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Poverty is prevalent in the small-farm sector of many developing countries. A large literature suggests that contract farming—a preharvest agreement between farmers and buyers—can facilitate smallholder market participation, improve household welfare, and promote rural development. These findings have influenced the development policy debate, but the external validity of the extant evidence is limited. Available studies typically focus on a single contract scheme or on a small geographical area in one country. We generate evidence that is generalizable beyond a particular contract scheme, crop, or country, using nationally representative survey data from 6 countries. We focus on the implications of contract farming for household income and labor demand, finding that contract farmers obtain higher incomes than their counterparts without contracts only in some countries. Contract farmers in most countries exhibit increased demand for hired labor, which suggests that contract farming stimulates employment, yet we do not find evidence of spillover effects at the community level. Our results challenge the notion that contract farming unambiguously improves welfare. We discuss why our results may diverge from previous findings and propose research designs that yield greater internal and external validity. Implications for policy and research are relevant beyond contract farming.

Young breeding programs in developing countries, like the Chibas sorghum breeding program in Haiti, face the challenge of increasing genetic gain with limited resources. Implementing genomic selection (GS) could increase genetic gain, but optimization of GS is needed to account for these programs’ unique challenges and advantages. Here, we used simulations to identify conditions under which genomic-assisted recurrent selection (GARS) would be more effective than phenotypic recurrent selection (PRS) in small new breeding programs. We compared genetic gain, cost per unit gain, genetic variance, and prediction accuracy of GARS (two or three cycles per year) vs. PRS (one cycle per year) assuming various breeding population sizes and trait genetic architectures. For oligogenic architecture, the maximum relative genetic gain advantage of GARS over PRS was 12–88%, which was observed only during the first few cycles. For the polygenic architecture, GARS provided maximum relative genetic gain advantage of 26–165%, and was always superior to PRS. Average prediction accuracy declines substantially after several cycles of selection, suggesting the prediction models should be updated regularly. Updating prediction models every year increased the genetic gain by up to 33–39% compared to no-update scenarios. For small populations and oligogenic traits, cost per unit gain was lower in PRS than GARS. However, with larger populations and polygenic traits cost per unit gain was up to 67% lower in GARS than PRS. Collectively, the simulations suggest that GARS could increase the genetic gain in small young breeding programs by accelerating the breeding cycles and enabling evaluation of larger populations.

ObjectivesThis study developed a practical, context-sensitive assessment tool to prioritize occupational risks in agriculture (TIERRA). We applied TIERRA in a case study with smallholder coffee farmers in Uganda (FarmCoUganda) to demonstrate its effectiveness.MethodsTIERRA follows a stepwise, participatory process beginning with an inventory of 80 occupational hazards, reviewed by local experts for clarity and prioritized by community stakeholders through a Delphi workshop. Participants rate the likelihood, severity, and risk of hazards. In the Ugandan case study, 31 stakeholders rated 59 hazards relevant to smallholder coffee farmers in Mbale District.ResultsStakeholders prioritized 23 hazards across six categories: biological, chemical, ergonomic, and physical hazards, each comprising three items, plus five environmental and six psychosocial hazards. “Contact with a pesticide” received the highest overall risk score. “Mosquito bites” emerged as the most significant biological risk. Ergonomic hazards received the highest categorical risk rating.ConclusionTIERRA fosters stakeholder ownership and facilitates dialogue toward action. It supports the development of tailored farmer surveys, training and safer working conditions. It offers a methodological blueprint for adaptation across diverse agricultural contexts, including in LMICs.

Global food security is increasingly jeopardized by climate-induced rainfall volatility, which disproportionately affects nations reliant on traditional agriculture. Although mechanization and modern inputs are critical for agricultural transformation, global yields continue to lag behind the requirements for universal food security. This disparity is often linked to the educational barriers faced by smallholder farmers, which impede the effective adoption of sophisticated productivity-enhancing technologies. Against this backdrop, the present study examines the moderating role of community-based technology hubs in the nexus between climate-smart agriculture and smallholder productivity within the Tanzanian context. Drawing on a primary dataset of 200 respondents and utilizing Structural Equation Modeling (SEM-AMOS 21), the results demonstrate that climate smart agriculture practices significantly augment yields when supported by the infrastructure of community-based technology hubs. These findings suggest that technology hubs bridge the knowledge gap inherent in low formal education settings. Consequently, the study advocates for policy frameworks that prioritize localized, community-centric climate smart agriculture integration to bolster long-term smallholder farmers’ yields and rural livelihoods.

Despite agriculture being a significant contributor to sub-Saharan Africa’s economy, its exploding population puts the region at the highest global risk for food insecurity. Agricultural productivity in the region must meet the growing domestic demand and the needs of global markets. However, the central actors, smallholder farmers, face chronic challenges marketing their produce in high-value markets. While local agricultural policies encourage smallholder farmers and give them education and access, subsistence mindsets are believed to hold them back. This study approaches this challenge from a different, farmer-centric view and proposes a new construct reflecting sustained and meaningful marketing activity—smallholder market participation. With survey data from 464 smallholder farmer-entrepreneurs in Zimbabwe, we reveal how market orientation, access to ancillary services, functional literacy, entrepreneurial abilities, and marketplace metacognition allowed them to beat the odds and grow in the market. We document financial and non-financial outcomes, such as increasing credibility in the marketplace. Our findings offer agribusiness marketers and policymakers more precise indicators of smallholder engagement with markets. The study contributes to marketing theory by highlighting the marketing caliber of an understudied actor, the smallholder farmer.

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.

Agricultural extension is widely recognized as a cornerstone of farmer development, playing a critical role in transferring knowledge that enables farmers to make informed decisions and address production challenges. Its effectiveness, however, hinges on mutual understanding between farmers and extension agents regarding their respective roles. This perspective article reflects on our extensive field experience engaging with more than 500 smallholder farmers across South Africa. We examine farmers' understanding of extension services and juxtapose our insights with existing literature suggesting that smallholders increasingly perceive extension officers primarily as providers of inputs rather than sources of advisory support. We argue that this misinterpretation may contribute to persistent criticisms of the extension system's performance. By highlighting gaps in farmer understanding and the implications for evaluating extension effectiveness, this article calls for renewed attention to the alignment of expectations, communication strategies, and the underlying socio-institutional dynamics influencing extension-farmer relations.

Agriculture is the economy’s backbone for most developing countries. Most of these countries suffer from insufficient agricultural production. The availability of real-time, reliable and farm-specific information may significantly contribute to more sufficient and sustained production. Typically, such information is usually fragmented and often does fit one-on-one with the farm or farm plot. Automated, precise and affordable data collection and dissemination tools are vital to bring such information to these levels. The tools must address details of spatial and temporal variability. The Internet of Things (IoT) and wireless sensor networks (WSNs) are useful technology in this respect. This paper investigates the usability of IoT and WSN for smallholder agriculture applications. An in-depth qualitative and quantitative analysis of relevant work over the past decade was conducted. We explore the type and purpose of agricultural parameters, study and describe available resources, needed skills and technological requirements that allow sustained deployment of IoT and WSN technology. Our findings reveal significant gaps in utilization of the technology in the context of smallholder farm practices caused by social, economic, infrastructural and technological barriers. We also identify a significant future opportunity to design and implement affordable and reliable data acquisition tools and frameworks, with a possible integration of citizen science.

We calculated a simple indicator of food availability using data from 93 sites in 17 countries across contrasted agroecologies in sub-Saharan Africa (>13,000 farm households) and analyzed the drivers of variations in food availability. Crop production was the major source of energy, contributing 60% of food availability. The off-farm income contribution to food availability ranged from 12% for households without enough food available (18% of the total sample) to 27% for the 58% of households with sufficient food available. Using only three explanatory variables (household size, number of livestock, and land area), we were able to predict correctly the agricultural determined status of food availability for 72% of the households, but the relationships were strongly influenced by the degree of market access. Our analyses suggest that targeting poverty through improving market access and off-farm opportunities is a better strategy to increase food security than focusing on agricultural production and closing yield gaps. This calls for multisectoral policy harmonization, incentives, and diversification of employment sources rather than a singular focus on agricultural development. Recognizing and understanding diversity among smallholder farm households in sub-Saharan Africa is key for the design of policies that aim to improve food security.

The association between farm production diversity and dietary diversity in rural smallholder households was recently analysed. Most existing studies build on household-level dietary diversity indicators calculated from 7d food consumption recalls. Herein, this association is revisited with individual-level 24 h recall data. The robustness of the results is tested by comparing household- and individual-level estimates. The role of other factors that may influence dietary diversity, such as market access and agricultural technology, is also analysed. A survey of smallholder farm households was carried out in Malawi in 2014. Dietary diversity scores are calculated from 24 h recall data. Production diversity scores are calculated from farm production data covering a period of 12 months. Individual- and household-level regression models are developed and estimated. Data were collected in sixteen districts of central and southern Malawi. Smallholder farm households (n 408), young children (n 519) and mothers (n 408). Farm production diversity is positively associated with dietary diversity. However, the estimated effects are small. Access to markets for buying food and selling farm produce and use of chemical fertilizers are shown to be more important for dietary diversity than diverse farm production. Results with household- and individual-level dietary data are very similar. Further increasing production diversity may not be the most effective strategy to improve diets in smallholder farm households. Improving access to markets, productivity-enhancing inputs and technologies seems to be more promising.