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作者	单位
商东耀，成林，马青荣，李筱涵，薛昌颖	(1.中国气象局/河南省农业气象保障与应用技术重点开放实验室，河南郑州 450003；2.河南省气象科学研究所，河南郑州 450003)

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中文摘要:

为了解河南省小麦品质与气象条件的关系，利用2017—2019 年河南省72 个县（区）强筋和非强筋小麦品种的287 份小麦样品品质测定资料、对应年份逐旬气象因子和小麦生育期观测数据，通过Pearson 相关分析、线性相关、二次曲线相关和逐步回归等方法，分析了气象因子对小麦主要籽粒品质形成的影响，构建了籽粒粗蛋白含量预报模型，探寻影响河南省强筋和非强筋小麦主要品质指标的关键气象因子。结果表明，河南省强筋小麦粗蛋白、湿面筋含量和降落值都高于非强筋小麦。两类筋型小麦降落值与拔节期以后的温度、日照时数和气温日较差关系密切，其中非强筋小麦降落值与气象因子的关联度较高。籽粒湿面筋含量与气温日较差密切相关，不同筋型小麦湿面筋含量对四月份部分气象因子的响应存在显著差异。从小麦籽粒粗蛋白含量预估模型可知，两类小麦粗蛋白含量均受气象条件的影响，但影响因子有所不同，非强筋小麦粗蛋白含量预估模型较为复杂。

英文摘要:

In order to understand the relationship between wheat quality and meteorological conditions in Henan Province, 287 wheat samples from 72 counties (districts) with strong and non strong gluten wheat varieties from 2017 to 2019, as well as meteorological factors and wheat development period observation data from corresponding years, were used to analyze the impact of meteorological factors on the formation of wheat main grain quality through Pearson correlation analysis, linear correlation, quadratic curve correlation, and stepwise regression methods. A prediction model for grain crude protein content was constructed, and the key meteorological factors affecting the main quality indicators of strong gluten and non strong gluten wheat in Henan Province were identified. The results showed that the crude protein, wet gluten content, and falling number of strong gluten wheat in Henan Province were higher than those of non strong gluten wheat. The falling number of two types of gluten wheat was closely related to the temperature, sunshine hours, and daily temperature range after the jointing stage, with non strong gluten wheat having a higher correlation with meteorological factors. The wet gluten content in grains was closely related to the daily temperature range, and there are significant differences in the response of different gluten types of wheat to some meteorological factors in April. From the prediction model of wheat grain crude protein content, it can be seen that both types of wheat crude protein content were affected by meteorological conditions, but the influencing factors were different. The prediction model of non strong gluten wheat crude protein content is more complex.

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