Maize (Zea mays L.) yield and yield variation are both affected by climate and cultivation management. Changing the sowing date (SD) is one of the most commonly used cultivation managements for achieving high yield of maize in North China Plain (NCP). Climate is one of the most important factors in maize yield variation under different SDs. But the yield variation under different SDs and the contribution of each climatic variable remain unclear. In this study, a 7-year field experiment of SDs was used to assess the changing trends of climatic variables under different SDs, and the relative contribution of climatic variables on yield and yield variation of maize were also evaluated. The experiment was conducted at Wuqiao Experimental Station in NCP, with 35 SDs in 7 years from 2013 to 2018, and 2021, totally. Through analyzing the historical meteorological data, our results showed that more photosynthetically active radiation (PAR) distributed in August and September, minimum temperature was increased from April to September, and high temperature days (HTDs) in a year was significantly advanced from 1990 to 2021. These changes in climate caused the optimum SD with both high yield and yield stability was in early- to mid-June, mainly because of the reduction of HTDs in 5 d pre-silking to 5 d post-silking (SS) and increased PAR in SS and silking to harvest (SH). Through variance partitioning analysis, the climatic variables in SS, SH and the whole growth stage (WS) contributed 56 %, 44 %, and 18 % of maize yield variation, respectively. In SS, 7 %, 28 % and 5 % of maize yield variation were explained by HTDs, PAR, and temperature independently. And this contribution was 18 % and 15 % of the PAR and temperature in SH. While in WS, only temperature explained 20 % of the yield variation. Our results highlight the importance of focusing on the yield stability of maize, and for the first time to clarify the differences in maize yield stability under different SDs in NCP. Meanwhile, the relative contribution of climate on yield variation was quantified. This study also proposed and predicted the optimal SDs for high and stable maize yield in NCP. These results will help to study the regional maize production under climate change in the future.

玉米 ( Zea mays L.) 产量和产量变化均受气候和种植管理的影响。改变播期（SD）是华北平原（NCP）玉米高产最常用的栽培管理方式之一。气候是影响不同标准差下玉米产量变化的最重要因素之一。但不同SDs下的产量变化以及每个气候变量的贡献仍不清楚。本研究通过为期 7 年的 SDs 田间试验，评估了不同 SDs 下气候变量的变化趋势，并评估了气候变量对玉米产量和产量变化的相对贡献。实验在华北吴桥实验站进行，2013年至2018年、2021年7年共35个SDs。通过分析历史气象数据，我们的研究结果表明，从 1990 年到 2021 年，光合有效辐射 (PAR) 分布在 8 月和 9 月，最低温度从 4 月到 9 月有所增加，一年中的高温天数 (HTDs) 显着提前。这些气候变化导致具有高产和产量稳定性的最佳 SD 出现在 6 月上旬至中旬，这主要是因为在 5 d 的丝前 5 d 到 5 d 的丝后 (SS) 的 HTDs 减少以及 SS 和丝到收获的 PAR 增加。嘘）。通过方差划分分析，SS、SH和全生育期（WS）的气候变量对玉米产量变异的贡献分别为56%、44%和18%。在 SS 中，7%、28% 和 5% 的玉米产量变化由 HTD、PAR 和温度独立解释。而这一贡献是 SH 中 PAR 和温度的 18% 和 15%。而在 WS 中，只有温度解释了 20% 的产量变化。我们的研究结果强调了关注玉米产量稳定性的重要性，并首次阐明了 NCP 在不同 SD 下玉米产量稳定性的差异。同时，量化了气候对产量变化的相对贡献。本研究还提出并预测了 NCP 玉米高产稳定的最佳 SD。这些结果将有助于研究未来气候变化下的区域玉米生产。并首次阐明了 NCP 在不同 SD 下玉米产量稳定性的差异。同时，量化了气候对产量变化的相对贡献。本研究还提出并预测了 NCP 玉米高产稳定的最佳 SD。这些结果将有助于研究未来气候变化下的区域玉米生产。并首次阐明了 NCP 在不同 SD 下玉米产量稳定性的差异。同时，量化了气候对产量变化的相对贡献。本研究还提出并预测了 NCP 玉米高产稳定的最佳 SD。这些结果将有助于研究未来气候变化下的区域玉米生产。