Abstract
Abstract: The objective of this work was to evaluate the spatial and temporal variability of the dry matter yield of irrigated corn for silage, as well as its economic return. The study was conducted in an irrigated silage corn field of 18.9 ha in the municipality of São Carlos, in the state of São Paulo, Brazil. The spatial variability of the yield of three crop seasons, normalized yield indexes, production cost, profit, and soil electrical conductivity (EC) were modeled using semivariograms. Yield maps were obtained by kriging, and management zones were mapped based on average yield, normalized index, and EC. The results showed a structured spatial variability of corn yield, production cost, profit, and soil EC within the irrigated area. The adopted precision agriculture tools were useful to indicate zones of higher yield and economic return. The sequences of yield maps and the analysis of spatial and temporal variability allow the definition of management zones, and soil EC is positively related to corn yield.
Highlights
Precision agriculture is a management concept that takes into account the spatial variability of an area, aiming to maximize economic return and minimize risks of environmental damage, through agricultural practices based on information technologies (Inamasu et al, 2011)
It can be understood as a cycle that begins with data collection, continuing through analyses, interpretation of obtained information, generation of recommendations, and application in the field, aiming the evaluation of results (Gebbers & Adamchuk, 2010)
It reinforces the vision of the knowledge chain, in which machines, applications, and equipment are tools that can support this type of management (Inamasu & Bernardi, 2014)
Summary
Precision agriculture is a management concept that takes into account the spatial variability of an area, aiming to maximize economic return and minimize risks of environmental damage, through agricultural practices based on information technologies (Inamasu et al, 2011). It can be understood as a cycle that begins with data collection, continuing through analyses, interpretation of obtained information, generation of recommendations, and application in the field, aiming the evaluation of results (Gebbers & Adamchuk, 2010). The information obtained by yield mapping can be used for several analyses and interferences in the field
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