1 陕西师范大学地理科学与旅游学院,陕西 西安 710062;
2 西安理工大学土建学院,陕西 西安 710048; 3 中国科学院西北生态环境资源研究院,甘肃 兰州 730000
收稿日期: 2019-05-22
修回日期: 2019-11-28
网络出版日期: 2020-03-25
基金资助
国家自然科学基金 （41877077，51479163）资助
Influencing factors of agricultural production changes in Guanzhong based on PCA
1 School of Geography and Tourism,Shaanxi Normal University,Xi’an 710062,Shaanxi,China;
2 School of Civil Engineering and Architecture,Xi’an University of Technology,Xi’an 710048,Shaanxi,China; 3 Northwest Institute of EcoEnvironment and Resources,CAS,Lanzhou 730000,Gansu,China
Received date: 2019-05-22
Revised date: 2019-11-28
Online published: 2020-03-25
针对陕西省关中区域1978—2017年的农业生产数据，在分析关中40 a农业粮食生产的趋势变化后，运用主成分分析法，对影响关中农业生产中的地理环境和生产投入等主要因素进行了评价研究。结果表明：（1） 关中农业粮食生产的趋势变化呈现周期为3～7 a的循环增长方式，平均每周期峰值增长率为4.5%。（2） 主成分分析研究后得出，第一主成分全是地理因素指标，方差贡献率达到0.554，对关中地区农业粮食生产起着非常显著的决定影响作用，包括受灾农田面积（不含病虫害）、主要粮食作物播种面积、成灾农田面积（不含病虫害）、有效灌溉耕地面积、耕地面积；第二主成分方差贡献率为0.25，是影响粮食生产的重要因素和农业生产的生命补给。包括农业用电量、化肥、农用机械等生产资料投入和主要粮食作物稳产面积、劳动力投入因素指标；第三主成分为农药应用量，方差贡献率为0.068，影响较小。主成分累计方差贡献为0.872。通过对关中地区农业粮食生产变化的影响因素分析，可以为政府部门提出数据支撑和相关性的建议。
韩群柱, 冯起, 高海东, 陈桂萍 . 基于主成分分析的关中地区农业粮食生产变化的影响因素研究[J]. 干旱区地理, 2020 , 43(2) : 474 -480 . DOI: 10.12118/j.issn.1000-6060.2020.02.22
This study is based on the statistical data of agricultural grain production in the Guanzhong region of Shaanxi Province,China from 1978 to 2017.This paper discusses the changing trends of agricultural grain production in the Guanzhong region from 1978 to 2017.In addition,this study analyzed the factors influencing grain production from 1978 to 2017 by means of principal component analysis (PCA).The main results of the analysis and research are summarized below.First,the trend change of agricultural grain production in the Guanzhong region shows a cyclical growth pattern with a cycle of 3-7 and the average growth rate of grain production in each cycle is 4.5%.The grain production process is manifested as a series of continuous “large valleys” or “large peaks” with high-yield years and low-yield years occurring successively,thus causing the grain yield to be extremely unstable.Second,the statistical data for agricultural production were calculated and analyzed by a PCA model.The cumulative variance contribution rate was greater than the 0.85 standard and there were three main components that had greater impacts on grain production.The first principal component factors are all geographical factors and the variance contribution rate reached 0.55;this indicates a very significant and decisive role on agricultural grain production in the Guanzhong region and is the most basic condition for guaranteeing grain production in Guanzhong.The main components include the farmland areas affected by disasters (excluding diseases and pests),areas cultivated with major food crops,areas of farmland affected by disasters (excluding diseases and pests),and effective areas of irrigated farmland and cultivated areas.The second principal component,with a cumulative variance of 0.25,is an important factor affecting grain production and vital supply for agricultural production in Guanzhong.In addition to the areas of farmland with stable grain production based on geographical factors,the index of input factors of production materials and the labor force such as agricultural electricity consumption,chemical fertilizers,and agricultural machinery are included.The third principal component is pesticide application,with a cumulative variance of 0.068,which exhibited little effect.The actual cumulative variance contribution rate of the three principal components is 0.87.
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