The identification of homogeneous management zones within a field is crucial for variable rate application of agronomic inputs. This study 12 proposed a methodology to identify homogeneous management zones within a 8 ha field, based on the stability of measured and simulated yield 13 patterns in a maize–soybean–wheat crop rotation in north-east Italy. Crop growth and yield were simulated over a 14-year period (1989–2002) using 14 CERES-Maize, CROPGRO-Soybean and CERES-Wheat models to account for weather effects on yield spatial patterns. The overlay of long-term 15 assessments of yield spatial and temporal data allowed for the identification of two stable zones with different yield levels, one with greater yield 16 (called HS for high and stable yield) and one with lower yield (called LS for low and stable yield). The size of the HS zone identified using 14 17 years of simulated yield was smaller than the one obtained when considering only yield monitor data taken during the 5-year crop rotation. The LS 18 zone was larger when using simulated data, confirming that the consistency of temporal stability increased by increasing the years considered. The 19 models were able to closely simulate yield across the field when site-specific inputs were used, showing potential for use in yield map interpretation 20 in the context of precision agriculture. Results showed that a combination of GIS tools and crop growth simulation models can be used to identify 21 temporally stable zones, which is a fundamental prerequisite for adopting variable rate technologies.

Analyzing the effects of climate variability on spatial pattern of yield in a maize-wheat-soybean rotation

SARTORI, LUIGI;
2007

Abstract

The identification of homogeneous management zones within a field is crucial for variable rate application of agronomic inputs. This study 12 proposed a methodology to identify homogeneous management zones within a 8 ha field, based on the stability of measured and simulated yield 13 patterns in a maize–soybean–wheat crop rotation in north-east Italy. Crop growth and yield were simulated over a 14-year period (1989–2002) using 14 CERES-Maize, CROPGRO-Soybean and CERES-Wheat models to account for weather effects on yield spatial patterns. The overlay of long-term 15 assessments of yield spatial and temporal data allowed for the identification of two stable zones with different yield levels, one with greater yield 16 (called HS for high and stable yield) and one with lower yield (called LS for low and stable yield). The size of the HS zone identified using 14 17 years of simulated yield was smaller than the one obtained when considering only yield monitor data taken during the 5-year crop rotation. The LS 18 zone was larger when using simulated data, confirming that the consistency of temporal stability increased by increasing the years considered. The 19 models were able to closely simulate yield across the field when site-specific inputs were used, showing potential for use in yield map interpretation 20 in the context of precision agriculture. Results showed that a combination of GIS tools and crop growth simulation models can be used to identify 21 temporally stable zones, which is a fundamental prerequisite for adopting variable rate technologies.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2474688
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