欢迎访问《中国农学通报》,

中国农学通报 ›› 2012, Vol. 28 ›› Issue (30): 95-100.doi: 10.11924/j.issn.1000-6850.2012-0340

• 农学 农业基础科学 • 上一篇    下一篇

基于综合整理的中低产田划分研究

杨建波   

  • 收稿日期:2012-02-08 修回日期:2012-03-07 出版日期:2012-10-25 发布日期:2012-10-25
  • 基金资助:

    河南省重点攻关项目

Based on the comprehensive consolidation is medium low yield cropland division research

  • Received:2012-02-08 Revised:2012-03-07 Online:2012-10-25 Published:2012-10-25

摘要:

研究目的:基于综合整理视角下划分河南省高中低产田水平,为打造粮食核心区提供支撑。研究方法:对比分析法、GIS空间分析法、实证分析法。研究结果:高中低产田水平的划分结果要综合考虑粮食产量、耕地地力、土壤肥力等多种因素的共同影响; 根据综合因素划分的河南省高中低产田面积比例为49:31:20。研究结论:(1)粮食产量仍是划分中低产田最主要因素,该因素对高中低产田的划分影响最大,结果间的差异率最小;用土壤肥力因素划分结果的差异率最大;用耕地等指数因素划分结果的均衡性最好,可以采用耕地等指数(特别是利用等指数)作为划分中低产田的一种方法。(2)采用单因子或侧重耕地某方面特性划分的结果都有局限性;(3)以因素为标准进行的高中低产田划分,其结果的聚拢性要好于因子。

关键词: 长白猪, 长白猪

Abstract:

The purpose of this paper is to divide cropland of the low yield in Henan province level in a comprehensive perspective, in order to build the grain core area to provide support. Methods employed are the method of comparative analysis, the GIS spatial analysis method, empirical analysis. The results indicate that(1)in low yield cropland level dividing results to be integrated into the grain yield, soil fertility, soil fertility and other factors;(2)according to the comprehensive factors of Henan province high school low yield cropland area ratio of 49 : 31: 20.It is concluded that (1)food production is still the main factor division of cropland of the low yield in, the factors on the high school division of cropland of the low yield the greatest impact, the difference between the results of minimum rate; It is the biggest to use of soil fertility factors classification result difference rate; It is best to use of farmland index factor classification results of equilibrium, it can use farmland index (particularly the use of index ) as a division of cropland of the low yield in a method.(2) Using single factor or focusing characteristics of farmland a divided the results are limited;(3) The factors for the standards of high school low yield cropland classification, the result collection effect is better than the factor.