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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.

PURPOSE: The expected increase in demand for food raises concerns about the expansion of agricultural land worldwide. To avoid expansion, we need to focus on increasing land productivity, reducing waste, and shifting human diets. Studies exploring diet shifts so far have ignored competition for land between humans and animals. Our objective was to study the relation between land use, the share of animal protein in the human diet, population size, and land availability and quality. METHODS: We used linear programming to determine minimum land required to feed a population a diet with 0–80 % of the protein derived from terrestrial domestic animals. Populations ranged from 15 million to the maximum number of people that could be supported by the system. The agricultural system in the Netherlands was used as illustration, assuming no import and export of feed and food. Daily energy and protein requirements of humans were fulfilled by a diet potentially consisting of grain (wheat), root and tuber crops (potato, sugar beet), oil crops (rapeseed), legumes (brown bean), and animal protein from ruminants (milk and meat) and monogastrics (pork). RESULTS AND DISCUSSION: Land is used most efficiently if people would derive 12 % of dietary protein from animals (% PA), especially milk. The role of animals in such a diet is to convert co-products from crop production and the human food industry into protein-rich milk and meat. Below 12 % PA, human-inedible products were wasted (i.e., not used for food production), whereas above 12 % PA, additional crops had to be cultivated to feed livestock. Large populations (40 million or more) could be sustained only if animal protein was consumed. This results from the fact that at high population sizes, land unsuitable for crop production was necessary to meet dietary requirements of the population, and contributed to food production by providing animal protein without competing for land with crops. CONCLUSIONS: A land use optimization model including crop and animal production enables identification of the optimal % PA in the diet. Land use per capita was lowest at 12 % PA. At this level, animals optimally consume co-products from food production. Larger populations, furthermore, can be sustained only with diets relatively high in % PA, as land unsuitable for crop production is needed to fulfil their food demand. The optimal % PA in the human diet depended on population size and the relative share of land unsuitable for crop production.

Africa produces around 60% of the rice the continent consumes, relying heavily on rice imports to fulfill the rest of the domestic demand. Over the past 10 years, the rice-agricultural area increased nearly 40%, while average yield remained stagnant. Here we used a process-based crop simulation modelling approach combined with local weather, soil, and management datasets to evaluate the potential to increase rice production on existing cropland area in Africa and assess cropland expansion and rice imports by year 2050 for different scenarios of yield intensification. We find that Africa can avoid further increases in rice imports, and even reduce them, through a combination of cropland expansion following the historical trend together with closure of the current exploitable yield gap by half or more. Without substantial increase in rice yields, meeting future rice demand will require larger rice imports and/or land conversion than now. Here the authors demonstrate that cropland expansion following the historical trend together with closing the current exploitable yield gap by half or more across Africa reduces the continent’s reliance on land conversions and imports by 2050.

Phosphorus (P) is a finite and dwindling resource. Debate focuses on current production and use of phosphate rock rather than on the amounts of P required in the future to feed the world. We applied a two-pool soil P model to reproduce historical continental crop P uptake as a function of P inputs from fertilizer and manure and to estimate P requirements for crop production in 2050. The key feature is the consideration of the role of residual soil P in crop production. Model simulations closely fit historical P uptake for all continents. Cumulative inputs of P fertilizer and manure for the period 1965–2007 in Europe (1,115 kg⋅ha–1 of cropland) grossly exceeded the cumulative P uptake by crops (360 kg⋅ha–1). Since the 1980s in much of Europe, P application rates have been reduced, and uptake continues to increase due to the supply of plant-available P from residual soil P pool. We estimate that between 2008 and 2050 a global cumulative P application of 700–790 kg⋅ha–1 of cropland (in total 1,070–1,200 teragrams P) is required to achieve crop production according to the various Millennium Ecosystem Assessment scenarios [Alcamo J, Van Vuuren D, Cramer W (2006) Ecosystems and Human Well-Being: Scenarios, Vol 2, pp 279–354]. We estimate that average global P fertilizer use must change from the current 17.8 to 16.8–20.8 teragrams per year in 2050, which is up to 50% less than other estimates in the literature that ignore the role of residual soil P.

Although global food demand is expected to increase 60% by 2050 compared with 2005/2007, the rise will be much greater in sub-Saharan Africa (SSA). Indeed, SSA is the region at greatest food security risk because by 2050 its population will increase 2.5-fold and demand for cereals approximately triple, whereas current levels of cereal consumption already depend on substantial imports. At issue is whether SSA can meet this vast increase in cereal demand without greater reliance on cereal imports or major expansion of agricultural area and associated biodiversity loss and greenhouse gas emissions. Recent studies indicate that the global increase in food demand by 2050 can be met through closing the gap between current farm yield and yield potential on existing cropland. Here, however, we estimate it will not be feasible to meet future SSA cereal demand on existing production area by yield gap closure alone. Our agronomically robust yield gap analysis for 10 countries in SSA using location-specific data and a spatial upscaling approach reveals that, in addition to yield gap closure, other more complex and uncertain components of intensification are also needed, i.e., increasing cropping intensity (the number of crops grown per 12mo on the same field) and sustainable expansion of irrigated production area. If intensification is not successful and massive cropland land expansion is to be avoided, SSA will depend much more on imports of cereals than it does today.

Nutrient budgets help to identify the excess or insufficient use of fertilizers and other nutrient sources in agriculture. They allow for the calculation of indicators, such as the nutrient balance (surplus if positive or deficit if negative) and nutrient use efficiency, that help to monitor agricultural productivity and sustainability across the world. We present a global database of country-level budget estimates for nitrogen (N), phosphorus (P) and potassium (K) on cropland. The database, disseminated in FAOSTAT, is meant to provide a global reference, synthesizing and continuously updating the state of the art on this topic. The database covers 205 countries and territories, as well as regional and global aggregates, for the period from 1961 to 2020. Results highlight the wide range in nutrient use and nutrient use efficiencies across geographic regions, nutrients, and time. The average N balance on global cropland has remained fairly steady at about 50–55 kg ha−1 yr−1 during the past 15 years, despite increasing N inputs. Regional trends, however, show recent average N surpluses that range from a low of about 10 kg N ha−1 yr−1 in Africa to more than 90 kg N ha−1 yr−1 in Asia. Encouragingly, average global cropland N use efficiency decreased from about 59 % in 1961 to a low of 43 % in 1988, but it has risen since then to a level of 55 %. Phosphorus deficits are mainly found in Africa, whereas potassium deficits occur in Africa and the Americas. This study introduces improvements over previous work in relation to the key nutrient coefficients affecting nutrient budgets and nutrient use efficiency estimates, especially with respect to nutrient removal in crop products, manure nutrient content, atmospheric deposition and crop biological N fixation rates. We conclude by discussing future research directions and highlighting the need to align statistical definitions across research groups as well as to further refine plant and livestock coefficients and expand estimates to all agricultural land, including nutrient flows in meadows and pastures. Further information is available from https://doi.org/10.5061/dryad.hx3ffbgkh (Ludemann et al., 2023b) as well as the FAOSTAT database (https://www.fao.org/faostat/en/#data/ESB; FAO, 2022a) and is updated annually.

Wheat yields in Ethiopia need to increase considerably to reduce import dependency and keep up with the expected increase in population and dietary changes. Despite the yield progress observed in recent years, wheat yield gaps remain large. Here, we decompose wheat yield gaps in Ethiopia into efficiency, resource, and technology yield gaps and relate those yield gaps to broader farm(ing) systems aspects. To do so, stochastic frontier analysis was applied to a nationally representative panel dataset covering the Meher seasons of 2009 and 2013 and crop modelling was used to simulate the water-limited yield (Yw) in the same years. Farming systems analysis was conducted to describe crop area shares and the availability of land, labour, and capital in contrasting administrative zones. Wheat yield in farmers’ fields averaged 1.9 t ha − 1 corresponding to ca. 20% of Yw. Most of the yield gap was attributed to the technology yield gap (> 50% of Yw) but narrowing efficiency (ca. 10% of Yw) and resource yield gaps (ca. 15% of Yw) with current technologies can nearly double actual yields and contribute to achieve wheat self-sufficiency in Ethiopia. There were small differences in the relative contribution of the intermediate yield gaps to the overall yield gap across agro-ecological zones, administrative zones, and farming systems. At farm level, oxen ownership was positively associated with the wheat cultivated area in zones with relatively large cultivated areas per household (West Arsi and North Showa) while no relationship was found between oxen ownership and the amount of inputs used per hectare of wheat in the zones studied. This is the first thorough yield gap decomposition for wheat in Ethiopia and our results suggest government policies aiming to increase wheat production should prioritise accessibility and affordability of inputs and dissemination of technologies that allow for precise use of these inputs.

Ethiopia has achieved the second highest maize yield in sub-Saharan Africa. Yet, farmers’ maize yields are still much lower than on-farm and on-station trial yields, and only ca. 20% of the estimated water-limited potential yield. This article provides a comprehensive national level analysis of the drivers of maize yields in Ethiopia, by decomposing yield gaps into efficiency, resource and technology components, and accounting for a broad set of detailed input and crop management choices. Stochastic frontier analysis was combined with concepts of production ecology to estimate and explain technically efficient yields, the efficiency yield gap and the resource yield gap. The technology yield gap was estimated based on water-limited potential yields from the Global Yield Gap Atlas. The relative magnitudes of the efficiency, resource and technology yield gaps differed across farming systems; they ranged from 15% (1.6 t/ha) to 21% (1.9 t/ha), 12% (1.3 t/ha) to 25% (2.3 t/ha) and 54% (4.8 t/ha) to 73% (7.8 t/ha), respectively. Factors that reduce the efficiency yield gap include: income from non-farm sources, value of productive assets, education and plot distance from home. The resource yield gap can be explained by sub-optimal input use, from a yield perspective. The technology yield gap comprised the largest share of the total yield gap, partly due to limited use of fertilizer and improved seeds. We conclude that targeted but integrated policy design and implementation is required to narrow the overall maize yield gap and improve food security.

Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that (1) crop models cannot account for all relevant climate change impacts and adaptation options, and (2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semi-quantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world.

Ensuring an adequate food supply in systems that protect environmental quality and conserve natural resources requires productive and resource-efficient cropping systems on existing farmland. Meeting this challenge will be difficult without a robust spatial framework that facilitates rapid evaluation and scaling-out of currently available and emerging technologies. Here we develop a global spatial framework to delineate 'technology extrapolation domains' based on key climate and soil factors that govern crop yields and yield stability in rainfed crop production. The proposed framework adequately represents the spatial pattern of crop yields and stability when evaluated over the data-rich US Corn Belt. It also facilitates evaluation of cropping system performance across continents, which can improve efficiency of agricultural research that seeks to intensify production on existing farmland. Populating this biophysical spatial framework with appropriate socio-economic attributes provides the potential to amplify the return on investments in agricultural research and development by improving the effectiveness of research prioritization and impact assessment.