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中国农学通报 ›› 2020, Vol. 36 ›› Issue (29): 153-160.doi: 10.11924/j.issn.1000-6850.casb20190900631

• 三农研究 • 上一篇    下一篇

湖南省粮食产量波动的影响因素分析及预测

杨凡雨1(), 刘黎明1(), 袁承程2   

  1. 1中国农业大学土地科学与技术学院,北京 100193
    2中国土地勘测规划院,北京 100035
  • 收稿日期:2019-09-09 修回日期:2019-11-25 出版日期:2020-10-15 发布日期:2020-10-16
  • 通讯作者: 刘黎明
  • 作者简介:杨凡雨,女,1996年出生,重庆垫江人,硕士研究生,研究方向:土地资源可持续利用与景观规划。通信地址:100193 北京市海淀区圆明园西路2号 中国农业大学西校区土地科学与技术学院土地资源管理系,Tel:86-10-62732936,Email:244388687@qq.com
  • 基金资助:
    国家自然科学基金重点项目“高集约化农区土地利用系统过程模拟及其环境风险控制”(41130526)

Influencing Factors of Grain Production Fluctuation in Hunan Province: Analysis and Prediction

Yang Fanyu1(), Liu Liming1(), Yuan Chengcheng2   

  1. 1College of Land Science and Technology, China Agricultural University, Beijing 100193
    2 China Land Surveying and Planning Institute, Beijing 100035
  • Received:2019-09-09 Revised:2019-11-25 Online:2020-10-15 Published:2020-10-16
  • Contact: Liu Liming

摘要:

旨在维护国家稳定,为预判粮食生产前景、提高粮食生产效率、保障粮食安全提供理论依据。利用湖南省统计数据,运用灰色关联分析法筛选关联性较强的影响因素,并建立GM(1,N)预测模型预测粮食产量。2008—2017年与湖南省粮食产量关联度最大的影响因素是粮食作物播种面积和农业机械总动力;科技因素是影响2008—2017年湖南省粮食产量的主要因素,其次是自然因素,社会因素;2018—2027年湖南省粮食产量有较小波动,且农业机械总动力和财政农业支出影响较大;农业机械总动力在前后十年对粮食产量都有较重要的影响,越来越占据主导地位。粮食产量受国家政策的影响,受农业机械总动力影响最大,维持产量水平需高度重视农业机械化水平,稳步提高粮食作物播种面积。

关键词: 灰色关联分析, GM(1,N)预测模型, 粮食产量, 影响因素, 湖南省

Abstract:

The aim is to provide a theoretical basis for predicting the prospect of grain production, improving the efficiency of grain production and ensuring food security. Using the statistical data of Hunan Province, the grey relational analysis method was used to screen the highly relevant influencing factors and a GM (1, N) prediction model was established to predict the grain production. The most influential factors related to the grain production of Hunan in 2008-2017 are the sowing area of grain crops and the total power of agricultural machinery. The scientific and technological factors are the main factors that affect the grain production, followed by natural and social factors. In 2018-2027, the grain production of Hunan has less fluctuation, and the total power of agricultural machinery and the fiscal agricultural expenditure have a greater impact. The total power of agricultural machinery has an important influence on grain production in the past and next ten years, and it is increasingly dominant. To maintain the level of production, it is necessary to attach great importance to the level of agricultural mechanization and steadily increase the sowing area of grain crops.

Key words: grey relational analysis, GM (1,N) prediction model, grain production, influencing factor, Hunan Province

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