield under low rainfall at Makoholi (a) with no mineral fertilizer N addition and (b) plus 120 kg N ha-1. ... 80 Figure 5.3 Relationship between maize total N uptake and grain yield under high


denote high biomass application rates of 7.5 t C ha-1 (versus 2.5 t C ha-1) for the same organic resource. Solid symbols denote mineral N fertilized treatments) ... 85 Figure 6.1 Rainfall distribution during the 2003-2004 season at Makoholi (total =

647 mm) and Zimuto (total = 659 mm). (Major events during the season are indicated by arrows) ... 100 Figure 6.2 Soil NH4+-N dynamics under different quality organic resources applied

at 1.2 t C ha-1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2004. ... 104 Figure 6.3 Soil NH4+-N dynamics under five different quality organic resources

applied at 4.0 t C ha-1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2004. ... 106 Figure 6.4. Soil NO3--N dynamics under different quality organic resources applied

at 1.2 t C ha-1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2004. ... 108 Figure 6.5 Soil NO3--N dynamics under five different quality organic resources

applied at 4.0 t C ha-1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2004. ... 109 Figure 6.6 Relationship between maize grain yields and mid-season (Feb.) soil N

availability in the top 30 cm of the profile following incorporation of different organic nutrient sources at two carbon rates on a sandy soil at Makoholi 114


Figure 6.7 Soil available mineral N during mid (February) and end (April) of the season (2003-4) following incorporation of different nutrient sources in a sandy soil by smallholder farmers in Zimuto ... 116 Figure 6.8 Relationship between total amount of N supplied in different nutrient

sources and maize grain yield under smallholder farmer management in Chikwaka, Chinyika and Zimuto ... 118 Figure 7.1 Schematic diagram showing procedure used to separate particulate

organic matter and organo-mineral fractions in soil ... 133 Figure 7.2 Relative C distribution in separated POM- and organo-mineral fractions

following two seasons application of 4 t C ha-1 of different quality organic resources on (i) a sandy clay loam at Domboshawa and (ii) a coarse sand at Makoholi ... 136 Figure 7.3 Relative C distribution in the different POM- and organo-mineral

fraction following application of different quality organic resources on a coarse sands under (i) high rainfall area at Chikwaka and (ii) semi-arid conditions at Zimuto during the 2003-04 season ... 139 Figure 7.4 Size and distribution of two POM fractions and an organo-mineral

fraction following incorporation of different quality organic resources at 4 t C ha-1 on a sandy clay loam soil under high rainfall conditions at Domboshawa, and coarse sands under semi-arid conditions at Makoholi ... 141 Figure 7.5 Potential mineralizable N from the macro-, meso-POM and organo-mineral fractions following incorporation of 4 t C ha-1 of different quality organic resources on (i) a sandy clay loam soil at Domboshawa and (ii) coarse sand at Makoholi... 143


Figure 7.6 Relationship between maize yield and potential mineralizable N from the macro-POM fraction in the top 30 cm of a sandy clay loam soil at Domboshawa. ... 146 Figure 7.7 Relationship between maize yield and potential mineralizable N from

the organo-mineral fraction in the top 30 cm of a coarse sandy soil at Makoholi ... 147 Figure 7.8 Relationship between maize yield and the sum of potential

mineralizable N from the macro- meso-POM and organo-mineral fractions in the top 60 cm of a coarse sandy soil at Zimuto ... 148 Figure 8.1 C and N inputs from different quality nutrient sources applied to most

productive (rich) and least productive (poor) field types under different rainfall regimes of Chikwaka, Chinyika and Zimuto smallholder farming areas (n = 20) ... 166 Figure 8.2 Enrichment of different POM-size fractions following field application of

different quality nutrient sources in three smallholder farming areas of Zimbabwe ... 168 Figure 8.3 Topsoil (0-20 cm) enrichment of different POM-size fractions for the

most productive (rich) and least productive (poor) fields under smallholder management in semi-arid Zimuto Communal Area (n = 20) ... 169 Figure 8.4 Mid-season (February) cumulative labile C fractions from the 0-20 cm

and 0-60 cm soil depths following deliberate application of known quantities of different quality nutrient sources in Chikwaka (a) and Zimuto (b) Communal Areas ... 174 Figure 8.5 Relative distribution of three different POM fractions under smallholder


Figure 8.6 Relationship between maize grain yield, mineralizable N and readily available C in the top 20 cm of most productive (rich) and least productive (poor) fields under smallholder farmer management in Zimuto ... 178 Figure 9.1 Possible enrichment of measurable organic matter fractions in fields

differing in their productivity potential. Arrow size shows the magnitude of either C entering the pool (block arrows) or the amount of potential mineralizable N released from the fraction (simple solid arrows) ... 190



Box 8.1 Soil fertility management strategies at Mr Mazarire’s farm using cattle manure………170 Box 8.2 Soil fertility management strategies at Mrs Mbokochena farm using woodland litter ………..171 Box 8.3 Soil fertility management strategies at Mrs Chirakata’s farm ………….171



Appendix 1. Monthly rainfall during 2002/03 and 2003/04 seasons at Makoholi and Domboshawa Experimental Stations ... 213 Appendix 2. Rainfall distribution during the 2003/04 season in Chikwaka (total =

765 mm), Chinyika (total = 631 mm) and Zimuto (total = 659 mm) ... 214 Appendix 3. Publications from this thesis ... 215



AREX Agricultural Research and Extension

C Carbon

CEC Cation exchange capacity

FPRA Farmer participatory research approach GHI Grain harvest index

GIS Geographical Information System

M Molarity

masl Metres above sea level

N Nitrogen

NH4+-N Ammonium nitrogen

NIRS Near Infra-red reflectance spectroscopy NO3- -N Nitrate nitrogen

NR Natural Region

POM Particulate organic matter SOC Soil organic carbon

SOM Soil organic matter

WAE Weeks after crop emergence



Introduction and Problem Definition

1.1 Background

Increasing smallholder agricultural productivity in sub-Saharan Africa has been identified in the UN Millennium Development Goals (MDG) as key to reducing extreme poverty and hunger (United Nations, 2000). Agricultural output has been declining in most parts of Africa not only threatening achievement of MDG1 (extreme poverty and hunger eradication), but also compromising environmental sustainability as farmers often move into marginal areas. Soil fertility degradation still remains the single most important constraint to food production in sub-Saharan Africa including Zimbabwe (Sanchez et al., 1997; Mapfumo and Giller, 2001), and it has become vital to adopt a holistic approach in the promotion of improved soil productivity, particularly in the smallholder sector. In Zimbabwe alone, failure of the 2003/04 and 2004/05 seasons due to persistent droughts and government land reform programmes has led to an officially acknowledged maize (Zea mays L.) deficit of 1.2 million metric tonnes, requiring over US$200 million for grain importation alone (United Nations, 2005). This emphasizes the importance of understanding the processes underpinning soil productivity and how these could be manipulated to enhance agricultural productivity.

At national level, one of the many ways in tackling food security demands includes formulation of strategies that help bring back depleted soils to their original agricultural production potential. Maintaining productivity of those soils that are currently productive without encroaching into marginal areas remains a major


challenge to agricultural productivity. This may require that the soil resource base is able to adequately provide the nutrients required to sustain the increased crop yields. Continued decline in soil productivity has necessitated the formulation of improved management strategies that maintain and protect the soil resource base.

Traditional methods for sustaining soil productivity have been outpaced by a growing population, a diminishing natural resource base, and a downward spiral of many national economies. Moreover, insufficient nutrient inputs in the form of organic and mineral fertilizers to replace harvested or exported nutrients typify the majority of such cropping systems (Smaling et al., 1997). In most instances, maintenance of soil fertility on smallholder farms in sub-Saharan Africa is almost entirely dependent on locally available organic resources, which are often in insufficient quantities to make the desired impact (Mapfumo and Giller, 2001). Use of mineral fertilizers, despite their acknowledged benefits by smallholder farmers (Piha, 1994), have remained prohibitively expensive. For instance, the retail price of about US$30 per 50 kg bag of nitrogen (N) fertilizer, (retail price of 2005) is far beyond the reach of most smallholder farmers, who survive on <US$1 a day.

About 70% of Zimbabwe is covered by inherently poor coarse sandy soils derived from granite (Thompson and Purves, 1981). However, the predominantly resource-constrained farmers in the smallholder sector still rely heavily on these soils for dry-land farming with very little or no external nutrient additions. Soil organic matter (SOM) has been identified as the single major source of nutrients sustaining crop productivity in such low-input systems (Woomer et al., 1994; Hassink, 1997). Sandy soils characterizing many Zimbabwean smallholder farms invariably contain small amounts of SOM because of their lack of capacity to


protect organic matter from microbial degradation (Giller et al., 1997). How smallholder farmers continue to maintain the productivity of their arable fields therefore remains a puzzle and requires further research on crop-soil management interactions. The importance of SOM in nutrient cycling has long been recognized although a mechanistic understanding of the relationship between SOM and nutrient availability has only begun to emerge in recent years (Vanlauwe et al., 2002a; Mtambanengwe and Mapfumo, 2005).

Nutrient release from SOM is dependent upon mineralization of biologically active fractions, which may vary qualitatively and quantitatively in relation to the quality and quantity of organic inputs (Vanlauwe et al., 1994; Barrios et al., 1996). The fractions may or may not be homogeneously distributed in space and time. However, information on the actual fate of the applied organic resources to soil is still scanty (Palm et al., 2001a). Significant advances have been made in understanding the influence of resource quality on plant nutrient availability (particularly N and P), but to date the effect of resource quality and management factors on SOM dynamics over different time frames have not been clearly understood (Mapfumo et al., 2001a). The major challenge on arable lands is to arrest SOM decline, and wherever possible, promote its build-up through appropriate management of organic resources available to farmers. Farmers often face complex management decisions involving resource allocation to different field typologies, as well as labour constraints (Tittonell et al., 2005a).

1.2 Variability and soil fertility gradients on smallholder farms

Physical, chemical and biological soil properties may vary over short distances resulting in uneven crop stands. While much of the variation in soil productivity


observed across faming landscapes has often been attributed to inherent differences in soil forming factors such as climate, parent material (Foth, 1984) and catenary positioning (Tittonell et al., 2005b), soil processes leading to the manifestation of within-field and within-farm variation are still not well understood. For instance, differences in productivity between two sections of the same field, or between fields sharing the same soil parent material and textural properties are often evident within and across fields and farms (Mapfumo et al., 2001a). While farmers generally recognize the existence of such spatial soil variation within their fields and farms (Scoones et al., 1996; Chikuvire, 1998), the nature and causes of these high and low zones of fertility, or ‘soil fertility gradients’, are largely unknown. The little explained variation has been attributed to the physically well-defined field environments such as termite mounds, homestead surroundings and areas under tree canopies. Evidence exists that farmers deliberately exploit these ‘islands of fertility’ in order to maximize use of available nutrients in these niches (Carter and Murwira, 1995; Chikuvire, 2000).

Variation in crop yield largely occurs as a result of either environmental limitations or differences in management by farmers within specific cultural and socio-economic contexts (Tittonell et al., 2005a). Such gradients are more pronounced under unfavourable crop growth conditions, such as low or poor rainfall distribution or low nutrient application. Resource allocation to various fields/ field sections belonging to the same farmer may vary substantially creating zones of nutrient accumulation and depletion (Vanlauwe et al., 2001; Smaling et al., 2002). The practice of preferential distribution of resources within and between farms is common under most smallholder farms in sub-Saharan Africa, and the challenge is to come up with tools that could help manage these differences rather than


concentrating on bringing areas of low fertility in line with the rest of the fields. Such localized nutrient concentrations are likely to have a differential impact on the SOM status of the different fields. Whether soil fertility gradients evolving from farmer management are more important in determining overall farm productivity compared to those from inherent soil properties still needs verification and more empirical data is required.

1.3 Study rationale

Use of organic nutrient sources by the majority of smallholder farmers is often seen as an alternative to expensive mineral fertilizers. However, organic resources are rarely available in sufficient quantities to cover land area required for optimal crop production, particularly the maize staple food. Although information on the amount of nutrients potentially released by different quality organic materials is available (Palm et al., 2001a; Chikowo, 2005), the net flow of resources at field scale is only beginning to emerge. Little is known about the behaviour of the applied organic resources under different land management systems or how they affect soil-nutrient-crop interactions spatially and temporally. Several studies have demonstrated additive effects between organic and mineral fertilizers combinations (Palm et al., 1997; Giller 2001). With the exception of cattle manure, information on which of the readily available organic resources on smallholder farms can be applied together with mineral fertilizers to maximize crop yields is still scanty. More work on nutrient combinations under smallholder management is necessary to be able to come up with a step-by step decision guide enumerating the exact quantities for either of the nutrient source required. It remains a fact that there is no achievable yield without mineral fertilizer application for most cultivated


soils in Zimbabwe (Grant, 1967; Mapfumo et al., 2001b), and it is therefore imperative that farmers increase the efficiency of mineral fertilizer use.

Most of the studies on organic matter decomposition and nutrient release have been mainly concentrated on homogenous materials such specific leguminous species and crop residues (Cadisch and Giller, 1997). This poses a challenge for a predictive understanding of the behaviour of SOM on real farm situations since organic resources accessible to most smallholder farmers are highly heterogeneous in quality and vary in quantity. Apart from the knowledge that high quality organic inputs release nutrients in short-term through their interaction with the active SOM fraction (Drinkwater et al., 1996; Palm et al., 2001), the pathways of SOM formation from different quality organic residues are not clearly understood. There is critical need to improve our understanding of resource quality and SOM management interactions in order to translate the available knowledge on soil biological processes into practical management solutions that are adaptable on-farm (Mapfumo et al., 2001a).

The quality of resources available for soil amelioration on smallholder farms still needs characterization using set parameters of the decision tree for organic matter management (Giller, 2000; Palm et al., 1997, 2001). It is only after quality assessments that the impact of such resources on SOM build-up across different agroecological zones can be predicted. Studies by Bonde et al. (1992) suggest that annual inputs to soils contribute to a C build-up in the clay fraction. Given that soils on many smallholder farms of Zimbabwe are sandy and inherently low in clay content, chances of building SOM in such soils are slim (Giller et al., 1997; Mapfumo and Giller, 2001), and yet some farmers still achieve high crop yields.


There is need to understand and document possible SOM pathways and short-term N availability driving crop productivity in these coarse textured soils following use of different quality/quantity organic resources. Of critical importance is how some of these coarse-textured soils continue to maintain reasonable productivity over time. In some instances, the observed yield response patterns and nature of interactions have largely been difficult to explain at field level.

While there is considerable development in our understanding of the role of SOM in nutrient cycling, indices quantitatively defining possible linkages between farmer management practices and soil biological processes need to be developed. Thresholds for defining optimum crop productivity need to be identified in order to come up with management tools similar to those developed for mineral fertilizers (Piha et al., 1998). This study focused on mechanisms of SOM formation and N availability under management systems involving C substrates of different quality. The main objective of the study was based on the understanding that SOM is the driving force behind sustainable crop productivity on depleted sandy soils characterizing the majority of smallholder farms in Zimbabwe. Emphasis was put on establishment of relationships between SOM fractions, N release, fertilizer use efficiency and maize yields, and their links with organic matter management practices by farmers belonging to different social status (Mabeza-Cimedza, 2000; Ramisch, 2004). This was then used to account for the observed fertility gradients within and across farms, and the implications of farmers’ medium- and long-term organic management practices.


1.4 Hypotheses

With this background, the following hypotheses were formulated:

1. Soil fertility gradients are a result of systematic organic matter management by different farmer resource groups.

2. Repeated application of low quality organic matter (high lignin, low N) results in significant build-up of SOM and increased fertilizer use efficiency.

3. The quantity, quality and management of organic nutrient sources applied to soil by smallholder farmers are mainly dependant on the wealth status of individual farmers.

4. Systematic application of organic resources to soil enriches functional SOM fractions resulting in an enhanced supply of nutrients, particularly N, to growing crops.

5. Crop yield responses observed on selected smallholder farms are a consequence of systematic management of organic matter that enriches the size and quality of functional SOM pools and ensures a steady supply of nutrients to crops over time.

1.5 Objectives of the study

The overall objective of the study was to determine the quality and quantity of organic materials applied to soil under different management systems in Zimbabwe by smallholder farmers belonging to different social categories, and how these resources influence SOM formation, soil nutrient supply patterns and efficient use of added mineral fertilizers.


1. Identify management factors influencing the formation of within-field/ farm soil fertility gradients paying particular attention to the organic carbon (C) and nitrogen (N) inputs by farmers across different social gradients.

2. Evaluate the effects of organic resource quality and quantity on maize productivity and determine fertilizer use efficiency of different organic C sources.

3. Characterize the different organic nutrient resources under smallholder farming systems and determine their N supply characteristics in relation to soil profile N changes and maize productivity on sandy soils.

4. Quantify the interactive effects of organic resource quality and quantity on SOM functional pools essential for maintenance of maize productivity under different management systems and soil types

5. Establish the relative influence of annual organic inputs by different farmer resource groups on the size of soil available C pools and how this C accounts for observed maize yield.

1.6 Thesis structure

Chapter 1 gives the problem definition and justification while an overview of relevant literature relating soil organic matter to soil fertility is reported in Chapter 2. In Chapter 3, a detailed description of the study sites where most of the experimental work was carried out is outlined. The selection process of host farmers for on-farm study sites is also described in Chapter 3. Chapter 4 deals with identification of management factors influencing the formation of within-field/farm soil fertility gradients. This was explored through quantification of in situ field biomass in fields differing in productivity. Farmer indices of productivity were


also enumerated and compared with laboratory indices. Chapter 5 compares the short-term effects of organic resource quality on maize productivity under different environments. The benefits of combining organic with mineral nutrient resources were also quantified. The N-supply capacity of organic resources varying in quality and quantity to a growing maize crop and the fate of NO3--N and NH4+-N released

was explored under sandy soil profiles both on-station and on farmers’ fields (Chapter 6). The relative contribution of different quality organic materials to POM fraction of SOM and subsequent nutrient release was quantified on soils differing in texture (Chapter 7). Chapter 8 investigates possible enrichment of the biologically active labile C fractions under smallholder farmer management in different agro-ecosystems. The impact of differential farmer management practices on manifestation of soil fertility gradients was also explored using Zimuto Communal area as a case study. In Chapter 9, findings of the whole study are distilled and the impact of differential organic matter management to fields differing in productivity conceptualized. The study’s overall conclusions and recommendations are also made.



Literature Review

2.1 The soil fertility management paradigm and soil organic matter

Over the last two decades, research has focused on understanding the potential role of SOM as a source of plant nutrients in tropical ecosystems (Swift, 1985; Duxbury et al., 1989; Seward and Woomer, 1993; Barrios et al., 1997; Bergström and Kirchmann, 1998). Some of this research has paid particular attention to factors governing SOM decay and build-up as well as partitioning it into fractions under natural and derived agro-ecosystems in Zimbabwe (King and Campbell, 1994; Mtambanengwe, 2000; Chivenge, 2003). There however, has been limited information on possible avenues to fully exploit SOM for integrated soil fertility management in tropical cropping systems. Studies in temperate environments have shown that the functions of SOM include nutrient supply, water retention, buffering and CEC (Oades et al., 1989; Feller, 1993). However, given the inherent differences in climate, vegetation, soils, topography and land management, chances are that the critical SOM values needed to achieve these services are different under tropical conditions might be different. Observed trends in nutrient depletion on smallholder farms in the tropics have been largely linked to the continued decline in SOM (Sanchez et al., 1997).

While SOM itself is not a direct requirement for plant growth, it acts as a store for nutrients, particularly N, P and S, which become available for plant uptake as the SOM is mineralized (Wander et al., 1994; Woomer et al., 1994). Of great importance in SOM studies is, perhaps, the relationship between organic inputs


and their effect on SOM build-up in the different fractions in relation to plant productivity. The quality of organic inputs, soil textural composition and land-use type may affect the composition and stability of SOM. The substrate quality and its rate of decomposition largely regulate the time over which mineral nutrients are released from an organic resource for plant uptake. The C sources in the organic substrates range from simple sugars to complex organic compounds including lignin, cellulose and polyphenols. High concentrations of some of these secondary compounds in organic inputs have been correlated to SOM stabilization as defined by their mean turnover times (Parton et al., 1987; Oades, 1988).

Research in soil fertility and productivity has been concerned with attempts to fractionate SOM into components and to try to define the role of each component (Elliot and Cambardella, 1991; Swift et al., 1994). According to Feller et al. (1983), SOM can be separated into functional pools each of which is believed to play a particular role in nutrient release, cation exchange, water holding capacity and soil aggregation. Three basic fractions have commonly been associated with SOM and these include the light (active) fraction including the particulate organic matter (POM) and microbial biomass pool, the slow fraction and the humic (passive) fraction (Parton et al., 1988; Duxbury et al., 1989). The different functional pools, based on their decomposition rates and mean residence time in soils, may be important in providing insights on the possible link between SOM dynamics and nutrient availability (Swift and Woomer, 1993).

2.2 Quantification of SOM

While there is no general consensus as to the actual definition of SOM, it usually refers the organic fraction of the soil, which includes plant and animal residues at


various stages of decomposition, cellular fractions and tissues of microbes and substances synthesized by the soil population (Campbell, 1989). Dead organic matter (fine litter and SOM) constitute ~50% C in tropical soils, 60-70% in savanna and about 95% in tropical grasslands (Theng et al., 1989). The humus fraction which is basically associated with clay minerals may constitute up to 80-90% of C in soil (Duxbury et al., 1989). In areas where the soils have a significant clay content, SOM levels are much higher (2% versus 0.5% for most sandy soils) even under similar climates and management practices. Measurements of the biological active pools of SOM (Motavalli et al., 1994; Blair et al., 1997) may help provide insights on the build up of SOM under organic residue management applied to soils of varying textural properties.

Over the past two decades, research has been focused on the fractionation of SOM under natural and agricultural ecosystems through both physical and chemical methods (Stevenson and Elliott, 1989; Chotte et al., 1993; Barrios et al., 1997; Blair et al., 1995, 1997; Chivenge et al., 2000). Physical fractionation involves the disruption of the soil structure by shaking, floatation, and separation of organic fractions according to density, wet sieving and sedimentation. Chemical procedures separate humic and non-humic substances in acid or alkali. Much of the soil ‘humus’ consists of humin, humic acid and fulvic acids, all of which are collectively referred to as humic substances, but these have not been found to be closely related to SOM functions (Stevenson and Elliott, 1989). It is the non-humic substances including various classes of biochemical compounds such as carbohydrates, proteins and lipids that may be responsible for long term nutrient release. However, no ideal method has been identified to separate most of these compounds from soil due the complex nature of SOM. Both physical and chemical


fractionation methods seem to have had success in SOM studies in approximating SOM pool sizes (Feigl et al., 1995; Magid et al., 1996).

2.3 Functional pools of SOM

2.3.1 Coarse light fraction

The coarse light fraction is also referred to as the labile or POM fraction. It largely consists of a range of different products ranging from unprotected rapidly mineralizable components of plant debris and soil fauna to the more recalcitrant compounds such as lignin and polyphenols. By definition, it is assumed to be that organic fraction lying between 53-2000 µm with a wide C:N ratio of between 15-40 and constitutes 45-65% of total SOM (Sollins et al., 1984; Anderson and Ingram, 1993; Okalebo et al., 1993). Although it is regarded as highly labile, it does not constitute the majority of the active SOM pool and has been known to vary within and between seasons (Boone, 1994; Woomer et al., 1994). Residue inputs and climate are the main factors controlling the POM pool. The greater part of this fraction has a short turnover period ranging from a few days to a few years. The light fraction of SOM plays an intermediary role between plants and humus. It has been reported to be a major source of N and other readily decomposable plant compounds. Changes in the POM fraction often reflect changes in organic inputs.

2.3.2 Microbial biomass fraction

The microbial biomass pool (the active fraction) is highly labile and is the SOM fraction with the most rapid turnover rate (Paul and Clark, 1989). This pool is unprotected and constitutes a transformation matrix for organic matter in soil and acts as a reservoir for plant labile nutrients. Because it is living, this pool responds quickly to stresses in the environment or changes in organic matter inputs than


does SOM as a whole (Theng et al., 1989; Woomer et al., 1994). Measurable changes in microbial biomass may reflect changes in land management long before such changes are reflected in total SOM. It constitutes between 1 to 5% of total SOM (Henis, 1986) although some studies in natural tropical woodlands has shown higher concentrations (Anderson and Domsch, 1989; Srivastava and Singh, 1991; Kirchmann and Eklund, 1994).

2.3.3 Heavy fraction

This fraction is humified soil comprising physically protected and/ or chemical forms of organic matter which are resistant to decomposition. The fraction’s turnover time ranges between 20 to 40 years for ‘slow soil’ and up to 200 to 1000 years for ‘passive soil’ depending on degree of physical disturbance (Anderson and Ingram, 1989). The heavy fraction (>1.6 g cm-3) contributes 30-50% of total SOM and may contain materials with a narrow C:N (Meijboom et al., 1995). Tillage, aggregate disruption and soil particle-size distribution control the pool size. It is a biologically passive pool, and is sometimes loosely referred to as the ‘humus’ representing organic matter adsorbed on mineral surfaces or contained in microaggregates. Organic matter in this fraction is found in close association with clay and silt and hence is physically protected from microbial attack.

High clay content in soil is considered a factor that promotes C stabilization through bonding of organic colloids with mineral surfaces (Tiessen and Stewart, 1983; Motavalli et al., 1994). Although humus decomposition is slow, there is a low but continual release of nutrients as the components of this fraction decompose. This fraction releases more mineral N than other SOM fractions in the long term and contains the highest population of soil microorganisms (Jenkinson and


Rayner, 1977). The passive pool has a very high CEC (100-300 cmol(c) kg-1), and

therefore contributes significantly to the CEC of low-clay or highly weathered soils. Organic matter in this fraction has been reported to undergo slow changes during cultivation, thus is likely to contribute little to the short- or medium-term fertility of soils (Meijboom et al., 1995).

2.4 Causes of SOM decline

2.4.1 Tillage

Different SOM fractions mineralize nutrients at different rates under different management practices. It is not the loss of soil C that poses a threat to smallholder farmers, but rather the decline in crop yields resulting from SOM-associated properties. The efficiency with which nutrients are recycled within existing cropping systems are dependant on SOM (Swift and Woomer, 1994). The quality and quantity of SOM can vary monthly, depending on site conditions. In addition to land degradation and erosion processes, continuous cropping can negatively affect SOM levels of most agricultural soils. Upon cultivation, organic material in soil disintegrates rapidly to enter finer, mineral-associated organic pools which during their subsequent mineralization, contributing significantly to the soils’ available nutrient pool. Generally, tillage results in the disruption of soil aggregates (Six et al., 2002) and improved aeration. This increases microbial activity, and hence the rate of SOM decomposition, as microorganisms gain access to intra-aggregate organic matter (Tiessen and Stewart, 1983). Tillage alters lateral distribution of organic matter by physically importing topsoil into lower depths.

The decline in SOM is also accelerated when the rate at which C is added to the soil system is exceeded by C losses due to decomposition under different land


management such as tillage. Under mulching or minimum tillage, SOM accumulates but is restricted to the surface while conventional tillage that incorporates crop residues may affect SOM contents at lower depths (Elwell and Norton, 1988; Vogel, 1994; Grant, 1995). Known consequences of SOM loss include the reduction in soil nutrient supply and storage capacity, reduced soil aggregate stability, reduction in soil biological activity and increased susceptibility to erosion (Srivastava and Singh, 1989).

2.4.2 Erosion

Both wind and rain play a predominant role in distribution of organic matter in natural and arable systems through their erosive processes. Erosion not only affects the direct distribution of organic matter in productive environments, but may have long term consequences on plant productivity through depletion of labile SOM pools (Swift and Woomer, 1994). Immediate effects of soil erosion are not only the declines in soil fertility (Elwell and Stocking, 1988), but also the potential increase in floods and salinization of surface water (Murphy, 2002), absolute decline of arable and grazing land (Janzen et al., 2002) leading to a reduction in agricultural and livestock outputs. Organic matter decline in agricultural systems is exacerbated by overexploitation of arable land by man (Bunders, 1990). Janzen et

al., (2002) identified three ways in which erosion can affect organic matter. These

include either physical removal of organic matter from the site, mixing of subsoil into the surface layer by stripping the surface away or deposition of soil eroded from elsewhere in the landscape. The effects of erosion vary from place to place across the landscape.


2.5 Building SOM?

Use of organic matter inputs by the majority of smallholder farmers is often aimed at improving the physical structure of the soil and providing nutrients to growing crops with little emphasis on the biological aspect (Woomer et al., 1994). The substrate quality and its rate of decomposition largely regulate the time over which mineral nutrients are released from an organic resource for plant uptake. The C sources in the organic substrates range from simple sugars to complex organic compounds including lignin, cellulose and polyphenols. High concentrations of some of these secondary compounds in organic inputs have been correlated to SOM stabilization (Parton et al., 1987; Oades, 1988).

High quality organic materials, defined on the basis of their high nitrogen (N) concentration relative to lignin and polyphenols, have been known to have fast turnover rates, and poor precursors for SOM build-up (Palm et al., 1997; Giller et

al., 1998). Given the relative scarcity of high quality resources on-farm, there is

need to consider a possible complementary role of low quality organic materials in the development of soil fertility technologies. Low quality organic resources may be good precursors to SOM build-up because of their low turnover rates, and are therefore likely to significantly influence the spatial and temporal distribution of SOM in arable lands.

Application of large amounts of lignified materials or those rich in polyphenols have the potential to allow SOM accumulation since they have mean resident time of >5 years (Melillo et al., 1989). Studies by Bonde et al. (1992) suggest that annual inputs seem to simultaneously contribute to a C build-up in the clay fraction. The relative proportion of clay in soil may be important in promoting SOM


stabilization through bonding of organic colloids with mineral surfaces (Tiessen and Stewart, 1983; Motavalli et al., 1994). Soils on many smallholder farms of Zimbabwe are sandy with mean clay contents rarely exceeding 60 g clay kg-1 soil. Given the critical role that SOM plays in low input cropping systems, what are the chances for building SOM under such conditions? Giller et al. (1997) and Palm et

al. (2001a) both concluded that chances of building SOM in sandy soils are slim as

these soils have no capacity to store and protect critical SOM levels required to sustain crop productivity.

2.6 SOM and Nutrient management strategies by smallholder farmers As low-input agricultural systems remain dominant in sub-Saharan Africa including Zimbabwe, it is essential to improve understanding of the functioning of SOM under smallholder management. There is little available information on the degree to which overall farm management affects the various functions of the component parts of SOM. Smallholder farmers in Zimbabwe clearly recognize the importance of soil fertility and conservation (Mugwira and Shumba, 1986; Murwira and Mukamuri, 1998; Mapfumo and Giller; 2001), which is almost entirely dependant on locally available resources. There is general knowledge that application of organic residues improves the physical conditions of soil although information as to why this happens is still scanty (Sanchez et al., 1989). Farmer manipulation of the soil resource base differs in intensity partly because of the limited availability of either nutrient source or a result of differences in farmers’ conceptualization of soil fertility management. The issue of resource allocation influences production goals and is of direct relevance to soil fertility management. It therefore calls for a more direct intervention to improve soil status while at the same time strengthening farmer knowledge and skills.


Smallholder farmers have, over time, found widespread use of locally available forms of organic nutrient sources such as livestock manures, woodland litter, green manures, composted materials, household waste and crop residues (Campbell et al., 1998; Mapfumo and Giller, 2001). However, the negative nutrient balances, estimated at -22 kg N ha-1,-2.5 kg P ha-1 and -15 kg K ha-1 from arable lands (Smaling et al., 1997), are suggestive of management practices that are purely extractive with inadequate nutrient inputs to balance the system (Grant, 1995). The socio-economic boundaries within which farmers operate are inundated with numerous constraints. For example, crop residues have alternative uses as dry season livestock feed and/ or livestock bedding during the rainy months in Zimbabwe (Murwira, 1993; Nzuma et al., 1998). Manure application is a preserve of cattle owners, while composting is often too labour intensive. Overall, the quantities of organic nutrient inputs available to farmers are limited (Mapfumo and Giller, 2001).

Farmers’ options for soil fertility replenishment may be grouped into three broad categories. These include (i) use of mineral fertilizers, (ii) crop sequences and intercrops with N2-fixing grain legumes, green manures and trees, and (iii)

livestock manure, crop residues and other forms of organic nutrient sources from within and around the farm (Mugwira and Murwira, 1997; Buresh and Giller, 1998). In addition to supplying nutrients and improving soil physical properties, organic inputs can also lead to the formation of SOM (Woomer and Swift, 1994). However, SOM formation can be controlled to some extent by the quality, quantity and management of these organic residues.


2.6.1 Livestock manure

Livestock manure, cattle manure in particular, is a traditional source of plant nutrients and can be rated as one of cheapest sources of organic fertilizer in many smallholder farming systems (Mugwira, 1984; Mugwira and Murwira, 1997). Manure application to soil results in increases in soil pH, infiltration rate, water holding capacity and decreased bulk densities (Grant, 1967; Murwira, 1993). Apart from supplying N, several studies have demonstrated the importance of manure as a major source micro-nutrients (Grant, 1967; Nhamo, 2001). The quality of livestock manure is very variable due to variation in animal diets and manure management before field application. Feeds rich in secondary compounds like lignin and polyphenols are more likely to contribute to increasing SOM levels following application of manure from such feeds. Decomposition studies of some communal area cattle manures by Murwira (1993) and Nyamangara et al. (1999) showed that N release is slow and spread over time. This therefore means that its application may not necessarily benefit the growing crop, but may have advantageous residual effects in the medium- to long-term. However, use of manure is a benefit of livestock owners. Soil C content under manure management is likely to be variable due to differences in the chemical composition of the manures, rate and mode of application and the frequency with which the manure is applied to a particular field.

2.6.2 Green manures

The multiple role of leguminous crops in the smallholder farming systems ranks them highly on the soil fertility agenda (Sanchez, 1995; Giller et al., 1998; Mapfumo, 2000). Apart from supplying plant nutrients, legume green manure can be produced and utilized in situ. Application of legume green manure in arable


farming systems provides a large amount of readily decomposable C and a ready supply of N for soil microorganisms. In Zimbabwe, leguminous species such as

Tephrosia, Crotalaria and Mucuna were recommended as N supply sources to

maize as early as the 1950s (Rattray and Ellis, 1952; Gilbert, 1998). Studies have shown that between 40-80% of applied organic N from high quality residues is added to soil and mineralized to available forms (Haggar et al., 1993; Palm, 1995).

In cereal cultivation, N contributions from high quality organic resources such as green manures were estimated to reach high levels of up to 250 kg N ha-1 yr-1 (Giller, 2001). However, information on potential contributions of green manures to the different SOM fractions is still scanty. Although green manures are most beneficial in providing nutrients in the short-term, an option more likely to be appealing to most smallholder farmers, they are likely to have a minimal role in SOM build-up (Palm et al., 2001).

2.6.3 Intercrops and rotations

The practice of legume-cereal intercrops by smallholder farmers is common in Zimbabwe although there is a general lack of awareness on the beneficial role in soil fertility amelioration of this farming method. Groundnut (Arachis hypogaea) has often been the common legume intercropped or grown in rotation with maize (Shumba, 1983; Waddington et al., 1998), although other legumes like cowpea (Vigna unguiculata) (Nhamo et al., 2003) are widely intercropped with maize. Inclusion of legumes in cropping systems may result in erosion control (Chikowo, 2004), smothering of weeds (Mapfumo et al., 2005), soil moisture conservation (Mapfumo and Giller, 2001) and biological nitrogen fixation (Giller, 2001), although the net benefits may vary significantly between seasons.





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