A common theme emerging from nutrient omission trials conducted extensively across sub-Saharan Africa has been the large variability in yield response to applied nutrients. Yet, little is known about the factors associated with this variability. Therefore, the objectives of this review were to (1) synthesize the available data from nutrient omission trials of maize and rice and quantify spatial variability in yield responses and the probability of attaining specified yield targets; (2) identify the genotypic, environmental, and nutrient management factors associated with yield responses; and (3) provide insights and actionable information for setting priorities for future nutrient management research and development. Here, we provide distributions and expected values of yield response and agronomic efficiencies of nitrogen (N), phosphorus (P), and potassium (K) to serve as benchmarks for improving fertilizer recommendations. We also show that with the combined application of NPK fertilizer, rain-fed maize and rice yields can be raised from the current yields of ~2 Mg ha⁻¹ to 4 Mg ha⁻¹. Yield responses to N, P, and K were in the ratio of 11:6:1 in maize and 13:7:5 in rice, probably arising from differences in uptake requirements and growing environments. K yield responses were 2–3 times higher in rice than in maize. Explorative analysis using machine learning algorithms provided further insights into the possible interaction of agroecology, soil type, and exchangeable cations on the spatial variability in yield responses to N, P, and K in maize and rice. We recommend future research to address site-specific interactions between the applied and indigenous soil nutrients, focusing on optimizing application rates of K, other macronutrients and micronutrients for sustainable intensification of maize and rice production. This study highlights the critical need for balanced fertilization to optimize the productivity and nutrient use efficiencies in rice and maize production in smallholder farming systems in SSA.

在撒哈拉以南非洲广泛开展的养分遗漏试验中出现的一个共同主题是产量对所施养分的反应存在很大差异。然而，人们对与这种可变性相关的因素知之甚少。因此，本次审查的目标是（1）综合玉米和水稻营养缺失试验的可用数据，量化产量响应的空间变异性和达到特定产量目标的概率；(2) 确定与产量反应相关的基因型、环境和养分管理因素；(3) 为确定未来养分管理研究和开发的优先事项提供见解和可操作的信息。在这里，我们提供了氮 (N)、磷 (P)、产量响应和农艺效率的分布和预期值，和钾 (K) 作为改进肥料建议的基准。我们还表明，结合使用 NPK 肥料，雨养玉米和水稻的产量可以从目前约 2 Mg ha 的产量提高^-1至 4 毫克公顷^-1. 玉米对 N、P 和 K 的产量响应比例为 11:6:1，水稻为 13:7:5，这可能是由于吸收需求和生长环境的差异。水稻的钾产量反应是玉米的 2-3 倍。使用机器学习算法进行的探索性分析进一步深入了解了农业生态学、土壤类型和可交换阳离子对玉米和水稻对 N、P 和 K 的产量响应的空间变异性的可能相互作用。我们建议未来的研究解决应用和本地土壤养分之间特定地点的相互作用，重点是优化钾、其他常量营养素和微量营养素的施用率，以实现玉米和水稻生产的可持续集约化。