Predicting the probability that higher profits could be achieved by adopting PA
2021
Murdoch, A. J. | Todman, L. | Mahmood, S. A. | Karampoiki, M. | Paraforos, D. S. | Antognelli, S. | Guidotti, D. | Ranieri, E. | Ahrholz, T. | Petri, J. | Engel, T.
Algorithms were developed to predict spatial variation of yield and quality within winter wheat crops intended for bread-making. Bayesian networks were used to predict spatial probability maps of yield and quality based on data sources including yield maps, fertiliser applications, soil variables and Sentinel 2 satellite data. Results presented here for five UK fields show that there was a 65% likelihood of achieving a grain protein premium with variable rate nitrogen application compared to 50% with uniform N. Achieving this premium would increase revenues by £150/ha. A similar comparison for five German fields did not demonstrate a higher probability of profit.
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