摘要
基于陕西关中地区半干旱的地理条件,针对1980-2017年农业生产的实际统计数据,以5年为计算时间尺度单元,建立了关中地区农业生产的主成分回归(PCR)分析模型,定量地研究了陕西关中地区地理环境和生产投入对农业生产的绩效贡献。结果表明:(1)对各时段的PCR方程模型自变量平均弹性系数的计算分析表明,促进农业生产效益提高的主要指标有Y3(实际灌溉农田面积,0.117)、Y4(高产稳产农田面积,0.509)、Y7(农用施用化肥总量,0.793)、Y8(农用机械总动力,0.091)、Y9(总农业用电量,0.478)、Y10(农业劳动力人数,0.106);减少效益的主要指标有Y1(农田面积,-0.763)、Y5(受灾农田面积,-0.052)、Y6(成灾农田面积,-0.062)。(2)自然灾害对关中地区农业粮食生产的影响处于非常显著位置,但影响总的而言比较平稳。(3)在这些指标因素的综合影响下,关中农业粮食生产产量呈现高低起伏、周期性循环、持续增长的趋势。
Natural geographical factors and production input on the agricultural production has a significant influence in arid and semi-arid region. In this paper, based on the analysis of the trend of grain yield by the data of agricultural food production during 1980-2017 in the Guanzhong area of Shaanxi Province,the PCR(principal component regression simulation)equation of the agricultural production in Guanzhong area is established by the help of PCA( principal component analysis) theory, then, on the basis of calculating the dependent variable(Y) elastic coefficient of regression equation, the performance contribution of geographical factors and production input index(Y) to grain yield of guanzhong area was analyzed and studied. The natural geographical factors include: Y1(farmland cultivation area),Y2(the main food crop farming area),Y3(grain stable yield farmland area),Y4(the effective irrigation farmland area), Y5(affected farmland area),Y6(disaster farmland area);the production input factors include: Y7(total amount of fertilizer applied in agriculture),Y8(total power of agricultural machinery),Y9(agricultural electricity consumption),Y10(number of agricultural labor force),Y5(total pesticide usage),Y12(agricultural film usage). According to the calculating data of the PCR model analysis, the main results show that: the factors of independent variable whose average elastic coefficient is greater than 0 are Y3(0.117),Y4(0.509),Y7(0.793), Y8(0.091), Y9(0.478),Y10(0.106), Y12(0,002) and it had greatly promoted the development of agriculture. Less than 0 of the factors are Y1(-0.763), Y2(-0,009), Y5(-0.052),Y6(-0,062), Y11(-0,001) and it were a more obvious obstacle to improve the efficiency of agricultural production. In dependent variable(Y) of the geographical factors, the index Y3 and Y4,Whose 75% of the elastic coefficients are greater than 0, are the main contributions to the performance of grain production in Guanzhong area. In dependent variable(Y) of the production input, the indexs Y7,Y8 and Y9, Whose 79.2%
作者
韩群柱
冯起
高海东
陈桂萍
Han Qunzhu;Feng Qi;Gao Haidong;Chen Guiping(Tourism andEnvironment College,Shaanxi Normal University,Xi'an 710062,China;School of Civil Engineering and Architecture,Xi'an University of Technology,Xi'an 710048,China;Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China)
出处
《中国沙漠》
CSCD
北大核心
2020年第2期118-124,共7页
Journal of Desert Research
基金
国家自然科学基金项目(41877077,51479163)。
关键词
关中
地理
主成分回归(PCR)
系数
Guanzhong Area
geographical factors
principal component regression(PCR)
coefficient
