Food security interventions and policies need reliable estimates of crop production and the scope to enhance production on existing cropland. Here we assess the performance of two widely used ‘top-down’ gridded frameworks (Global Agro-ecological Zones and Agricultural Model Intercomparison and Improvement Project) versus an alternative ‘bottom-up’ approach (Global Yield Gap Atlas). The Global Yield Gap Atlas estimates extra production potential locally for a number of sites representing major breadbaskets and then upscales the results to larger spatial scales. We find that estimates from top-down frameworks are alarmingly unlikely, with estimated potential production being lower than current farm production at some locations. The consequences of using these coarse estimates to predict food security are illustrated by an example for sub-Saharan Africa, where using different approaches would lead to different prognoses about future cereal self-sufficiency. Our study shows that foresight about food security and associated agriculture research priority setting based on yield potential and yield gaps derived from top-down approaches are subject to a high degree of uncertainty and would benefit from incorporating estimates from bottom-up approaches.

粮食安全干预措施和政策需要对作物产量和提高现有农田产量的范围进行可靠估计。在这里，我们评估了两个广泛使用的“自上而下”网格框架（全球农业生态区和农业模型比较和改进项目）与替代“自下而上”方法（全球产量差距图集）的性能。全球产量差距图集估计了一些代表主要粮仓的地点在当地的额外生产潜力，然后将结果放大到更大的空间尺度。我们发现自上而下框架的估计值惊人地不可能，估计的潜在产量低于某些地区当前的农业产量。以撒哈拉以南非洲为例说明了使用这些粗略估计来预测粮食安全的后果，在该地区使用不同的方法将导致对未来谷物自给自足的不同预测。我们的研究表明，基于自上而下方法得出的产量潜力和产量差距来确定粮食安全和相关农业研究重点的远见受到高度不确定性的影响，并将受益于结合自下而上方法的估计。