基于GIS和多种土壤属性的烟田养分分区管理研究

摘要

以平顶山典型烟区烟田土壤为研究对象,用111个样点耕层土壤(0～20 cm)的pH、有机质、总N、碱解N、速效P、速效K、活性有机质、阳离子交换量等数据对烟田进行管理分区研究.利用主成分分析从繁杂的数据中提取3个主成分,利用MZA软件进行模糊聚类分析从而实现分区,采用FPI和NCE来确定最佳分区数.结果表明研究区的最佳分区数为3,模糊指数为1.5.各分区内土壤养分的变异系数都较整个研究区有所降低,而分区间土壤养分差异显著.研究区的平均混乱度指数为0.37,不同模糊类别交叠程度较小,地理空间上土壤的隶属关系相对明确.通过模糊聚类分析法可以较好地进行管理分区的划分,分区结果可以作为变量施肥的单独作业单元进行肥料管理.%This research was to define management zones of tobacco planting field in Pingdingshan. The variables of pH, total nitrogen, organic matter, alkalytic nitrogen, available phosphorous, available potassium, active soil organic matter and cation exchange capacity data determined in 111 topsoil (0-20 cm) samples were selected as data sources. Principal components analysis (PCA) and fuzzy cluster algorithm were then performed to delineate management zones (MZs); fuzzy performance index (FPI) and normalized classification entropy (NCE) were used to determine the optimum cluster number. The results showed that the optimum number of MZs for this study area was three and the fuzziness exponent was 1.5. The analysis of variance indicated the heterogeneity of soil fertility among different MZs, while the variation coefficient of soil nutrients decreased. The average confusion index was 0.37 in this area. The overlapping of fuzzy classes at points was low and the spatial distribution of membership grades was unambiguous. The results indicated that fuzzy c-means clustering algorithm could be used to delineate management zones. The defined MZs provide a basis of information for site-specific fertilizer management in the tobacco-planted field.