Management Zones Delineation through Clustering Techniques Based on Soils Traits, NDVI Data, and Multiple Year Crop Yields

• Published in: Agriculture (Basel) Vol. 12; no. 2; p. 231
• Main Authors: Ali, Abid, Rondelli, Valda, Martelli, Roberta, Falsone, Gloria, Lupia, Flavio, Barbanti, Lorenzo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2022
• Subjects: Agricultural production; agriculture; biomass; Cereals; clay fraction; Clay soils; Cluster analysis; Clustering; computer software; Corn; Crop management; Crop yield; crop yields; Crops; Data collection; Datasets; Environmental impact; Fertilizers; fuzzy c-means clustering; georeferencing; geostatistics; Helianthus annuus; Italy; kriging; Landsat; Limestone; management zones; NDVI; normalized difference vegetation index; Normalized difference vegetative index; Pixels; precision field cropping; Productivity; Remote sensing; Soil analysis; soil traits; Sorghum; Spatial analysis; Sunflowers; total nitrogen; wheat; yield mapping; United Kingdom > UK; United States > US; Italy
• ISSN: 2077-0472; 2077-0472
• DOI: 10.3390/agriculture12020231

Availability of georeferenced yield data involving different crops over years, and their use in future crop management, are a subject of growing debate. In a 9 hectare field in Northern Italy, seven years of yield data, including wheat (3 years), maize for biomass (2 years), sunflower, and sorghum,...