Boosting grapevine phenological stages prediction based on climatic data by pseudo-labeling approach

Boosting grapevine phenological stages prediction based on climatic data by pseudo-labeling approach

Predicting grapevine phenological stages (GPHS) is critical for precisely managing vineyard operations, including plant disease treatments, pruning, and harvest. Solutions commonly used to address viticulture challenges rely on image processing techniques, which have achieved significant results. Ho...

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Bibliographic Details
Main Authors: Mehdi Fasihi, Mirko Sodini, Alex Falcon, Francesco Degano, Paolo Sivilotti, Giuseppe Serra
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-09-01
Series:Artificial Intelligence in Agriculture
Subjects:
Grapevine phenological stages prediction
Climatic data
Supervised learning
Semi-supervised learning
Machine learning
Pseudo-labeling approach
Online Access:http://www.sciencedirect.com/science/article/pii/S2589721725000303
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