Resource use and food self-sufficiency at farm scale within two agro-ecological zones of Rwanda

Revisiting Rwanda’s agricultural intensification policy: benefits of embracing farmer heterogeneity and crop-livestock integration strategies

The government of Rwanda is promoting agricultural intensification focused on the production of a small number of targeted commodities as a central strategy to pursue the joint policy goals of economic growth, food security and livelihood development. The dominant approach to increase the productive capacity of the land, crops and animal resources has been through large-scale land consolidation, soil fertility management, and the intensive use of biotechnology and external inputs. However, evidence has shown that many Rwandan farmers, who employ various strategies and mixed farming practices based on their specific economic, social, and environmental circumstances, face difficulties adopting the singular prescribed approach to become more productive, modern commodity producers. To empirically explore diversity in smallholders’ strategies and their contributions to livelihoods and compatibility with the recent intensification policies, we conducted household surveys and in-depth qualitative interviews in rural and peri-urban zones in Rwamagana district in Eastern Rwanda. Our analysis demonstrates how the dominant approach to intensification and specialisation overlooks the heterogeneity and dynamic nature of smallholder strategies. Moreover, our findings illustrate that a comprehensive understanding of farmer heterogeneity is necessary to explain the critical disjuncture between the government’s vision of modern agriculture and the ability of many smallholders to engage with this agenda and may inform opportunities to adapt policies to better align productivity goals and livelihoods. In doing so, we contribute to debates about the current framing of intensification policy that promotes Green Revolution technologies and emphasise alternative pathways for more inclusive and resilient agricultural development in sub-Saharan Africa.

Monitoring and Analyzing Yield Gap in Africa through Soil Attribute Best Management Using Remote Sensing Approaches: A Review

Africa has the largest population growth rate in the world and an agricultural system characterized by the predominance of smallholder farmers. Improving food security in Africa will require a good understanding of farming systems yields as well as reducing yield gaps (i.e., the difference between potential yield and actual farmer yield). To this end, crop yield gap practices in African countries need to be understood to fill this gap while decreasing the environmental impacts of agricultural systems. For instance, the variability of yields has been demonstrated to be strongly controlled by soil fertilizer use, irrigation management, soil attribute, and the climate. Consequently, the quantitative assessment and mapping information of soil attributes such as nitrogen (N), phosphorus (P), potassium (K), soil organic carbon (SOC), moisture content (MC), and soil texture (i.e., clay, sand and silt contents) on the ground are essential to potentially reducing the yield gap. However, to assess, measure, and monitor these soil yield-related parameters in the field, there is a need for rapid, accurate, and inexpensive methods. Recent advances in remote sensing technologies and high computational performances offer a unique opportunity to implement cost-effective spatiotemporal methods for estimating crop yield with important levels of scalability. However, researchers and scientists in Africa are not taking advantage of the opportunity of increasingly available geospatial remote sensing technologies and data for yield studies. The objectives of this report are to (i) conduct a review of scientific literature on the current status of African yield gap analysis research and their variation in regard to soil properties management by using remote sensing techniques; (ii) review and describe optimal yield practices in Africa; and (iii) identify gaps and limitations to higher yields in African smallholder farms and propose possible improvements. Our literature reviewed 80 publications and covered a period of 22 years (1998-2020) over many selected African countries with a potential yield improvement. Our results found that (i) the number of agriculture yield-focused remote sensing studies has gradually increased, with the largest proportion of studies published during the last 15 years; (ii) most studies were conducted exclusively using multispectral Landsat and Sentinel sensors; and (iii) over the past decade, hyperspectral imagery has contributed to a better understanding of yield gap analysis compared to multispectral imagery; (iv) soil nutrients (i.e., NPK) are not the main factor influencing the studied crop productivity in Africa, whereas clay, SOC, and soil pH were the most examined soil properties in prior papers.

Systemic Design for Food Self-Sufficiency in Urban Areas

This article adopts a systemic approach to address the problem of the operationalization of relationships between actors conducive to food self-sufficiency in urban areas. Through the use of Social Network Analysis (SNA), the literature on urban agriculture was analyzed, detecting eight key trends and topic areas. This information was used to design a generic recursive organizational structure with the identification of the key roles and functions for management and governance in the multi-level and multi-stakeholder relationships of a sustainable urban self-sufficient food production system, inspired by the principles of complexity management and organizational cybernetics. Methodologically, this is the first application that combines the exploratory capability of SNA and the recursive structure of the Viable System Model (VSM) to propose applicable organizational structures in any urban area, suggesting a new route for the study and application of systemic thinking in the development of urban agriculture schemes. However, due to the conceptual nature of this work, this study opens a discussion on how we can rethink interactions to seek continuous adaptation in food self-sufficiency, provide tools that foster inclusion, and adapt to every context to support the relevant actors and academics in urban agriculture.

Determining and managing maize yield gaps in Rwanda

Smallholder maize growers are experiencing significant yield gaps due to sub-optimal agricultural practices. Adequate agricultural inputs, particularly nutrient amendments and best management practices, are essential to reverse this trend. There is a need to understand the cause of variations in maize yield, provide reliable early estimates of yields, and make necessary recommendations for fertilizer applications. Maize yield prediction and estimates of yield gaps using objective and spatial analytical tools could provide accurate and objective information that underpin decision support. A study was conducted in Rwanda at Nyakiliba sector and Gashora sector located in Birunga and Central Bugesera agro-ecological zones, with the objectives of (1) determining factors influencing maize yield, (2) predicting maize yield (using the Normalized Difference Vegetation Index (NDVI) approach), and (3) assessing the maize yield gaps and the impact on food security. Maize grain yield was significantly higher at Nyakiliba (1.74 t ha−1) than at Gashora (0.6 t ha−1). NDVI values correlated positively with maize grain yield at both sites (R2 = 0.50 to 0.65) and soil fertility indicators (R2 = 0.55 to 0.70). Maize yield was highest at 40 kg P ha−1 and response to N fertilizer was adequately simulated at Nyakiliba (R2 = 0.85, maximum yield 3.3 t ha−1). Yield gap was 4.6 t ha−1 in Nyakiliba and 5.1 t ha−1 in Gashora. Soil variables were more important determinants of social class than family size. Knowledge that low nutrient inputs are a major cause of yield gaps in Rwanda should prioritize increasing the rate of fertilizer use in these agricultural systems.

Benefits of inoculation, P fertilizer and manure on yields of common bean and soybean also increase yield of subsequent maize

Common bean and soybean yield poorly on smallholder farms in Rwanda. We evaluated the benefits of inoculation combined with P fertilizer and manure on yields of common bean and soybean in three agro-ecological zones (AEZs), and their residual effects on a subsequent maize crop. In the first season, the treatments included inoculum, three rates of manure, and two rates of P fertilizer, with nine replications (three per AEZ). Both legumes responded well to inoculation if applied together with manure and P fertilizer. Grain yields varied from 1.0 t ha^-1 to 1.7 t ha^-1 in unamended control plots to 4.8 t ha^-1 for common bean and 3.8 t ha^-1 for soybean in inoculated plots with both P and manure addition. The response of common bean and soybean to inputs varied greatly between AEZs. In the AEZ with low and erratic rainfall (Bugesera), yields of both legumes and maize were low and maize after soybean failed to yield any grain due to drought. In this regard, early maturing legume varieties are advised in regions of low rainfall. Responses of maize to an input applied to the legumes strongly increased when other inputs were applied together to the legume. This allowed greater maize yields which ranged from 0.8 t ha^-1 in control plots to 6.5 t ha^-1 in treatments previously inoculated with P and manure added for maize grown after common bean and from 1.9 t ha^-1 in control plots to 5.3 t ha^-1 for maize grown after soybean. The amount of N₂-fixed measured using the ¹⁵N-natural abundance method differed between the two legumes and varied between 15 and 198 kg N₂ ha^-1 for common bean and between 15 and 186 kg N₂ ha^-1 for soybean and differed enormously among treatments and AEZs. Application of inputs to the legumes also resulted in enhanced N and P uptake of the subsequent maize. The use of inoculum combined with manure and P fertilizer is a good option for smallholder farmers growing common bean and soybean in rotation with maize. We observed strong effects of environment and call for care when targeting crops and technologies for sustainable crop production.