Spatial heterogeneity of county-level grain protein content in winter wheat in the Huang-Huai-Hai region of China

文献类型： 外文期刊

第一作者： Zhao, Yu

作者： Zhao, Yu;Zhao, Chunjiang;Zhao, Yu;Li, Zhenhai;Yang, Guijun;Duan, Dandan;Fu, Yuanyuan;Zhao, Chunjiang;Wang, Bujun;Liang, Jian

作者机构：

关键词： Geographically weighted regression; Grain protein content; European Center for Medium-range Weather Forecasts (ECMWF) meteorological data; Spatial heterogeneity

期刊名称：EUROPEAN JOURNAL OF AGRONOMY （ 影响因子：5.722； 五年影响因子：6.384 ）

ISSN： 1161-0301

年卷期： 2022 年 134 卷

页码：

收录情况： SCI

摘要： Timely and accurate forecasting of crop grain protein content (GPC) is helpful in planning to acquire the desired target protein levels. A geographically weighted regression (GWR) model was estimated based on meteorological factors to predict the winter wheat GPC at the county level. In the Huang-Huai-Hai region, the grain protein content of winter wheat increased by 0.29% for every 1 degrees increase in latitude. GPC prediction with this model was more precise than that of the multiple linear regressions (MLR) model. The correlation coefficient (R) and Akaike information criterion (AIC) value ranges were 0.26 similar to 0.66 and 1573.86 similar to 1710.70 for the GWR, and 0.06 similar to 0.46 and 1670.18 similar to 1939.76 for the MLR, respectively. Except for radiation in March (RAD03), radiation in April (RAD04) and radiation in May (RAD05), the sensitivity index of other monthly weather indicators to GPC had a high correlation with latitude. With 36 degrees north latitude (L) as the limit, the correlation between RAD03 (R-L< 36 degrees = 0.36, R-L> 36 degrees = 0.29), RAD04 (R-L< 36 degrees = 0.31, R-L> 36 degrees = 0.35) and RAD05 (R-L< 36 degrees = 0.20, R-L> 36 degrees = -0.20) with latitude all showed an opposite trend. We highlight that spatial information needs to be considered when predicting county-level winter wheat GPC.

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