INVESTIGADORES
DIAZ ZORITA Martin
artículos
Título:
Field methods for making productivity classes for site-specific management of wheat
Autor/es:
LÓPEZ DE SABANDO, MARCELO JOSÉ; DIAZ-ZORITA, MARTÍN
Revista:
PRECISION AGRICULTURE
Editorial:
SPRINGER
Referencias:
Año: 2022
ISSN:
1385-2256
Resumen:
Reducing the decision-making unit to classes within fields can improve yields, efficiency in the use of nutrients and profitability of crops. Fields can be organized in small and uniform decision units according to diverse information describing different productivity classes. The objectives were to compare methods for class delimitation in wheat (Triticum aestivum L.) crops based on apparent productivity levels and to establish similarities among them in terms of spatial overlapping, productive attributes and in the use of nitrogen (N). In three wheat fields high and low apparent productivity classes (APC) were defined based on eight methodologies: yield maps, soil maps, gramineae vegetation index, rotation crop index, interpretation of satellite images, management records, elevation and integrated soil and yield maps. In each APC, soil and crop yield components were determined under five N fertilization levels. Among the studied delimitation methodologies, the degree of coincidence varied from 1.4 to 81.7%. The differences in soil properties, N use efficiency and grain yields were greater among fields than among APC within in each field. Within each field, the delimitation methodologies identified different single factors that discriminated among the potential management classes and were partially associated with the crop grain yields. The wheat crops at the low APC yielded 39% less and 12% less than at the high APC, respectively. The N fertilization, at the rate for maximum productivity for each ACP, reduced the yield differences between contrasting APC. N fertilization also modified clustering of classes based on expected yields. Making management classes for wheat based on expected productivity is more accurate when it is based on previous crop production information under similar N fertilization conditions than the targeted crop.