Abstract

ABSTRACTDelineation of site-specific nutrient management zones (MZ) provides a basis for practical and cost-effective management of spatial soil fertility in precision agriculture. Therefore, the objective of this study was the delineation of MZs in a soybean field using geostatistics, principal component analysis (PCA), and the fuzzy k-means algorithm. The study was carried out in a field with 204 ha located in São Desidério, western Bahia state, Brazil (12 ° 25 ‘ 12” S, 45 ° 29ʹ 46” W). To do so, samples of soil attributes (0–20 cm), soybean yield, electrical conductivity (EC) at 0.20 m (EC02), 0.50 m (EC05), 1.00 m (EC1), 2.00 m (EC2) soil profile depth, and the Normalized Difference Vegetation Index (NDVI) were obtained in 204 points (100 x 100 m grid). After soil sampling and laboratory analyzes, the data were submitted to descriptive statistics and a Spearman correlation analysis was performed to select those attributes related to soybean yield. Then, the spatial variability of these attributes was assessed and spatial distribution maps were constructed using geostatistical tools. Next, PCA and fuzzy k-means algorithm were then performed to delineate MZs. Finally, the agreement between the MZs maps obtained from the PCA and soybean yield was assessed using the Kappa index. Results showed that the optimal number of MZs was two, which resulted in a Kappa index of 0.61 (very good). Moreover, the analysis of variance indicated heterogeneity between all attributes analyzed in the MZs. Finally, the defined MZs provide a basis of information for site-specific nutrient management.

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