基于SPSS的日照市茶叶产量预测模型的建立

根据1993-2008年山东省日照市气象资料和茶叶产量资料,采用SPSS统计软件对气候因子和茶叶产量进行了相关性分析,从132个气象因子中筛选出年日照时数、7月份15 cm平均地温、7月份20 cm平均地温、7月份平均最高气温、8月份平均最高气温共5个相关性较高的因子,建立了多元回归模型。利用该模型对历年产量进行预测,结果表明,茶叶预测产量与实际产量拟合率较高,预测精度最高为100%,最低为86%,平均精度为94%。该模型具有较高的精度和实用性,可作为茶叶产量预报的有效工具。

The Tea Yield Prediction Model Based on SPSS Statistical Software in Rizhao City

According to the data of meteorological and tea production from 1993 to 2008 in Rizhao city in Shandong province,correlation analysis of tea production and climatic factors was counducted by using the SPSS statistical software.Five high correlation factors,namely,sunshine hours,15cm ground temperature in July,20cm ground temperature in July,average maximum temperature in July,average maximum temperature in August were selected and established the multiple regression models.Then the production of calendar year is tested.The results showed that tea yield can be forecasted and fits a higher rate of actual yield,and the maximum prediction accuracy can be up to 100%,and the smallest accuracy is 86% with the average accuracy of 94%.The prediction model has high accuracy and practicality,and can be used as an effective tool for prediction of tea production.