中国农业科学 ›› 2009, Vol. 42 ›› Issue (5): 1656-1664 .doi: 10.3864/j.issn.0578-1752.2009.05.019

• 土壤肥料·节水灌溉·农业生态环境 • 上一篇    下一篇

东北黑土区土壤生产力评价方法研究

  

  1. 北京师范大学地理学与遥感科学学院/地表过程与资源生态国家重点实验室
  • 收稿日期:2008-09-12 修回日期:2008-11-03 出版日期:2009-05-10 发布日期:2009-05-10
  • 通讯作者: 谢云

Study on the Method of Soil Productivity Assessment in Northeast Black Soil Regions of China

  

  1. 北京师范大学地理学与遥感科学学院/地表过程与资源生态国家重点实验室
  • Received:2008-09-12 Revised:2008-11-03 Online:2009-05-10 Published:2009-05-10
  • Contact: XIE Yun

摘要:

【目的】探讨在东北黑土区简单实用的土壤生产力评价方法。【方法】基于PI(productivity index)模型,根据研究区土壤特性选择8项土壤指标,对研究区25个黑土土种120个土壤样本的这8项理化性质实测数据进行了聚类和相关分析,以确定模型参数。然后确定各参数的适宜性指数。从而得到修订参数的研究区的生产力指数模型MPI(modify productivity index),最后利用实地调查获得的正常年景玉米单产进行了验证。【结果】适宜东北黑土区的土壤生产力评价参数是土壤有效含水量、酸碱度、黏粒含量和有机质含量;与原模型(PI)相比增加了有机质和黏粒含量参数而减去了容重参数,经过验证分析证明参数改变后模型的评价效果得到很大改善;MPI指数和玉米单产之间有极显著的相关性,可利用MPI指数模拟玉米单产:Y = 3.1275ln(MPI) + 10.052,模型的决定系数为0.7564。【结论】修订后的生产力指数模型是一种在研究区进行土壤生产力相关评价的好方法。

关键词: PI, MPI, 土壤生产力, 东北黑土区

Abstract:

【Objective】 Investigate a simple and practical method for soil productivity assessment in Northeast black soil regions of china. 【Method】 The research based on soil Productivity Index model(PI for short). Firstly, 8 kinds of physico-chemical properties had been chosen base on the Characteristics of research area, cluster and correlation analysis had been done to 8 kinds of physico-chemical properties of 120 soil samples from 25 black soil local type. Subsequently, parameter index were calculated with existing findings. Modify Productivity Index (MPI) which suitable to apply in research regions was gained finally. And simulated results were compared with crop yield of these soil profiles. 【Result】 The results showed that the suitable parameters for soil productivity assessment in Northeast black soil regions were soil available water, soil pH, clay content and Organic Matter content,compared with original PI,MPI expanded clay content and Organic Matter content parameters, condensed bulk density parameter ; The verification result indicated that the validation of MPI was better than PI’s, there were high significant correlation between MPI index and unit yield of maize, the equation was: Y = 3.1275 ln (MPI) + 10.052, with R2=0.7564.【Conclusion】 The analysis results show that PI is a good model for such study as soil productivity assessment in the research area.

Key words: PI, MPI, soil productivity, Northeast black soil regions