基于大数据分析的农业气候与农作物产量变化研究

THE CHANGE OF AGRICULTURAL METEOROLOGY AND CROP PRODUCTIONBASED ON BIG DATA ANALYSIS

关键词:  农业产量 气候变化 主成分因素 C-D-A模型 实证分析

Key words:  agricultural production  climate change  principal component factors  C-D-A model  empirical analysis

摘要:

［目的］作为农业大国，我国农业产量直接影响着我国未来发展进度，而气候的变化直接牵动着农业产量的变化。［方法］文章基于农业气候对农作物产量的影响，借鉴已有研究从农业气候变化的角度入手，介绍气候变化对农作物产量等方面的影响，并以华北、华东及东北水稻产区为例，通过主成分因素分析设定降水量、气温、光照及太阳辐射度等指标因素，并建立C-D-A模型，［结果］降水量、气温及光照等气候因素对农作物产量的影响明显，其中干旱天气的影响最大。［结论］通过实证分析验证了该模型具有较高的可信度，以期为各种天气条件下保障与提高农作物产量提供理论依据。

Abstract:

Climate change directly affects the change of agricultural production, and hence affects the progress of a country′s future development. Based on the agrometeorological influences on crop yieldsin recent years, This paper summarized the study progress of the impactsof agricultural climate change on crops. And then, taking the rice production areas in north China, east China and northeastas an example, it analyzedtheindex factors such as precipitation, temperature, light and solar radiation degree usingthe principal component factor analysis, andestablisheda C-A-D model. The results showed that the climate factors such as precipitation, temperature and illumination had great effects on crop yield, especially the dry weather. It concluded that the model had high credibility, so as to provide a reference for guaranteeing and improving the crop yields in various weather conditions.