- ASA 2022 Data-Driven Decision Making
- A cura di Enrico di Bella, Luigi Fabbris, Corrado Lagazio
On the utility of treating a vineyard against Plasmopara viticola: a Bayesian analysis
- Lorenzo Valleggi
- Federico Mattia Stefanini
- © 2023 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-0106-3.41
Plasmopara viticola is the causal agent of the downy mildew, the most severe disease of grapevines. In order to prevent and/or mitigate the plant disease, fungicide treatments are often required, despite the presence of side effects on the environment and the potential hazard for human health in case of prolonged exposition. The choice of proper treatments and optimal scheduling is the key to managing downy mildew in an eco-friendly way. Plasmopara viticola’s growth depends on meteorological variables, like temperature and rain, plant’s genotype, the degree of exposition to oospores and soil conditions. Field measurements are expensive both for the high cost of oospore sensors and for the need of meteorological sensors describing the microclimate around each plant. Whatever the amount of information gathered from sensors of a vineyard, a decision must be taken, e.g. according to the predicted probability of infected leaves (and grapes) and considering side effects like the impact of a chemical treatment on the soil and on biodiversity. A multi-attribute utility function on variables describing future consequences of a decision may be defined by following the assumptions of utility independence and preferential independence. The inherent uncertainty is described by a Bayesian prior-predictive distribution where prior are elicited from experts, and eventually updated using available data. The resulting optimal decision is defined as the argument that maximises the expected value of the utility function. The proposed utility function may be tuned to match the individual preference scheme of the winegrower and eventually extended to include further variables like those describing the quality and yield of grapes.
- Keywords:
- Optimal decision,
- Precision agriculture,
- Phytopathogen,
- Sustainability,
University of Florence, Italy - ORCID: 0000-0002-8529-3046
University of Milan, Italy - ORCID: 0000-0003-4248-6275
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Informazioni sul capitolo
Titolo del capitolo
On the utility of treating a vineyard against Plasmopara viticola: a Bayesian analysis
Autori
Lorenzo Valleggi, Federico Mattia Stefanini
Lingua
English
DOI
10.36253/979-12-215-0106-3.41
Opera sottoposta a peer review
Anno di pubblicazione
2023
Copyright
© 2023 Author(s)
Licenza d'uso
Licenza dei metadati
Informazioni bibliografiche
Titolo del libro
ASA 2022 Data-Driven Decision Making
Sottotitolo del libro
Book of short papers
Curatori
Enrico di Bella, Luigi Fabbris, Corrado Lagazio
Opera sottoposta a peer review
Anno di pubblicazione
2023
Copyright
© 2023 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press, Genova University Press
DOI
10.36253/979-12-215-0106-3
eISBN (pdf)
979-12-215-0106-3
eISBN (xml)
979-12-215-0107-0
Collana
Proceedings e report
ISSN della collana
2704-601X
e-ISSN della collana
2704-5846