Yield and yield stability of single cropping maize under different sowing dates and the corresponding changing trends of climatic variables

文献类型： 外文期刊

第一作者： Li, Teng

作者： Li, Teng;Zhang, Xuepeng;Liu, Qing;Liu, Jin;Chen, Yuanquan;Sui, Peng;Yan, Peng

作者机构：

关键词： Maize yield; Yield stability; Sowing dates; Climatic variables

期刊名称：FIELD CROPS RESEARCH （ 影响因子：6.145； 五年影响因子：7.234 ）

ISSN： 0378-4290

年卷期： 2022 年 285 卷

页码：

收录情况： SCI

摘要： 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.

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