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.

Global support for Conservation Agriculture (CA) as a pathway to Sustainable Intensification is strong. CA revolves around three principles: no-till (or minimal soil disturbance), soil cover, and crop rotation. The benefits arising from the ease of crop management, energy/cost/time savings and soil and water conservation led to widespread adoption of CA, particularly on large farms in the Americas and Australia, where farmers harness the tools of modern science: highly-sophisticated machines, potent agrochemicals and biotechnology. Over the past ten years CA has been promoted among smallholder farmers in the (sub-) tropics, often with disappointing results. Growing evidence challenges the claims that CA increases crop yields and builds-up soil carbon although increased stability of crop yields in dry climates is evident. Our analyses suggest pragmatic adoption on larger mechanized farms, and limited uptake of CA by smallholder farmers in developing countries. We propose a rigorous, context-sensitive approach based on Systems Agronomy to analyze and explore sustainable intensification options, including the potential of CA. There is an urgent need to move beyond dogma and prescriptive approaches to provide soil and crop management options for farmers to enable the Sustainable Intensification of agriculture.

Most 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.

The concept of technology adoption (along with its companions, diffusion and scaling) is commonly used to design development interventions, to frame impact evaluations and to inform decision-making about new investments in development-oriented agricultural research. However, adoption simplifies and mischaracterises what happens during processes of technological change. In all but the very simplest cases, it is likely to be inadequate to capture the complex reconfiguration of social and technical components of a technological practice or system. We review the insights of a large and expanding literature, from various disciplines, which has deepened understanding of technological change as an intricate and complex sociotechnical reconfiguration, situated in time and space. We explain the problems arising from the inappropriate use of adoption as a framing concept and propose an alternative conceptual framework for understanding and evaluating technological change. The new approach breaks down technology change programmes into four aspects: propositions, encounters, dispositions and responses. We begin to sketch out how this new framework could be operationalised.

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia’s Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.