Towards site specific management zones delineation in rotational cropping system: Application of multivariate spatial clustering model based on soil properties
Sofiane Ouazaa, Camilo Ignacio Jaramillo‐Barrios, Nesrine Chaali, Yeison Mauricio Quevedo Amaya, John Edinson Calderón-Carvajal, Omar Montenegro Ramos
Abstract
Site|specific management for irrigation purposes remains a great challenge especially when dealing with mixed cropping systems due to spatial variability of soil properties. This variability generates crop yield heterogeneity within agricultural fields. In this study, rice-corn, cotton rotational cropping system was cultivated in Tolima region-Colombia. A total of 72 geo-referenced representative surface soil samples (0–20 cm depth) were collected covering a total area of 5 ha of Inceptisols . The aim was to delineate field management zones (MZs) using three methods M1, M2 and M3, and evaluate their usefulness for a further site-specific management. Georeferenced soil samples were analyzed for soil texture , bulk density (BD), field capacity (FC), soil available water (AW), mesopores percentage (Mes), soil penetration resistance (PR), organic matter (OM), available phosphorus (P), and exchangeable bases content (Ca + Mg/K). Spatial variability of soil properties was analyzed with geostatistics approach. Further, spatial principal component (sPC), were performed to delineate the MZs using: M1- Fisher-Jenks algorithm with the first sPC; M2- Fuzzy k-means cluster analysis with two sPC; and M3- Fuzzy k-means with soil variables. MZs delineation results were validated by comparing the zones to soil properties and yield data coming from the rice-corn, cotton system. Two MZs were recommended using M2 due to its lower fragmentation compared to other methodologies. This delineation could be suggested for fertilization management since Clay + Silt , OM, P, and Ca + Mg/K content differentiate when delineating one and two MZs. M2 provided differences for AW, Mes, and PR when considering three MZs which can be used as a basis for irrigation site-specific management in precision agriculture.