Wheat yield and protein content are spatially variable because of inherent spatial variability of factors affecting the yield at field scale. In Mediterranean environments, yield variability is often caused by the irregular weather pattern, particularly rainfall and by position on the landscape. The objective of this study was to determine the effects of landscape position and rainfall on spatial variability of wheat yield and protein in a rolling terrain field of Southern Italy, and to propose stable management areas through simulation modelling and georesistivity imaging in rolling landscape. The study was carried out in Southern Italy, during 2 years of wheat monoculture; extensive soil properties and in-season plant measurements were measured. This study showed that soil water content was the main factor affecting spatial variation of yield for both years. The interactions between rainfall, topography and soil attributes increase the chances to observe yield variability among years. The principal component analysis demonstrated that for both years, soil water content explained most of the variability. The crop simulation model provided excellent results when compared with measured data with root mean square error of 0.2 t ha)1. The simulated cumulative probability function showed that the model was able to confirm the yield temporal stability of three different zones.

Landscape position and precipitation effects on spatial variability of wheat yield and grain protein in southern Italy

BASSO, Bruno;AMATO, Mariana;
2009

Abstract

Wheat yield and protein content are spatially variable because of inherent spatial variability of factors affecting the yield at field scale. In Mediterranean environments, yield variability is often caused by the irregular weather pattern, particularly rainfall and by position on the landscape. The objective of this study was to determine the effects of landscape position and rainfall on spatial variability of wheat yield and protein in a rolling terrain field of Southern Italy, and to propose stable management areas through simulation modelling and georesistivity imaging in rolling landscape. The study was carried out in Southern Italy, during 2 years of wheat monoculture; extensive soil properties and in-season plant measurements were measured. This study showed that soil water content was the main factor affecting spatial variation of yield for both years. The interactions between rainfall, topography and soil attributes increase the chances to observe yield variability among years. The principal component analysis demonstrated that for both years, soil water content explained most of the variability. The crop simulation model provided excellent results when compared with measured data with root mean square error of 0.2 t ha)1. The simulated cumulative probability function showed that the model was able to confirm the yield temporal stability of three different zones.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11563/1929
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