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基于主成分和聚类分析的村域稻田土壤肥力评价
引用本文:王小艳,冯跃华,李云,武彪,陈山,王旭,李香玲,莫银化. 基于主成分和聚类分析的村域稻田土壤肥力评价[J]. 中国农学通报, 2014, 30(33): 46-50. DOI: 10.11924/j.issn.1000-6850.2014-2090
作者姓名:王小艳  冯跃华  李云  武彪  陈山  王旭  李香玲  莫银化
作者单位:贵州大学农学院,贵州大学农学院,贵州大学农学院,贵州大学农学院,贵州大学南校区,贵州大学农学院,贵州大学农学院,贵州大学农学院
基金项目:国家自然科学基金项目“黔中喀斯特山区村级尺度土壤养分、水稻生长特性和产量的空间变异及其协同机理研究”(31160263);贵州省农业科技攻关项目“机插水稻高产栽培关键技术研究与示范”[黔科合NY(2011)3085];贵州省科学技术基金项目“水氮互作对杂交水稻碳氮代谢和产量及品质的影响机理”[黔科合(2011)2139]
摘    要:为了解贵州省安顺市西秀区文星村稻田土壤肥力状况,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:研究区土壤肥力因子除pH、总孔隙度、毛管孔隙度变异系数小于10%,为弱变异外,其他变异系数在10%~100%之间,均为中等变异,有效养分硫、铁、锰等元素的变异相对较大,变异系数均大于75%。主成分分析表明,可归为6个主要成分的22个评价因子,其累计贡献率达74.26%,可以从一定程度上反应田区土壤的肥力标准概况。土壤综合肥力指标(IFI)值的得分为-1.7422~1.8230,聚类分析将其分为Ⅰ、Ⅱ、Ⅲ、Ⅳ 4个等级,所占样点比例分别为2.5%、52.5%、30%和15%。该方法能相对正确的对土壤养分供应能力及丰缺度作出评价,为稻田土壤的合理施肥提供参考依据。

关 键 词:产量  产量  
收稿时间:2014-07-31
修稿时间:2014-11-11

Evaluation on Rice Soil Fertility Quality Based on Principal Component Analysis and Cluster Analysis at Village-region
Wang Xiaoyan,Feng Yuehua,Li Yun,Wu Biao,Chen Shan,Wang Xu,Li Xiangling,Mo Yinhua. Evaluation on Rice Soil Fertility Quality Based on Principal Component Analysis and Cluster Analysis at Village-region[J]. Chinese Agricultural Science Bulletin, 2014, 30(33): 46-50. DOI: 10.11924/j.issn.1000-6850.2014-2090
Authors:Wang Xiaoyan  Feng Yuehua  Li Yun  Wu Biao  Chen Shan  Wang Xu  Li Xiangling  Mo Yinhua
Affiliation:(Agronomy College of Guizhou University, Guiyang 550025)
Abstract:In order to clarity the soil fertility status of paddy fields in Wenxing Village, Anshun City, GuizhouProvince, principal component analysis combined with the cluster analysis was used to analyze the soil fertility.The results showed that the CV of soil p H, total porosity and capillary were lower than 10%, indicating theirweak variation. In contrast, other variation coefficients were from 10% to 100%, belonging to moderatevariation. The variability of available S, available Fe and available Mn were intensive with variation coefficientof more than 75%. Principal component analysis showed that 22 evaluation factors could be classified into sixmajor components, its cumulative contribution rate had reached 74.26%, could reflect the soil fertility standardat a certain extent. The IFI values of soil samples were from-1.7422 to 1.8230, which had been divided intofour levels as Ⅰ, Ⅱ, Ⅲ and Ⅳ by the cluster analysis with their proportion of 2.5%, 52.5%, 30% and 15%,respectively. This method could make a relatively correct evaluation on soil nutrient supply capacity and thedegree of abundance, and provide a reference for reasonable application of fertilizer in paddy field.
Keywords:soil nutrient   principal component analysis   cluster analysis   evaluation on the fertility
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