Yield gaps between organic and conventional agriculture raise concerns about future agricultural systems which should reduce external inputs and face an unpredictable climate. In the UK, the performance gap is especially severe for wheat that, as a result, has a small and shrinking organic acreage. In organic wheat production, most determinants of crop performance are managed at a rotation level, which leaves cultivar choice as the major decision on a seasonal basis. Yet, conventionally generated cultivar recommendations might be inappropriate to organic farms. Furthermore, uncertainty about field-scale crop performance hinders positive developments of the supply chain of organic grains and seeds. Here, we present a field-scale evaluation of winter wheat cultivars, integrated with an agronomic crop performance survey, across a network of organic farms. The relation between crop performance and climatic patterns is explored, to capitalise past growing seasons in cultivar and management decisions on-farm. Grain yield and grain protein content were linked by a dual relation, positive across environments and negative across cultivars. Feed-grade cultivars showed a relatively high yield (4.5–5.5 t/ha) but low protein (8.5–9.3%), whereas breadmaking and historic cultivars showed higher protein (10.4–11.1%) and lower yields (3.5–4.0 t/ha). Historic phenotypes showed better weed suppressive ability than modern ones, without trade-offs with yield or quality. Multiple regressions showed that weed abundance at wheat anthesis was the main yield predictor. The effects of two different post-emergence weed management strategies were observed. Farms relying on interrow hoeing showed lower weed abundance, but a higher relative abundance of the dominant species than that of those relying on spring tine harrowing. Future wheat breeding and cultivar testing should account for crop-weed relations, weed management strategies and their effects on nutrient use efficiency. Further data collection can inform plant breeding on critical traits for low-input farming and shed light on cultivar-environment-management interactions.

有机农业和传统农业之间的产量差距引发了人们对未来农业系统的担忧，这些系统应该会减少外部投入并面临不可预测的气候。在英国，小麦的性能差距尤其严重，因此有机种植面积小且不断缩小。在有机小麦生产中，作物表现的大多数决定因素在轮作水平上进行管理，这使得品种选择成为季节性的主要决定。然而，传统生成的栽培品种推荐可能不适合有机农场。此外，田间作物表现的不确定性阻碍了有机谷物和种子供应链的积极发展。在这里，我们提出了冬小麦品种的田间规模评估，并结合了农艺作物性能调查，跨越有机农场网络。探索了作物表现与气候模式之间的关系，以利用过去的生长季节来进行栽培品种和农场管理决策。谷物产量和谷物蛋白质含量通过双重关系联系起来，在环境中是正的，在品种之间是负的。饲料级品种表现出相对较高的产量（4.5-5.5 吨/公顷）但蛋白质含量较低（8.5-9.3%），而面包制作和历史品种表现出较高的蛋白质（10.4-11.1%）和较低的产量（3.5-4.0 吨/公顷）哈）。历史表型显示出比现代表型更好的杂草抑制能力，而无需牺牲产量或质量。多元回归表明小麦开花期杂草丰度是主要的产量预测因子。观察了两种不同的芽后杂草管理策略的效果。依靠行间锄耕的农场杂草丰度较低，但优势种的相对丰度高于依靠春叉耙的农场。未来的小麦育种和品种试验应考虑作物与杂草的关系、杂草管理策略及其对养分利用效率的影响。进一步的数据收集可以为植物育种提供低投入农业的关键性状，并阐明品种-环境-管理的相互作用。