HUANG Kai ,SHAO Jin-hua,HUANG Xu-sheng ,WU Wei-xiong,HUANG Guo-qin ,TANG Hai-ying
China Rural Water and Hydropower. 2020, (7):
129-135.
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With mathematical statistics, principal causes analysis and multiple linear regression analysis, in this paper,it has comprehensively analyzed the response of grain crops yields on the climatic change, farmland under effective irrigation, and fertilizer purified usage of Guangxi during 1978a to 2017a. It showed that, ①in the bivariate correlation statistics, grain cropping yield in Guangxi is positively correlated with the annual effective accumulated temperature, annual mean temperature, effective irrigated area and fertilizer purified usage; ②Four principal component factors were extracted from the main cause analysis. The component matrix load after rotation of the annual irradiation time, annual average daily-total solar radiation exposure, annual precipitation and annual mean minimum temperature, in the 1st principal component were 0.815, 0.742, -0.673 and -0.594,respectively.The annual effective accumulated temperature and the annual mean temperature were 0.980 and 0.973 respectively after rotation in the 2nd principal component.The effective irrigation area and fertilizer purified usage were 0.980 and 0.973, respectively, after rotation in the 3rd principal component.The annual mean minimum temperature and annual mean maximum temperature were 0.557 and 0.876, respectively, after rotation in the 4th principal component; ③With 4 extracted principal components,a multivariate regression model was constructed after the main cause analysis. This model can explain 50.5% of the variation in yield of grain cropping in Guangxi (P=0.041<0.05), and can be used to comprehensive analyze and predict the yield of grain cropping in Guangxi based on the change of climate factors, effective irrigation area and fertilizer usage.