Integrating yield and protein spatial information: a framework for analysis and interpretation

Abstract

Although precision agriculture tools employed by farm managers have the capability to provide data-rich information, agronomic interpretation of this information lags well behind. Protein mapping, using remote or on-board sensor technology, is set to improve this interpretation, but a framework is needed that can extract the maximum value from these data. We have collected coincidental yield and protein data sets across cereal crops in northern Australia for 3 years, and a number of useful strategies have been demonstrated that maximise the extraction of agronomic information for advisers and farm managers. Nitrogen (N) management, using N removal, N supply and N deficit maps, and probability maps, that estimate the likelihood of response to applied N, can be obtained with coincidental yield/protein maps. Water use efficiency and starting-soil moisture supplies, using reverse-cycle modelling, can also be verified from these layers. Economic interpretations, using gross margins and sensitivity analyses, can similarly be provided. Issues still to be resolved in mapping coincidental maps are discussed.