A loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopy

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dc.contributor.authorBreure, Timo Samuel
dc.contributor.authorHaefele, S. M.
dc.contributor.authorHannam, Jacqueline A.
dc.contributor.authorCorstanje, Ronald
dc.contributor.authorWebster, R.
dc.contributor.authorMoreno-Rojas, S.
dc.contributor.authorMilne, A. E.
dc.date.accessioned2022-03-28T10:25:41Z
dc.date.available2022-03-28T10:25:41Z
dc.date.issued2022-03-12
dc.description.abstractModern sensor technologies can provide detailed information about soil variation which allows for more precise application of fertiliser to minimise environmental harm imposed by agriculture. However, growers should lose neither income nor yield from associated uncertainties of predicted nutrient concentrations and thus one must acknowledge and account for uncertainties. A framework is presented that accounts for the uncertainty and determines the cost–benefit of data on available phosphorus (P) and potassium (K) in the soil determined from sensors. For four fields, the uncertainty associated with variation in soil P and K predicted from sensors was determined. Using published fertiliser dose–yield response curves for a horticultural crop the effect of estimation errors from sensor data on expected financial losses was quantified. The expected losses from optimal precise application were compared with the losses expected from uniform fertiliser application (equivalent to little or no knowledge on soil variation). The asymmetry of the loss function meant that underestimation of P and K generally led to greater losses than the losses from overestimation. This study shows that substantial financial gains can be obtained from sensor-based precise application of P and K fertiliser, with savings of up to £121 ha−1 for P and up to £81 ha−1 for K, with concurrent environmental benefits due to a reduction of 4–17 kg ha−1 applied P fertiliser when compared with uniform application.en_UK
dc.description.sponsorshipBiotechnology and Biological Sciences Research Council (BBSRC): BBS/E/C/000I0320; BBS/E/C/000I0330; BBS/E/C/000I0100.en_UK
dc.identifier.citationBreure TS, Haefele SM, Hannam JA, et al., (2022) A loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopy, Precision Agriculture, Volume 23, Issue 4, August 2022, pp. 1333–1353en_UK
dc.identifier.eissn1573-1618
dc.identifier.issn1385-2256
dc.identifier.urihttps://doi.org/10.1007/s11119-022-09887-2
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/17692
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectGeostatisticsen_UK
dc.subjectPrecision agricultureen_UK
dc.subjectVariable-rate applicationen_UK
dc.subjectProximal soil sensingen_UK
dc.subjectX-ray fuorescenceen_UK
dc.titleA loss function to evaluate agricultural decision-making under uncertainty: a case study of soil spectroscopyen_UK
dc.typeArticleen_UK

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