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Little is known about productivity of smallholder maize–pigeonpea intercropping systems in sub-Saharan Africa. We conducted a survey of 277 farm households in Northern Tanzania to assess socio-economic factors, field management characteristics, and their association with productivity of maize–pigeonpea intercrops. On each farm, crop assessments were focused on a field that the farmer identified as most important for food supply. Variables associated with yields were evaluated using linear regression and regression classification. Biomass production ranged between 1.0 and 16.6 for maize, and between 0.2 and 11.9 t ha−1 for pigeonpea (at maize harvest). The corresponding grain yields ranged between 0.1 and 9.5 for maize, and between 0.1 and 2.1 t ha−1 for pigeonpea. Plant density at harvest, number of years the field had been cultivated, slope, weeding, soil fertility class, fertiliser and manure use were significantly associated with variation in maize grain yield, with interactions among the factors. Fields on flat and gentle slopes with plant density above 24,000 ha−1 had 28% extra yields when fertiliser was applied, while less than 24,000 plants ha−1 yielded 16% extra yield when manure was applied. Plant density at harvest was the key factor associated with pigeonpea yield; fields with densities above 24,000 plants ha−1 yielded an average of 1.4 t ha−1, while less than 24,000 plants ha−1 yielded 0.5 t ha−1. We conclude that performance of intercrops can be enhanced through application of organic and inorganic nutrient sources, and agronomic interventions including weeding, implementing soil conservation measures on steep slopes and optimising plant density.

African swine fever (ASF) is a highly contagious fatal infectious disease of pigs and wild suids. The disease has a worldwide occurrence and significant impact on pig production. Two adult intensively raised large white boars from two farms in Jos with a history of sudden death were diagnosed of ASF between July and August 2019. Post‐mortem examination of carcasses grossly showed splenomegaly, haemorrhagic lymphadenitis and hepatomegaly with severe congestion. The kidneys were enlarged and had generalized petechiae and blood clot in the pelvis. The heart was moderately enlarged. Microscopic examination of the spleen and lymph nodes revealed severe lymphocytic depletion, haemorrhage and severe haemosiderosis. The liver was severely congested with focal coagulative necrosis of the hepatocytes. The kidneys were severely congested and showed renal tubular necrosis with few tubular protein casts. Tissue samples were confirmed to be positive for African swine fever virus (ASFV) by polymerase chain reaction (PCR) assay, and phylogenetic analysis revealed that the isolate belonged to genotype I., African swine fever is a highly contagious fatal infectious disease of pigs with a worldwide occurrence and economic importance. Two adult large white boars from two farms in Jos were diagnosed with African swine fever in 2019 through gross and histopathological evaluations, viral isolation and polymerase chain reaction. Sequences obtained were compared and deposited in the GenBank and were accessioned MN888693 and MN888694 and the phylogram showed that the ASFV belongs to genotype I.

Explicit spatial information about crop types on smallholder farms is important for the development of local precision agriculture. However, due to highly fragmented and heterogeneous cropland landscapes, fine-scale mapping of smallholder crops, based on low- and medium-resolution satellite images and relying on a single machine learning (ML) classifier, generally fails to achieve satisfactory performance. This paper develops an ensemble ML-based framework to improve the accuracy of parcel-level smallholder crop mapping from very high spatial resolution (VHSR) images. A typical smallholder agricultural area in central China covered by WorldView-2 images is selected to demonstrate our approach. This approach involves the task of distinguishing eight crop-level agricultural land use types. To this end, six widely used individual ML classifiers are evaluated. We further improved their performance by independently implementing bagging and stacking ensemble learning (EL) techniques. The results show that the bagging models improved the performance of unstable classifiers, but these improvements are limited. In contrast, the stacking models perform better, and the Stacking #2 model (overall accuracy = 83.91%, kappa = 0.812), which integrates the three best-performing individual classifiers, performs the best of all of the built models and improves the classwise accuracy of almost all of the land use types. Since classification performance can be significantly improved without adding costly data collection, stacking-ensemble mapping approaches are valuable for the spatial management of complex agricultural areas. We also demonstrate that using geometric and textural features extracted from VHSR images can improve the accuracy of parcel-level smallholder crop mapping. The proposed framework shows the great potential of combining EL technology with VHSR imagery for accurate mapping of smallholder crops, which could facilitate the development of parcel-level crop identification systems in countries dominated by smallholder agriculture.

Indiscriminate antimicrobial use (AMU) in animal production is a driver of antimicrobial resistance globally. There is a need to define sustainable interventions to reduce AMU in small-scale production systems, which currently represent the most widespread farming systems in South East Asia and many low- and middle-income countries. We conducted a before-and-after intervention study on a random sample of small-scale chicken farms in the Mekong Delta of Vietnam from 2016 to 2019. The study included a baseline followed by an intervention phase where farmers were provided with regular veterinary advice on flock health and husbandry, as well as antimicrobial replacement products. Of 102 recruited farms (raising >100 chickens per flock cycle), thirty-five (34.2%) entered the intervention phase, whilst the rest stopped raising chickens, mainly due to suboptimal flock performance. Through the implementation of our intervention, chicken flocks reduced levels of AMU by 66% [adjusted hazard ratio (HR) = 0.34; p = 0.002) from a baseline of 343.4 Animal Daily Doses per 1,000 chicken-days and decreased weekly mortality by 40% (adjusted HR = 0.60; p = 0.005) from a baseline mortality of 1.60 per 100 birds. Chicken bodyweight increased by 100 g (p = 0.002) in intervention flocks. Our findings demonstrate that the provision of veterinary advice can achieve substantial reductions in AMU in small-scale production systems without compromising flock health and productivity.

Achieving SDG2 (zero hunger) in a situation of rapid global population growth requires a continued focus on food production. Farming not merely needs to sustainably produce nutritious diets, but should also provide livelihoods for farmers, while retaining natural ecosystems and services. Rather than focusing on production principles, this article explores the interrelations between farms and farming systems in the global food system. Evaluating farming systems around the world, we reveal a bewildering diversity. While family farms predominate, these range in size from less than 0.1 ha to more than 10,000 ha, and from hand hoe use to machine-based cultivation, enabling one person to plant more than 500 ha in a day. Yet, farming in different parts of the world is highly interdependent, not least because prices paid for farm produce are largely determined by global markets. Furthermore, the economic viability of farming is a problem, globally. We highlight trends in major regions of the world and explore possible trajectories for the future and ask: Who are the farmers of the future? Changing patterns of land ownership, rental and exchange mean that the concept of ‘what is a farm’ becomes increasingly fluid. Next to declining employment and rural depopulation, we also foresee more environmentally-friendly, less external input dependent, regionalised production systems. This may require the reversal of a global trend towards increasing specialisation to a recoupling of arable and livestock farming, not least for the resilience it provides. It might also require a slow-down or reversal of the widespread trend of scale enlargement in agriculture. Next to this trend of scale enlargement, small farms persist in Asia: consolidation of farms proceeds at a snail’s pace in South-east Asia and 70% of farms in India are ‘ultra-small’ – less than 0.05 ha. Also in Africa, where we find smallholder farms are much smaller than often assumed (< 1 ha), farming households are often food insecure. A raft of pro-poor policies and investments are needed to stimulate small-scale agriculture as part of a broader focus on rural development to address persistent poverty and hunger. Smallholder farms will remain an important source of food and income, and a social safety net in absence of alternative livelihood security. But with limited possibilities for smallholders to ‘step-up’, the agricultural engine of growth appears to be broken. Smallholder agriculture cannot deliver the rate of economic growth currently assumed by many policy initiatives in Africa.

This book is a compilation of works by experts in food and nutrition security, following their participation to a workshop on “Local level food and nutrition security and the role of subsistence/smallholder farms”, held in Seville on 9–10 September 2015, as part of the Expo Milan 2015 under the theme “Feeding the planet, energy for life”. It discusses the current role of smallholders in connection with food security and poverty reduction in developing countries. It addresses their opportunities and constraints, by analysing the availability, access to and utilisation of production factors. Due to the relevance of smallholder farms, enhancing their production capacities and their economic and social resilience could produce positive impacts on food security and nutrition at a number of levels.; Cet ouvrage est une compilation de travaux d'experts en sécurité alimentaire et nutritionnelle, suite à leur participation à un atelier sur «La sécurité alimentaire et nutritionnelle au niveau local et le rôle des exploitations de subsistance / petites exploitations», qui s'est tenu à Séville du 9 au 10 septembre 2015, dans le cadre de l'Expo Milan 2015 sous le thème «Nourrir la planète, l'énergie pour la vie». Il examine le rôle actuel des petits exploitants en matière de sécurité alimentaire et de réduction de la pauvreté dans les pays en développement. Il aborde leurs opportunités et contraintes, en analysant la disponibilité, l'accès et l'utilisation des facteurs de production. En raison de la pertinence des petites exploitations agricoles, le renforcement de leurs capacités de production et de leur résilience économique et sociale pourrait avoir des effets positifs sur la sécurité alimentaire et nutritionnelle à plusieurs niveaux.

Assessing and prescribing fertilizer use is critical to profitable and sustainable coffee production, and this is becoming a priority concern for the Robusta coffee industry. In this study, annual survey data of 798 farms across selected Robusta coffee-producing provinces in Vietnam and Indonesia between 2008 and 2017 were used to comparatively assess the fertilizer management strategies in these countries. Specifically, we aimed to characterize fertilizer use patterns in the key coffee-growing provinces and discuss the potential for improving nutrient management practices. Four types of chemical (NPK, super phosphate, potassium chloride and urea) and two of natural (compost and lime) fertilizers were routinely used in Vietnam. In Indonesia, NPK and urea were supplemented only with compost. Farmers in Vietnam applied unbalanced quantities of chemical fertilizers (i.e., higher rates than recommended) and at a constant rate between years whereas Indonesian farmers applied well below the recommended rates because of poor accessibility and financial support. The overuse of chemical fertilizers in Vietnam threatens the sustainability of Robusta coffee farming. Nevertheless, there is a potential for improvement in both countries in terms of nutrient management and sustainability of Robusta coffee production by adopting the best local fertilizer management practices.

Background Poultry farming is widely practiced by rural households in Vietnam and the vast majority of domestic birds are kept on small household farms. However, smallholder poultry production is constrained by several issues such as infectious diseases, including avian influenza viruses whose circulation remains a threat to public health. This observational study describes the demographic structure and dynamics of small-scale poultry farms of the Mekong river delta region. Method Fifty three farms were monitored over a 20-month period, with farm sizes, species, age, arrival/departure of poultry, and farm management practices recorded monthly. Results Median flock population sizes were 16 for chickens (IQR: 10–40), 32 for ducks (IQR: 18–101) and 11 for Muscovy ducks (IQR: 7–18); farm size distributions for the three species were heavily right-skewed. Muscovy ducks were kept for long periods and outdoors, while chickens and ducks were farmed indoors or in pens. Ducks had a markedly higher removal rate (broilers: 0.14/week; layer/breeders: 0.05/week) than chickens and Muscovy ducks (broilers: 0.07/week; layer/breeders: 0.01–0.02/week) and a higher degree of specialization resulting in a substantially shorter life span. The rate of mortality due to disease did not differ much among species, with birds being less likely to die from disease at older ages, but frequency of disease symptoms differed by species. Time series of disease-associated mortality were correlated with population size for Muscovy ducks (Kendall’s coefficient τ = 0.49, p-value

A study was conducted in 2013 to assess opportunities and challenges of integrating dairy cattle into organic pineapple production in Uganda. Thirty organic pineapple farmers were interviewed using a semi-structured questionnaire. The main dairy cattle management systems were tethering (73%) and zero grazing (27%). Average landholding was 1.74 ± 1.06 and 3.75 ± 2.70 ha for zero grazing and tethering systems, respectively. All farms were diversified with various livestock such as cattle, goats, sheep, pigs, and chickens and crops including pineapples, maize, coffee, bananas, beans, sweet potatoes, and cassava. The level of integration of dairy cattle into pineapple production depended on the distance of crop fields from the livestock enterprises. More farms (83%) with pineapple fields closer (< 0.5 km) to the homesteads were able to use cattle manure as fertilizer compared to homesteads (50%) with more distant fields (> 0.5 km). The distance to the homestead did not influence 30% of the farmers who used crop residues for feeding dairy cattle. Farmers perceived cattle diseases and feed scarcity to be the major challenges in dairy farming. The sources of risk on the farms were perceived to be erratic rainfall, limited knowledge, and market for organic products. Majority of farmers (77%) expressed willingness to convert to organic dairy production. Availability of markets for organic dairy products (36%) and reduction of external input use (26%) were the main reasons for farmers’ willingness to convert. Integrating dairy cattle with pineapple production is an opportunity for closed nutrient cycles and income diversification. However, knowledge, access to inputs, and organized markets are needed as incentive for conversion to organic dairy production.

Remote sensing offers a way to map crop types across large spatio-temporal scales at low costs. However, mapping crop types is challenging in heterogeneous, smallholder farming systems, such as those in India, where field sizes are often smaller than the resolution of historically available imagery. In this study, we examined the potential of relatively new, high-resolution imagery (Sentinel-1, Sentinel-2, and PlanetScope) to identify four major crop types (maize, mustard, tobacco, and wheat) in eastern India using support vector machine (SVM). We found that a trained SVM model that included all three sensors led to the highest classification accuracy (85%), and the inclusion of Planet data was particularly helpful for classifying crop types for the smallest farms (

Agricultural production in Ghana should more than double to fulfil the estimated food demand in 2050, but this is a challenge as the productivity of food crops has been low, extremely variable and prone to stagnation. Yield gap estimations and explanations can help to identify the potential for intensification on existing agricultural land. However, to date most yield gap analyses had a disciplinary focus. The objective of this paper is to assess the impact of crop management, soil and household factors on maize (Zea mays) yields in two major maize growing regions in Ghana through an integrated approach. We applied a variety of complementary methods to study sites in the Brong Ahafo and Northern region. Farm household surveys, yield measurements and soil sampling were undertaken in 2015 and 2016. Water-limited potential yield (Yw) was estimated with a crop growth simulation model, and two different on-farm demonstration experiments were carried out in 2016 and 2017. There is great potential to increase maize yields across the study sites. Estimated yield gaps ranged between 3.8 Mg ha−1 (67% of Yw) and 13.6 Mg ha−1 (84% of Yw). However, there was no consistency in factors affecting maize yield and yield gaps when using complementary methods. Demonstration experiments showed the potential of improved varieties, fertilizers and improved planting densities, with yields up to 9 Mg ha−1. This was not confirmed in the analysis of the household surveys, as the large yield variation across years on the same farms impeded the disclosure of effects of management, soil and household factors. The low-input nature of the farming system and the incidence of fall armyworm led to relatively uniform and low yields across the entire population. So, farmers’ yields were determined by interacting, and strongly varying, household, soil and management factors. We found that for highly variable and complex smallholder farming systems there is a danger in drawing oversimplified conclusions based on results from a single methodological approach. Integrating household surveys, crop growth simulation modelling and demonstration experiments can add value to yield gap analysis. However, the challenge remains to improve upon this type of integrated assessment to be able to satisfactorily disentangle the interacting factors that can be managed by farmers in order to increase crop yields.

Smallholder farms represent the largest population of dairy cattle farms in Indonesia. Dairy activities can play an important role to secure the livelihood of smallholder farms. However, small farms face several constraints and challenges to be sustainable in the future. To assess the sustainability of smallholder dairy farms and to understand in what conditions farms are more sustainable, we conducted a study in two districts of the West Java Province. Our method was based on participatory meetings that allowed us to identify "critical features" of the local farming systems, and associated indicators. From discussions with local stakeholders, we proposed 6 "strategic indicators" of sustainability. Five of those indicators were related to the social and economic dimensions of sustainability, which appeared to be crucial in the local context. To assess the sustainability of farms based on those 6 indicators, we collected secondary data from the local cooperative, and carried out a formal field survey to 355 farmers from May to August 2015. Results showed that the most sustainable farms were those who had highest capital and diversified activity. Farms which had low capital but had additional activity were more sustainable than specialized ones. Whereas the level of farm income appears to be linked directly to farm capital, pluriactivity contributes to reduce risks related to dairy business and to gain benefit from synergies between activities. In the future, policies and projects to enhance farm capital and farmers' pluriactivity will be needed to support the sustainability of smallholder farms., Les petites exploitations constituent la majorité des fermes laitières en Indonésie.Les activités laitières jouent un rôle important pour assurer leur subsistance. Cependant, ces exploitations font face à plusieurs contraintes et défis pour être durables à l’avenir. Pour évaluer et identifier les conditions de la durabilité des exploitations laitières, une étude a été menée dans deux districts de la province de Java Ouest. Notre méthode repose sur des entretiens participatifs qui nous ont permis d’identifier des « points critiques » des systèmes d’élevage locaux, et de proposer des indicateurs de durabilité associés. À partir de réunions avec les acteurs locaux, nous avons identifié 6 indicateurs stratégiques. Parmi ces 6 indicateurs, 5relèvent des dimensions sociales et économiques de la durabilité qui sont essentielles dans le contexte local.Pour évaluer la durabilité des exploitations à l’aide de ces 6 indicateurs et comprendre les facteurs qui expliquent les différences dans ces indicateurs, nous avons conduit une enquête auprès de 355 agriculteurs de mai à août 2015. Ces données ont été complétées par des données secondaires fournis par la coopérative sur ces 355 élevages. Les résultats ont montré que les exploitations les plus durables étaient celles qui possédaient le capital le plus élevé et qui étaient pluriactives. Pour les fermes avec un faible capital, celles qui étaient diversifiées étaient plus durables que celles qui étaient spécialisées. Alors que le niveau de capital impacte directement le niveau de revenu, la pluriactivité contribue à réduire les risques liés aux activités laitières et permet de bénéficier des synergies entre les activités. Notre étude souligne l’importance des programmes de crédit en appui aux exploitations et des programmes d’appui à la diversification des ménages ruraux pour accroître la durabilité des petites exploitations.

International audience; Direct seeding mulch-based cropping (DMC) systems are often considered as an efficient way of combining ecological sustainability and economic viability while maintaining or increasing agricultural productivity. This paper describes a modelling analysis of the functioning of family farms in rural settlements of the agrarian reform in the Cerrados of Brazil. The aim was to assess the impact of the introduction of DMC systems with and without cover crops on crop-livestock management and net household income. A bio-economic farm model based on optimization of a utility function under multiple constraints was developed, capturing the interactions between livestock activities and the introduction of DMC systems. The model was run for six farms representing three farm types in the study area: 1) subsistence-oriented mixed crop-livestock farms; 2) market-oriented dairy farms; and 3) mixed crop-livestock farms, oriented to meat marketing. The following maize-based DMC systems were evaluated: a DMC system with mulch from residues of the previous maize crop and no cover crop, and two DMC systems with a fodder species, Brachiaria brizanta or Cajanus cajan, as cover crop. The simulated adoptability of DMC systems by farmers of the assentamentos depended to a large extent on the yields and feed quality of the fodder species. The modelling results suggested that DMC with C cajan as cover crop was the best suitable option for all simulated farm types. This was mainly explained by its high feed value (expressed in crude protein content). Furthermore, in the process of intensification and specialization in dairy production, farmers were likely to shift from using maize for pig husbandry to feeding it to the dairy cows. The introduction of cover crops in the farm systems was a source of additional animal feed during the dry season that was cheaper than the purchase of feed concentrates, when the size of the dairy herd did not exceed a certain threshold.

© 2017. This version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ In farming communities in Ghana and the West African region, crop residues are often unused and remain available for valorisation. This study has analysed the prospects of electricity generation using crop residues from smallholder farms within defined clusters. Data was collected from 14 administrative districts in Ghana, where surveys were conducted and residue-to-product ratios determined in farmer fields. Thermochemical characterisation of residues was performed in the laboratory. The number of clustered farms, reference residue yields and residue densities were determined to assess the distances within which it would be feasible to supply feedstock to CHP plants. The findings show that in most districts, a minimum of 22–54 larger (10 ha) farms would need to be clustered to enable an economically viable biomass supply to a 1000 kWe plant. A 600 kWe plant would require 13 to 30 farms. Financial analysis for a 1000 kWe CHP plant case indicate that such investment would not be viable under the current renewable feed-in-tariff rates in Ghana; increased tariff by 25% or subsidies from a minimum 30% of investment cost are needed to ensure viability using internal rate of return as an indicator. Carbon finance options are also discussed.

Despite continuing economic growth, Uganda faces persistent challenges to achieve food security. The effectiveness of policy and development strategies to help rural households achieve food security must improve. We present a novel approach to relate spatial patterns of food security to livelihood strategies, including the contribution of on- and off-farm activities to household food availability. Data from 1927 households from the World Bank Living Standards Measurement Study were used to estimate the calorific contribution of livelihood activities to food availability. Consumption of crops produced on-farm contributed most to food availability for households with limited food availability, yet the majority of these households were not food self-sufficient. Off-farm and market-oriented on-farm activities were more important for households with greater food availability. Overall, off-farm income was important in the north, while market-oriented on-farm activities were important in western and central Uganda. Food availability patterns largely matched patterns of agroecological conditions and market access, with households doing worst in Uganda’s drier and remote northeast. Less food-secure households depended more on short-cycle food crops as compared with better-off households, who focused more on plantation (cash) crops, although this varied among regions. Targeting interventions to improve food security should consider such differences in enterprise choice and include options to improve household market access and off-farm income opportunities.

Remote sensing offers a low-cost method for developing spatially continuous crop production statistics across large areas and through time. Nevertheless, it has been difficult to characterize the production of individual smallholder farms, given that the land-holding size in most areas of South Asia (

African farming systems are highly heterogeneous: between agroecological and socioeconomic environments, in the wide variability in farmers’ resource endowments and in farm management. This means that single solutions (or ‘silver bullets’) for improving farm productivity do not exist. Yet to date few approaches to understand constraints and explore options for change have tackled the bewildering complexity of African farming systems. In this paper we describe the Nutrient Use in Animal and Cropping systems – Efficiencies and Scales (NUANCES) framework. NUANCES offers a structured approach to unravel and understand the complexity of African farming to identify what we term ‘best-fit’ technologies – technologies targeted to specific types of farmers and to specific niches within their farms. The NUANCES framework is not ‘just another computer model’! We combine the tools of systems analysis and experimentation, detailed field observations and surveys, incorporate expert knowledge (local knowledge and results of research), generate databases, and apply simulation models to analyse performance of farms, and the impacts of introducing new technologies. We have analysed and described complexity of farming systems, their external drivers and some of the mechanisms that result in (in)efficient use of scarce resources. Studying sites across sub-Saharan Africa has provided insights in the trajectories of change in farming systems in response to population growth, economic conditions and climate variability (cycles of drier and wetter years) and climate change. In regions where human population is dense and land scarce, farm typologies have proven useful to target technologies between farmers of different production objectives and resource endowment (notably in terms of land, labour and capacity for investment). In such regions we could categorise types of fields on the basis of their responsiveness to soil improving technologies along soil fertility gradients, relying on local indicators to differentiate those that may be managed through ‘maintenance fertilization’ from fields that are highly-responsive to fertilizers and fields that require rehabilitation before yields can improved. Where human population pressure on the land is less intense, farm and field types are harder to discern, without clear patterns. Nutrient cycling through livestock is in principle not efficient for increasing food production due to increased nutrient losses, but is attractive for farmers due to the multiple functions of livestock. We identified trade-offs between income generation, soil conservation and community agreements through optimising concurrent objectives at farm and village levels. These examples show that future analyses must focus at farm and farming system level and not at the level of individual fields to achieve appropriate targeting of technologies – both between locations and between farms at any given location. The approach for integrated assessment described here can be used ex ante to explore the potential of best-fit technologies and the ways they can be best combined at farm level. The dynamic and integrated nature of the framework allows the impact of changes in external drivers such as climate change or development policy to be analysed. Fundamental questions for integrated analysis relate to the site-specific knowledge and the simplification of processes required to integrate and move from one level to the next. Keywords: Crop–livestock systems; Soil fertility; Smallholders; Farm types; Simulation modelling

Crop residues are important for livestock feed and nutrient cycling among many other functions on smallholder farming systems of sub-Saharan Africa. The objective of this study was to assess differences in resource endowment, crop productivity and crop residue management in selected sites in southern Africa. Three sites were selected along a gradient of intensification of crop production; Murehwa, Zimbabwe and Ruaca and Gorongosa, central Mozambique. Murehwa and Ruaca have mixed crop-livestock systems with more intensive crop production in Murehwa. Gorongosa is predominantly crop based with small livestock that do not impact on crop production. A combination of land size and cattle ownership was the major attribute that defined wealth status among farmers in mixed crop-livestock systems whereas land size and labor availability were important under crop-based extensification systems. Farm systems were more diverse where livestock was more important. The wealthiest farmers (resource group-RG1) in Murehwa produced an average of 2.2 t ha-1 maize crop residues, and productivity decreased with decrease in resource ownership with the poorest (RG4) achieving only 0.8 t ha-1. In Ruaca 1.3 and 0.5 t ha-1 was produced by RG1 and RG4 respectively, whereas in Gorongosa 0.4 and 0.2 t ha-1 was produced by RG1 and RG4. These crop residues are insufficient to achieve the minimum threshold of soil cover (30%) required for the practice of conservation agriculture. However, they can provide sufficient feed to sustain livestock of RG1 farmers in Murehwa for 63 days and 54 days for RG2 farmers. In Ruaca, they can feed cattle for 37 days for RG1 and 17 days for RG2 farmers. The product of livestock × population density determined the extent and manner in which crop residues are used. The population density limited the extent of the grazing area, increased grazing frequency and reduced the grazing quality leading to the need to supplement animal feed with crop residues. Farmers preferentially allocate crop residues to livestock where labor is available. The crop residues fed to animals allow farmers to increase manure quantity and quality which explains the major differences in crop productivity between the different resource groups. In the absence of cattle, crop residues are burned before the cropping season to facilitate land clearance. In conclusion, land size, cattle ownership and labor availability largely define the intensity of crop production and the fate of crop residues on smallholder farms in southern Africa.

Accurate measurements of crop production in smallholder farming systems are critical to the understanding of yield constraints and, thus, setting the appropriate agronomic investments and policies for improving food security and reducing poverty. Nevertheless, mapping the yields of smallholder farms is challenging because of factors such as small field sizes and heterogeneous landscapes. Recent advances in fine-resolution satellite sensors offer promise for monitoring and characterizing the production of smallholder farms. In this study, we investigated the utility of different sensors, including the commercial Skysat and RapidEye satellites and the publicly accessible Sentinel-2, for tracking smallholder maize yield variation throughout a ~40,000 km2 western Kenya region. We tested the potential of two types of multiple regression models for predicting yield: (i) a “calibrated model”, which required ground-measured yield and weather data for calibration, and (ii) an “uncalibrated model”, which used a process-based crop model to generate daily vegetation index and end-of-season biomass and/or yield as pseudo training samples. Model performance was evaluated at the field, division, and district scales using a combination of farmer surveys and crop cuts across thousands of smallholder plots in western Kenya. Results show that the “calibrated” approach captured a significant fraction (R2 between 0.3 and 0.6) of yield variations at aggregated administrative units (e.g., districts and divisions), while the “uncalibrated” approach performed only slightly worse. For both approaches, we found that predictions using the MERIS Terrestrial Chlorophyll Index (MTCI), which included the red edge band available in RapidEye and Sentinel-2, were superior to those made using other commonly used vegetation indices. We also found that multiple refinements to the crop simulation procedures led to improvements in the “uncalibrated” approach. We identified the prevalence of small field sizes, intercropping management, and cloudy satellite images as major challenges to improve the model performance. Overall, this study suggested that high-resolution satellite imagery can be used to map yields of smallholder farming systems, and the methodology presented in this study could serve as a good foundation for other smallholder farming systems in the world.

Legume technologies are widely promoted among smallholders in southern Africa, providing an opportunity for sustainable intensification. Farms and farming strategies of smallholders differ greatly within any given locality and determine the opportunities for uptake of technologies. We provide an ex-ante assessment of the impact of grain legumes on different types of farms and identify niches for grain legumes in Malawi. After creation of a farm typology, detailed farm characterisations were used to describe the farming system. The characterisations provided the basis for the construction of simplified, virtual farms on which possible scenarios for expanding and intensifying grain legume production were explored using the farm-scale simulation model NUANCES-FARMSIM. Observed yields and labour inputs suggested that maize provides more edible yield per unit area with a higher calorific value and greater labour use efficiency than groundnut and soybean. Crop yields simulated by the model partly confirmed these yield trends, but at farm level maize-dominated systems often produced less food than systems with more grain legumes. Improved management practices such as addition of P-based fertiliser to grain legumes and inoculation of soybean were crucial to increase biological nitrogen fixation and grain yields of legumes and maize, and created systems with increased area of legumes that were more productive than the current farms. Improved legume management was especially a necessity for low resource endowed farmers who, due to little past use of P-based fertiliser and organic inputs, have soils with a poorer P status than wealthier farmers. Economic analyses suggested that legume cultivation was considerably more profitable than continuous maize cropping. Highest potential net benefits were achieved with tobacco, but the required financial investment made tobacco cultivation riskier. Grain legumes have excellent potential as food and cash crops particularly for medium and high resource endowed farmers, a role that could grow in importance as legume markets further develop. For low resource endowed farmers, legumes can improve food self-sufficiency of households, but only if legumes can be managed with P fertiliser and inoculation in the case of soybean. Given that low resource endowed farmers tend to be risk averse and have few resources to invest, the ability of poorer farmers to adopt legume technologies could be limited.

Aiming to translate resilience thinking theory into farming systems design practice, this paper examines fundamental properties of complex systems dynamics and their relation with the mechanisms that govern resilience and transformability in African smallholder agriculture. Agroecosystems dynamics emerge from the aggregation of diverse livelihood strategies in response to changes in the agroecosystem context, and are characterised by non-linearity, irreversibility, convergence/divergence and hysteresis. I examine a number of case studies from Africa to verify three guiding hypotheses in connection to the diversity of rural livelihood strategies: (1) diversity as alternative system regimes; (2) diversity as the result of transformability; (3) diversity determined by changing agricultural contexts. The hierarchy of constraints that determine the space for manoeuvring in agroecosystems is described through the analogy of the Matryoshka nesting dolls: each system level confines and is confined by their immediate sub- and supra-systems. Agricultural contexts, as defined by agro-ecological potential, demography and market connectivity are also dynamic and their trajectory can be described as shifts across stability domains. An example from Kenya shows that household diversity can be described as alternative system regimes, through hysteretic rather than continuous, reversible models. In some particular cases diversity emerges from divergent pathways that may have implied radical transformations in the past, as shown here for rural livelihoods in northern Cameroun. A comparative analysis of East African agroecosystems shows that thresholds in specific variables that may point to the existence of possible tipping points are rather elusive and largely site specific, requiring systematic categorisation of agricultural contexts. While agroecology needs to provide the knowledge base for the ecological intensification of smallholder landscapes, policy and market developments are needed to deal with the Matryoshka effect – or with interactions that are presumably panarchical in certain cases. Desirable shifts in farming systems can only be stimulated by working on both ends simultaneously.

This paper examines a number of agronomic field experiments in different regions of sub-Saharan Africa to assess the associated variability in the efficiencies with which applied and available nutrients are taken up by crops under a wide range of management and environmental conditions. We consider N and P capture efficiencies (NCE and PCE, kg uptake kg-1 nutrient availability), and N and P recovery efficiencies (NRE and PRE, kg uptake kg-1 nutrient added). The analyzed cropping systems employed different soil fertility management practices that included (1) N and P mineral fertilizers (as sole or their combinations) (2) cattle manure composted then applied or applied directly to fields through animal corralling, and legume based systems separated into (3) improved fallows/cover cropscereal sequences, and (4) grain legume-cereal rotations. Crop responses to added nutrients varied widely, which is a logical consequence of the wide diversity in the balance of production resources across regions from arid through wet tropics, coupled with an equally large array of management practices and inter-season variability. The NCE ranged from 0.05 to 0.98 kg kg-1 for the different systems (NP fertilizers, 0.16-0.98; fallow/cover crops, 0.05-0.75; animal manure, 0.10-0.74 kg kg-1), while PCE ranged from 0.09 to 0.71 kg kg-1, depending on soil conditions. The respective NREs averaged 0.38, 0.23 and 0.25 kg kg-1. Cases were found where NREs were[1 for mineral fertilizers or negative when poor quality manure immobilized soil N, while response to P was in many cases poor due to P fixation by soils. Other than good agronomy, it was apparent that flexible systems of fertilization that vary N input according to the current seasonal rainfall pattern offer opportunities for high resource capture and recovery efficiencies in semi-arid areas. We suggest the use of cropping systems modeling approaches to hasten the understanding of Africa's complex cropping systems. (Resume d'auteur)

Traditional farming systems in Sub-Saharan Africa depend primarily on mining soil nutrients. The African green revolution aims to intensify agriculture through the dissemination of integrated soil fertility management (ISFM). This paper develops a robust and operational definition of ISFM based on detailed knowledge of African farming systems and their inherent variability and of the optimal use of nutrients. The authors define ISFM as a set of soil fertility management practices that necessarily include the use of fertilizer, organic inputs and improved germplasm, combined with the knowledge on how to adapt these practices to local conditions, aimed at maximizing agronomic use efficiency of the applied nutrients and improving crop productivity. All inputs need to be managed in accordance with sound agronomic principles. The integration of ISFM practices into farming systems is illustrated with the dual-purpose grain legume–maize rotations in the savannas and fertilizer micro-dosing in the Sahel. Finally, the dissemination of ISFM practices is discussed.

Variability of soil fertility within, and across farms, poses a major challenge for increasing crop productivity in smallholder systems of sub- Saharan Africa. This study assessed the effect of farmers' resource endowment and nutrient manage- ment strategies on variability in soil fertility and plant nutrient uptake between different fields in Gokwe South (ave. rainfall *650 mm year -1 ; 16.3 per- sons km -2 ) and Murewa (ave. rainfall *850 mm year -1 ; 44.1 persons km -2 ) districts, Zimbabwe. In Murewa, resource-endowed farmers applied manure ((3.5 t ha -1 year -1 ) on fields closest to their home- steads (homefields) and none to fields further away (outfields). In Gokwe the manure was not targeted to any particular field, and farmers quickly abandoned outfields and opened up new fields further way from the homestead once fertility had declined, but homefields were continually cultivated. Soil available P was higher in homefields (8-13 mg kg -1 ) of resource-endowed farmers than on outfields and all fields on resource constrained farms (2-6 mg kg -1 ) in Murewa. Soil fertility decreased with increasing distance from the homestead in Murewa while the reverse trend occurred in Gokwe South, indicating the impact of different soil fertility management strategies on spatial soil fertility gradients. In both districts, maize showed deficiency of N and P, implying that these were the most limiting nutrients. It was concluded that besides farmers' access to resources, the direction of soil fertility gradients also depends on agro-ecological conditions which influence resource management strategies.

SAD CT1 ridaura@supagro.inra.fr Nutrient Cycling in Agroecosystems: formerly Fertilizer Research ; FI 2008 1.282; International audience; Smallholder farming systems in sub-Saharan Africa are often nutrient-limited, and therefore imports must be increased to compensate exports and losses. To explore whether the properties of nutrient cycling networks relate to the systems'capability to sustain rural families, we investigated N flows within contrasting crop-livestock systems in Ethiopia, Kenya and Zimbabwe applying concepts from ecological network analysis. Farm households were conceptualised as networks, the compartments were the household and their farming activities which were connected by the N flows. Indicators assessing network size, activity and cycling, and the organisation and diversity of the N flows were compared with system productivity and food self-sufficiency. Results showed that organisation and diversity of N flows to, from and within the farm households differed more between farms of different resource endowments than across sites. The amount of N cycled per household was small and comparable across sites: less than 25 kg N year-1, and for the poor households less than 5 kg N year-1. Poor households with soil N stocks that were 50-60% smaller than wealthier households depended more on external inputs (e.g. a dependence of 65% vs. 45% in Zimbabwe). Productivity was positively related to network size, its organisation and N cycling, but utilisation efficiencies were different across sites in relation to soil N stock and the importance of livestock for N flows. Greater size of the N flow network and its organisation led to increased productivity and food self-sufficiency, reducing dependence, which may increase the adaptability and reliability of smallholder crop-livestock systems.

Information on fertilizer response in cassava in Africa is scarce. We conducted a series of on-farm and on-station trials in two consecutive years to quantify yield responses of cassava to mineral fertilizer in Kenya and Uganda and to evaluate factors governing the responses. Average unfertilized yields ranged from 4.2 to 25.7 t ha-1 between sites and years. Mineral fertilizer use increased yields significantly, but response to fertilizer was highly variable (- 0.2 to 15.3 t ha-1). Average yield response per kg applied nutrient was 37, 168 and 45 and 106, 482 and 128 kg fresh yield per kg of applied N, P and K, respectively in 2004 and 2005. Fertilizer response was governed by soil fertility, rainfall and weed management, but was not influenced by variety, pest and disease pressure and harvest age. Relative N and K yields were positively correlated to SOC and exchangeable K, while response to fertilizer decreased on more fertile soils. Still, fertilizer response varied widely on low fertility soils (e.g. on soils with