Predicting the probability that higher profits could be achieved by adopting PA

Murdoch, A. J., Todman, L. ORCID: https://orcid.org/0000-0003-1232-294X, Mahmood, S. A., Karampoiki, M., Paraforos, D. S., Antognelli, S., Guidotti, D., Ranieri, E., Ahrholz, T., Petri, J. and Engel, T. (2021) Predicting the probability that higher profits could be achieved by adopting PA. In: Precision agriculture '21, July 2021, Budapest, pp. 941-947. doi: 10.3920/978-90-8686-916-9_113 (9789086863631)

Abstract/Summary

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.

Item Type	Conference or Workshop Item (Paper)
URI	https://reading-clone.eprints-hosting.org/id/eprint/103132
Identification Number/DOI	10.3920/978-90-8686-916-9_113
Refereed	Yes
Divisions	Life Sciences > School of Agriculture, Policy and Development > Department of Crop Science
Uncontrolled Keywords	wheat, maps, grain yield, grain protein, probability, Bayesian Network
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