The objective of this research was to define management zones of oasis cotton field. The variables of organic matter, available N, available P and available K data determined in 193 topsoil (0-30cm) samples were selected as data sources. Fuzzy c-means clustering algorithm was used to delineate management zones. In order to determine the optimum fuzzy control parameters, the fuzziness performance index (FPI), c-Ф combinations and the multiple regression based on external variable were used in this study. Meanwhile, the cotton yield was chosen as the external variable. The whole field was divided in four management zones. And fuzziness exponent was 1.6. The zoning statistics showed that variation coefficient of soil nutrients decreased, while the means of the soil nutrients differed sharply between management zones. The average confusion index was 0.19 in all management zones. 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 by selecting the appropriate external variables. The defined management zones can be used for fertilizer recommendation to manage soil nutrient more efficiently.
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