Integrating farmer knowledge, precision agriculture tools, and crop simulation modelling to evaluate management options for poor-performing patches in cropping fields

Abstract

Cropping fields often have poor-performing patches. In an attempt to increase production on poor patches, farmers may apply additional fertiliser or ameliorants without economic or scientific justification. Improved understanding of the extent and causes of poor performance, management options, potential crop yield and economic benefits can give farmers the tools to consider management change. This paper presents an approach to integrating farmer knowledge, precision agriculture tools and crop simulation modelling to evaluate management options for poor-performing patches. We surveyed nine cropping fields in Western Australia and showed that (1) farmers have good understanding of the spatial extent and rank performance of poor-performing areas, when compared to NDVI or yield maps, (2) there is a wide range of physical and chemical soil constraints to crop yield in such patches, some of which can be ameliorated to raise yield potential, and others where crop inputs such as fertiliser can be better matched to low yield potential. Management options for poor-performing patches were evaluated through simulation analysis by removal of constraints to rooting to varying extents, and hence plant available water capacity. These examples show that if the constraint is mis-diagnosed then the potential benefits from amelioration can be overstated. In many cases constraints, often associated with physical limitations such as shallow available rooting depth or light-texture cannot be ameliorated or are uneconomic to ameliorate. In such cases the best intervention may be to lower crop inputs to better match the water-limited yield potential of such poor-performing areas. This research integrated farmer knowledge and spatial data to define yield zones in which targeted soil sampling and crop simulation were then used to determine yield potential and particular constraints to that potential. The economic costs and benefits of differential zone management were examined under a range of husbandry scenarios and, importantly, the sensitivity of economic gain to mis-diagnosis or errors in defining the zones was tested. This approach provided farmers with a robust and credible method for making decisions about spatial management of their fields.