Relationship Analysis and Prediction between the Meteorological Elements and Thousand Kernel Weight in Fuyang City

doi:10.14088/j.cnki.issn0439-8114.2019.03.011

Abstract

Abstract: Based on the thousand kernel weight and the meteorological data between heading period and mature period of wheat （Triticum aestivum L.） during 2006 to 2015, the relationship between the two was analyzed by using SPSS statistical analysis tool. The results showed that the daily minimum temperature had the most significant effect on the thousand kernel weight, followed by sunshine hours and total sunshine hours. The multivariate linear regression prediction model based on the correlation between the main influencing factors and thousand kernel weight was established as a basis for predicting the thousand grain weight of wheat. The independent forecasts inspection accuracy during 2016 to 2017 was about 67%, showed that the model has good application value.

Key words: wheat（Triticum aestivum L.）, SPSS, meteorological elements, thousand grain weight

CLC Number:

S512.1

WANG Xiao-ling, ZHANG Qing-kui, ZHANG Gui-fang. Relationship Analysis and Prediction between the Meteorological Elements and Thousand Kernel Weight in Fuyang City[J]. HUBEI AGRICULTURAL SCIENCES, 2019, 58(3): 42-44.

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