From fed by the world to food security : Accelerating agricultural development in Africa

This document presents the results of a search for policies and conditions that can help accelerate agricultural development in Africa. This development has been limited in many countries, as evinced by extreme low fertilizer use, low crop yields, poverty and high food insecurity. The rate of development is quantitatively described for the period 1961–2014 for almost fifty countries, those of the African mainland plus Madagascar, on the basis of data on the average cereal yield and fertilizer use. The way the rainfall impacts on the fertilizer-yield relationship has been studied, by comparing contrasting rainfall transects in Western and Southern Africa, occupied by respectively 19 and 9 countries. On the basis of data from the period 1981–2014, it is shown that soil fertility dominated over rainfall in determining crop yields. Data on the evolution of cereal yield rates over the entire 1961–2014 period have been used for dividing the 49 countries into two main groups, subdivided into four and two classes. In the first group of countries, the yields per hectare increased, in different degrees. The second group includes one class of countries with stagnating yields since 1961, and one that at present has lower yields than in 1961. Here, any increase in food production has come from area expansion. All countries have been categorized on the basis of socio-economic as well as agro-ecological conditions. The comparison of classes enables the identification of stimuli and obstacles for agricultural development. The role of policies for change has been studied as well, with a view to identifying policies that can help accelerate agricultural development in Africa. The dominance of poor soils, often combined with difficult climates, explains in part why agricultural development has been slow. In many places, the low average natural production conditions have resulted in a population density that is much too low to allow for a financially beneficial use of fertilizer and other external agricultural inputs. The high costs of transport and trade, and of food and labor, have seriously hindered agricultural development in many African countries. Market oriented production, for the national or the international market, did not become the driver for development, in contrast to countries with more suitable climates and better soils. A hopeful tendency emerges from this study: African agricultural development is taking off in response to population growth, as is shown by the cereal yield and fertilizer use adoption trends in many countries. Three quarters of the African population lives in countries with positive yield growth rates, with some of them having reached Green Revolution growth rates. Policies and conditions are presented that enable accelerated yield growth, which is a matter of life and death for the last quarter of the population, which lives in countries with no significant or negative yield growth rates, but is also of vital importance fo

Reintegration Of Crop-Livestock Systems In Europe : An Overview

International audienceOngoing specialization of crop and livestock systems provides socioeconomic benefits to the farmer but has led to greater externalization of environmental costs when compared to mixed farming systems. Better integration of crop and livestock systems offers great potential to rebalance the economic and environmental trade-offs in both systems. The aims of this study were to analyze changes in farm structure and review and evaluate the potential for reintegrating specialized intensive crop and livestock systems, with specific emphasis on identifying the co-benefits and barriers to reintegration. Historically, animals were essential to recycle nutrients in the farming system but this became less important with the availability of synthetic fertilisers. Although mixed farm systems can be economically attractive, benefits of scale combined with socio-economic factors have resulted in on-farm and regional specialization with negative environmental impacts. Reintegration is therefore needed to reduce nutrient surpluses at farm, regional and national levels, and to improve soil quality in intensive cropping systems. Reintegration offers practical and cost-effective options to widen crop rotations and promotes the use of organic inputs and associated benefits, reducing dependency on synthetic fertilisers, biocides and manure processing costs. Circular agriculture goes beyond manure management and requires adaptation of both food production and consumption patterns, matching local capacity to produce with food demand. Consequently, feed transport, greenhouse gas emissions, nutrient surpluses and nutrient losses to the environment can be reduced. It is concluded that reintegration of specialized farms within a region can provide benefits to farmers but may also lead to further intensification of land use. New approaches within a food system context offer alternatives for reintegration, but require strong policy incentives which show clear, tangible and lasting benefits for farmers, the environment and the wider community

VHR imagery to quantify crop response to fertilizer and develop business services for smallholders

Food needs arising from the demographic explosion of sub-Saharan Africa can only be met through agricultural intensification. Smallholder systems feature enormous yield gaps, which may be reduced through ISFM and other sustainable intensification practices. However, today’s huge variability in farming practices and returns on investments is likely to exacerbate in the future. Monitoring changes in productivity across scales is a significant challenge in heterogeneous systems, where overall low SOM and nutrient deficiencies prevail. Fortunately, remote sensing can help monitor crop performance at levels of granularity increasingly compatible with smallholder farming. This opens support applications for precision agriculture, allowing the exploitation – rather than the mitigation – of spatial heterogeneity, and the demonstration that enhanced productivity and livelihoods are possible in complex cropping systems

Small farms and development in sub‑Saharan Africa: farming for food, for income or for lack of better options?

Open Access Article; Published online: 15 Oct 2021Most food in sub-Saharan Africa is produced on small farms. Using large datasets from household surveys conducted across many countries, we find that the majority of farms are less than 1 ha, much smaller than previous estimates. Farms are larger in farming systems in drier climates. Through a detailed analysis of food self-sufficiency, food and nutrition security, and income among households from divergent farming systems in Ethiopia, Ghana, Mali, Malawi, Tanzania and Uganda, we reveal marked contrasts in food security and household incomes. In the south of Mali, where cotton is an important cash crop, almost all households are food secure, and almost half earn a living income. Yet, in a similar agroecological environment in northern Ghana, only 10% of households are food secure and none earn a living income. Surprisingly, the extent of food insecurity and poverty is almost as great in densely-populated locations in the Ethiopian and Tanzanian highlands that are characterised by much better soils and two cropping seasons a year. Where populations are less dense, such as in South-west Uganda, a larger proportion of the households are food self-sufficient and poverty is less prevalent. In densely-populated Central Malawi, a combination of a single cropping season a year and small farms results in a strong incidence of food insecurity and poverty. These examples reveal a strong interplay between population density, farm size, market access, and agroecological potential on food security and household incomes. Within each location, farm size is a major determinant of food self-sufficiency and a household’s ability to rise above the living income threshold. Closing yield gaps strongly increases the proportion of households that are food self-sufficient. Yet in four of the locations (Ethiopia, Tanzania, Ghana and Malawi), land is so constraining that only 42–53% of households achieve food self-sufficiency, and even when yield gaps are closed only a small proportion of households can achieve a living income. While farming remains of central importance to household food security and income, our results help to explain why off-farm employment is a must for many. We discuss these results in relation to sub-Saharan Africa’s increasing population, likely agricultural expansion, and agriculture’s role in future economic development

Sustainable intensification in Western Kenya : Who will benefit?

Sustainable Intensification (SI) is essential for Sub-Saharan Africa (SSA) to meet the food demand of the growing population under conditions of increasing land scarcity. However, access to artificial fertilizers is limited, and the current extension system is not effective in serving smallholder farmers. This paper studies farmers' response to improved fertilizer availability under field conditions. Data on farms and families were collected from 267 smallholder farms, while data on fertilizer use and crop response to fertilizer were collected on 127 farm plots. Fertilizer applications and maize yields were measured, and benefit to cost ratio (BCR) of fertilizer application was calculated and to assess its effect on food security. Farm household typologies were used to determine differences in farm endowment and food security classes. Fertilizer application did not significantly improve maize yields in 2017 due to unfavorable weather conditions and pest infestations, whereas significant yield responses were observed in 2018. Consequently, fertilizer application was economically beneficial (BCR >1) for only 45% of the farmers in 2017, compared to 94% in 2018 when 80% of the farmers passed the technology adaptation point (BCR > 2). Surprisingly, economic returns did not vary significantly between household types, implying that fertilizer application provides comparable benefits across all farm types. This is partly explained by the fact that soil fertility varied little between farm types (soil carbon content, for example, showed no correlation with farmer endowment). Still, large differences were observed in farmers' willingness to invest in larger fertilizer applications. Only a small proportion of farmers is expected to increase fertilizer applications as recommended. Our work demonstrates the need to address risks for smallholders and shows that socio-economic aspects are more important than biophysical constraints for policies promoting sustainable intensification.</p

Learning from the soil's memory : Tailoring of fertilizer application based on past manure applications increases fertilizer use efficiency and crop productivity on Kenyan smallholder farms

The large uncertainty in yield response to fertilizer application within smallholder cropping systems in sub-Saharan Africa (SSA) limits efforts aimed at intensifying crop production based on increased fertilizer application. We assessed the key field-scale cause of variability in maize (Zea mays) grain yield response to fertilizer nitrogen (N), phosphorus (P) and potassium (K) in the Sidindi area of Western Kenya based on past manure application, distance from the homestead, and clay and silt contents. We used data from nutrient omission trials conducted on 23 farms over seven consecutive cropping seasons covering the period 2013–2016, without changing treatments or plot location. Treatments included a control and PK, NK, NP and NPK. Accounting for past manure application increased the explained variability in maize yield, and yield response to N, P, and K application. Mean treatment maize grain yield in the control, PK, NK, NP and NPK treatments were 1.0, 2.2, 1.5, 2.9 and 4.5 t ha −1 at 88% dry matter respectively in fields without past manure application, and 2.4, 2.7, 4.4, 4.9 and 5.4 t ha -1 in fields which had received animal manure in at least two out of three seasons prior to the start of the trials. Mean maize yield response to N, P and K application was 2.3, 3.0 and 1.6 t ha −1 respectively in fields without past manure application, and 2.8, 1.1 and 0.6 t ha −1 in fields with past manure application. In the seventh cropping season, past animal manure application contributed a fertilizer equivalent of 28.3, 29.8 and 31.5 kg ha −1 of N, P and K, respectively. At both the onset and at the start of the last season, fields with past animal manure application had on average higher contents of SOC, available P and exchangeable K, yet differences were not always significant within treatments. Accounting for past animal manure application reduces crop fertilizer requirements for P and K as well as decreasing uncertainty in yield response to fertilizer. We conclude that the strong influence of past animal manure application on yield response to fertilizer application merits the inclusion of past manure application as a co-variate in analysis of yield response data from smallholder cropping systems of SSA. </p

Assessing yield and fertilizer response in heterogeneous smallholder fields with UAVs and satellites

Agricultural intensification and efficient use and targeting of fertilizer inputs on smallholder farms is key to sustainably improve food security. The objective of this paper is to demonstrate how high-resolution satellite and unmanned aerial vehicle (UAV) images can be used to assess the spatial variability of yield, and yield response to fertilizer. The study included 48 and 50 smallholder fields monitored during the 2014 and 2015 cropping seasons south-east of Koutiala (Mali), cropped with the five major crops grown in the area (cotton, maize, sorghum, millet and peanuts). Each field included up to five plots with different fertilizer applications and one plot with farmer practice. Fortnightly, in-situ in each field data were collected synchronous with UAV imaging using a Canon S110 NIR camera. A concurrent series of very high-resolution satellite images was procured and these images were used to mask out trees. For each plot, we calculated vegetation index means, medians and coefficients of variation. Cross-validated general linear models were used to assess the predictability of relative differences in crop yield and yield response to fertilizer, explicitly accounting for the effects of fertility treatments, between-field and within-field variabilities. Differences between fields accounted for a much larger component of variation than differences between fertilization treatments. Vegetation indices from UAV images strongly related to ground cover (R2=0.85), light interception (R2=0.79) and vegetation indices derived from satellite images (R2 values of about 0.8). Within-plot distributions of UAV-derived vegetation index values were negatively skewed, and within-plot variability of vegetation index values was negatively correlated with yield. Plots on shallow soils with poor growing conditions showed the largest within-plot variability. GLM models including UAV derived estimates of light interception explained up to 78% of the variation in crop yield and 74% of the variation in fertilizer response within a single field. These numbers dropped to about 45% of the variation in yield and about 48% of the variation in fertilizer response when lumping all fields of a given crop, with Q2 values of respectively 22 and 40% respectively when tested with a leave-field-out procedure. This indicates that remotely sensed imagery doesn’t fully capture the influence of crop stress and management. Assessment of crop fertilizer responses with vegetation indices therefore needs a reference under similar management. Spatial variability in UAV-derived vegetation index values at the plot scale was significantly related to differences in yields and fertilizer responses. The strong relationships between light interception and ground cover indicate that combining vertical photographs or highresolution remotely sensed vegetation indices with crop growth models allows to explicitly account for the spatial variability and will improve the accuracy of yield and crop production assessments, especially in heterogeneous smallholder conditions

Assessing yield and fertilizer response in heterogeneous smallholder fields with UAVs and satellites

Agricultural intensification and efficient use and targeting of fertilizer inputs on smallholder farms is key to sustainably improve food security. The objective of this paper is to demonstrate how high-resolution satellite and unmanned aerial vehicle (UAV) images can be used to assess the spatial variability of yield, and yield response to fertilizer. The study included 48 and 50 smallholder fields monitored during the 2014 and 2015 cropping seasons south-east of Koutiala (Mali), cropped with the five major crops grown in the area (cotton, maize, sorghum, millet and peanuts). Each field included up to five plots with different fertilizer applications and one plot with farmer practice. Fortnightly, in-situ in each field data were collected synchronous with UAV imaging using a Canon S110 NIR camera. A concurrent series of very high-resolution satellite images was procured and these images were used to mask out trees. For each plot, we calculated vegetation index means, medians and coefficients of variation. Cross-validated general linear models were used to assess the predictability of relative differences in crop yield and yield response to fertilizer, explicitly accounting for the effects of fertility treatments, between-field and within-field variabilities. Differences between fields accounted for a much larger component of variation than differences between fertilization treatments. Vegetation indices from UAV images strongly related to ground cover (R2 = 0.85), light interception (R2 = 0.79) and vegetation indices derived from satellite images (R2 values of about 0.8). Within-plot distributions of UAV-derived vegetation index values were negatively skewed, and within-plot variability of vegetation index values was negatively correlated with yield. Plots on shallow soils with poor growing conditions showed the largest within-plot variability. GLM models including UAV derived estimates of light interception explained up to 78% of the variation in crop yield and 74% of the variation in fertilizer response within a single field. These numbers dropped to about 45% of the variation in yield and about 48% of the variation in fertilizer response when lumping all fields of a given crop, with Q2 values of respectively 22 and 40% respectively when tested with a leave-field-out procedure. This indicates that remotely sensed imagery doesn't fully capture the influence of crop stress and management. Assessment of crop fertilizer responses with vegetation indices therefore needs a reference under similar management. Spatial variability in UAV-derived vegetation index values at the plot scale was significantly related to differences in yields and fertilizer responses. The strong relationships between light interception and ground cover indicate that combining vertical photographs or high-resolution remotely sensed vegetation indices with crop growth models allows to explicitly account for the spatial variability and will improve the accuracy of yield and crop production assessments, especially in heterogeneous smallholder conditions

Dynamics of N-P-K demand and uptake in cassava

Fertilizers are required to improve productivity of cassava and meet the increasing demand for cassava as food, feed, or raw material for processing industries. Our objective was to develop nutrition indices for N, P, and K to provide quantitative insight in the dynamics of nutrient demand and uptake of cassava. On-farm experiments were conducted at six locations in Nigeria from 2016 to 2018, across the major cassava growing agro-ecologies of West Africa. Nitrogen, P, and K were applied at different rates. Uptake of nutrients was measured in leaves, stems, and storage roots at 4, 8, and 12 or 14 months after planting (MAP) and used to construct NPK dilution curves and nutrition indices. About 67, 61, and 52% of total N, P, and K were taken up at 4 MAP, with a maximum uptake rate of 0.21, 0.03, and 0.12 g/m2/d for N, P, and K, respectively. Nutrient concentrations in stems and storage roots declined gradually, in contrast to concentrations in the leaves that fluctuated within narrow ranges. Dilution curves and nutrition indices for N, P, and K were established for the first time in cassava. Dilution curves of N, P, and K in the crop for the highest NPK application treatment were described as Nc = 82DM−0.61, Pc = 7.4DM−0.54, and Kc = 43DM−0.54, when total biomass was between 5 and 57 t/ha dry matter (DM). The nutrition indices were linearly related to relative crop biomass. Insight into the nutrient uptake and dilution patterns during the growth cycle can help to understand the temporal nutrient demands of cassava and identify sustainable management practices. Initial ample supply of N and P and moderate K, with extra K top-dress during the second growth phase, will benefit cassava growth and yield. Furthermore, such information provides a basis to develop a dynamic model to simulate nutrient-limited growth of cassava

Quantifying Fertilizer Application Response Variability with VHR Satellite NDVI Time Series in a Rainfed Smallholder Cropping System of Mali

Soil fertility in smallholder farming areas is known to vary strongly on multiple scales. This study measures the sensitivity of the recorded satellite signal to on-farm soil fertility treatments applied to five crop types, and quantifies this fertilization effect with respect to within-field variation, between-field variation and field position in the catena. Plant growth was assessed in 5–6 plots per field in 48 fields located in the Sudano-Sahelian agro-ecological zone of southeastern Mali. A unique series of Very High Resolution (VHR) satellite and Unmanned Aerial Vehicle (UAV) images were used to calculate the Normalized Difference Vegetation Index (NDVI). In this experiment, for half of the fields at least 50% of the NDVI variance within a field was due to fertilization. Moreover, the sensitivity of NDVI to fertilizer application was crop-dependent and varied through the season, with optima at the end of August for peanut and cotton and early October for sorghum and maize. The influence of fertilizer on NDVI was comparatively small at the landscape scale (up to 35% of total variation), relative to the influence of other components of variation such as field management and catena position. The NDVI response could only partially be benchmarked against a fertilization reference within the field. We conclude that comparisons of the spatial and temporal responses of NDVI, with respect to fertilization and crop management, requires a stratification of soil catena-related crop growth conditions at the landscape scale