Management Zones Delineation, Correct and Incorrect Application Analysis in a Coriander Field Using Precision Agriculture, Soil Chemical, Granular and Hydraulic Analyses, Fuzzy k-Means Zoning, Factor Analysis and Geostatistics

Abstract

The objective of our investigation was to study the various effects of correct and incorrect application of fuzziness exponent, initial parameterization and fuzzy classification algorithms modeling on homogeneous management zones (MZs) delineation of a Coriandrum sativum L. field by using precision agriculture, soil chemical, granular and hydraulic analyses, fuzzy k-means zoning algorithms with statistical measures like the introduced Percentage of Management Zones Spatial Agreement (PoMZSA) (%), factor and principal components analysis (PCA) and geostatistical nutrients GIS mapping. Results of the exploratory fuzzy analysis showed how different fuzziness exponents applied to different soil parameter groups can reveal better insights for determining whether a fuzzy classification is a correct or incorrect application for delineating fuzzy MZs. In all cases, the best results were achieved by using the optimal fuzziness exponent with the full number of parameters of each soil chemical, granular and hydraulic parameter group or the maximum extracted PCAs. In each case study where the factor analysis and PCA showed optimal MZs > 2, the results of the fuzzy PoMZSA clustering metric revealed low, medium and medium to high spatial agreement, which presented a statistically significant difference between the soil parameter datasets when an arbitrary or commonly used fuzziness exponent was used (e.g., φ = 1.30 or φ = 1.50). Soil sampling and laboratory analysis are tools of major significance for performing exploratory fuzzy analysis, and in addition, the FkM Xie and Benny’s index and the introduced fuzzy PoMZSA clustering metric are valuable tools for correctly delineating management zones.