A sensorless, Big Data based approach for phenology and meteorological drought forecasting in vineyards.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
05 Oct 2023
05 Oct 2023
Historique:
received:
27
06
2023
accepted:
03
10
2023
medline:
6
10
2023
pubmed:
6
10
2023
entrez:
5
10
2023
Statut:
epublish
Résumé
A web-based app was developed and tested to provide predictions of phenological stages of budburst, flowering and veraison, as well as warnings for meteorological drought. Such predictions are especially urgent under a climate change scenario where earlier phenology and water scarcity are increasingly frequent. By utilizing a calibration data set provided by 25 vineyards observed in the Emilia Romagna Region for two years (2021-2022), the above stages were predicted as per the binary event classification paradigm and selection of the best fitting algorithm based on the comparison between several metrics. The seasonal vineyard water balance was calculated by subtracting daily bare or grassed soil evapotranspiration (ET
Identifiants
pubmed: 37798342
doi: 10.1038/s41598-023-44019-4
pii: 10.1038/s41598-023-44019-4
pmc: PMC10556084
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
16818Subventions
Organisme : Regione Emilia-Romagna
ID : 5192993
Informations de copyright
© 2023. Springer Nature Limited.
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