The utilization of crop nitrogen (N) status as an in-season diagnosis tool for predicting N needs to maximize grain yield (GY) is a well-established concept in agronomy. However, a cross-species comparison including the characterization of yield components, grain number (GN) and grain weight (GW), to understand the physiological basis behind the GY-crop N status relationship is still missing. The main goal of this study was to perform a cross-species comparison for maize ( L.), rice ( L.), and wheat ( L.) of the relationship between crop N status around anthesis as a GY and GY components prediction diagnosis method. A systematic literature search was carried out for these major field crops, the final dataset (comprising 629 observations) consisted of 15 publications including information on i) shoot biomass and plant N concentration or N nutrition index (NNI) values at anthesis, ii) GY, and iii) GN and/or GW. An analysis was conducted to assess the (slope of the linear models) of GY, GN, and GW to changes in crop NNI status at anthesis. Notably, the crop N status at anthesis demonstrated a strong relationship between both GY (R between 0.66 and 0.93) and GN (R between 0.58 and 0.94) across all crops, with a slightly weaker relationship with GW (R between 0.30 and 0.83). Considerable uncertainty was observed on the GY and GN sensitivity () to N deficiency across all crops. Maize showed the greatest sensitivity of GY to NNI (= 964 g m), with lowest sensitivity for wheat crop (= 496 g m). Regarding GN, rice showed the greatest sensitivity to NNI (= 23859 GN m), whereas maize was less sensitive (= 2673 GN m). While maize exhibited a positive association between NNI and GW (although with considerable uncertainty), this relationship was less evident for rice and wheat crops. Our findings demonstrated that crop N status at anthesis is a better predictor of GY and GN than GW in maize, rice, and wheat. Maize showed the greatest range in observed values for relative GW relative to NNI, highlighting the impact of crop N status on GW determination. These findings contribute to improving the understanding of the importance of achieving adequate crop N status at anthesis as key aspect for yield formation, with implications for both breeding programs and the optimization of on-farm crop N management.

中文翻译：

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作物氮素状况和产量形成：玉米、水稻和小麦田间作物的跨物种比较


利用作物氮 (N) 状态作为当季诊断工具来预测最大化谷物产量 (GY) 所需的氮是农学中的一个成熟概念。然而，仍然缺乏跨物种比较，包括产量组成、粒数 (GN) 和粒重 (GW) 的表征，以了解 GY-作物氮状态关系背后的生理基础。本研究的主要目标是对玉米 (L.)、水稻 (L.) 和小麦 (L.) 进行跨物种比较，了解花期前后作物氮状态之间的关系，作为 GY 和 GY 成分预测诊断方法。对这些主要大田作物进行了系统的文献检索，最终数据集（包含 629 个观测值）由 15 篇出版物组成，包括 i) 芽生物量和植物氮浓度或花期氮营养指数 (NNI) 值，ii) GY 的信息和 iii) GN 和/或 GW。进行了一项分析，以评估 GY、GN 和 GW（线性模型的斜率）对花期作物 NNI 状态变化的影响。值得注意的是，花期作物氮状况表明，所有作物的 GY（R 在 0.66 和 0.93 之间）和 GN（R 在 0.58 和 0.94 之间）之间存在很强的关系，而与 GW 的关系稍弱（R 在 0.30 和 0.83 之间）。所有作物的 GY 和 GN 对氮缺乏的敏感性 () 都观察到相当大的不确定性。玉米表现出 GY 对 NNI 的最大敏感性 (= 964 gm)，对小麦作物的敏感性最低 (= 496 gm)。关于GN，水稻对NNI表现出最大的敏感性（= 23859 GN m），而玉米则不太敏感（= 2673 GN m）。虽然玉米在 NNI 和 GW 之间表现出正相关（尽管存在相当大的不确定性），但这种关系对于水稻和小麦作物来说不太明显。 我们的研究结果表明，在玉米、水稻和小麦中，花期作物氮状况比 GW 更能预测 GY 和 GN。玉米相对于 NNI 的相对 GW 观测值的变化范围最大，突出了作物氮状况对 GW 测定的影响。这些发现有助于提高人们对花期作物氮肥充足状态重要性的理解，这是产量形成的关键因素，对育种计划和农场作物氮肥管理的优化都有影响。