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中国农学通报 ›› 2017, Vol. 33 ›› Issue (33): 85-91.doi: 10.11924/j.issn.1000-6850.casb17070106

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

基于主成分和聚类分析的太原市小店污灌区土壤肥力评价

韩文辉,赵 颖,刘 娟   

  1. 山西省环境科学研究院,山西省环境科学研究院,山西省环境科学研究院
  • 收稿日期:2017-07-20 修回日期:2017-11-09 接受日期:2017-09-19 出版日期:2017-11-27 发布日期:2017-11-27
  • 通讯作者: 赵 颖
  • 基金资助:
    国家自然科学基金“生态补水影响下白洋淀湿地水生态系统对水文-气象-环境要素的响应关系研究”(41401020),“白洋淀湿地水-土-植被 体系碳排放及其调控机理研究”(41601202);山西省青年科技研究基金项目“污染农田土壤环境质量综合评价指标体系研究”(2015021173);山西省科 技攻关项目“汾河上中游流域生态系统健康状况研究”(20150313001-2)。

Evaluation on Soil Fertility in Sewage Irrigation Area of Xiaodian in Taiyuan: Based on Principal Component Analysis and Hierarchical Cluster Analysis

  • Received:2017-07-20 Revised:2017-11-09 Accepted:2017-09-19 Online:2017-11-27 Published:2017-11-27

摘要: 为了解山西省太原市小店污灌区土壤肥力状况,采用主成分与聚类分析相结合的方法,对研究区土壤肥力进行了评价。结果表明:全磷、有效磷和全氮总体含量丰富,有机质、碱解氮含量总体适量,有效钾处于贫乏状态。主成分分析将10 个评价因子归为4 个主要成分,其累计贡献率达80.24%,第一主成分为碱解氮、有效磷、速效钾、阳离子交换量和有机质;第二主成分为电导率和pH值;第三主成分为全磷和全氮;第四主成分为全钾。该分析可以在一定程度上反映土壤的肥力标准概况。聚类分析将土壤的18 个样本点分为四个等级,所占样点比例分别为5.6%、61%、27.8%和5.6%。该方法能相对正确的对土壤肥力状况作出评价,并为土壤的合理施肥提供参考依据。

Abstract: To clarify soil fertility status of sewage irrigation area in Xiaodian District of Taiyuan, the authors adopted the methods of principal component analysis and hierarchical cluster analysis. The results showed that the contents of total phosphorus, available phosphorus and total nitrogen were abundant, and the contents of organic matter and alkali-hydrolyzable nitrogen were moderate, while the available potassium content was poor. Principal component analysis showed that 10 evaluation factors could be classified into four major components, with 80.24% of cumulative contribution rate. The first main component consisted of alkali hydrolyzable nitrogen, available phosphorus, available potassium, cation exchange capacity and organic matter; the second principal component contained conductivity and pH value; the third principal component was composed of total phosphorus and total nitrogen; and the fourth principal component was total potassium. The results could reflect soil fertility to certain extent. The 18 soil samples were classified into four levels by the hierarchical cluster analysis with the proportion of 5.6%, 61%, 27.8% and 5.6%, respectively. This method could make a relatively correct evaluation on soil fertility status, and provide a reference basis for rational fertilization of soil.

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