Predicting Predawn Leaf Water Potential up to Seven Days Using Machine Learning

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2021

Autores

Ahmed A. Fares (Autor) Outra; Fabio Vasconcelos (Autor) Outra; João Mendes Moreira (Autor) FEUP; Carlos Ferreira (Autor) Outra

Ata de Conferência Internacional

Título: PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2021)

Páginas: 39-50

20th EPIA Conference on Artificial Intelligence (EPIA)

ELECTR NETWORK, SEP 07-09, 2021

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00V-CMQ

DOI: 10.1007/978-3-030-86230-5_4

Abstract (EN): Sustainable agricultural production requires a controlled usage of water, nutrients, and minerals from the environment. Different strategies of plant irrigation are being studied to control the quantity and quality balance of the fruits. Regarding efficient irrigation, particularly in deficit irrigation strategies, it is essential to act according to water stress status in the plant. For example, in the vine, to improve the quality of the grapes, the plants are deprived of water until they reach particular water stress before re-watered in specified phenological stages. The water status inside the plant is estimated by measuring either the Leaf Potential during the Predawn or soil water potential, along with the root zones. Measuring soil water potential has the advantage of being independent of diurnal atmospheric variations. However, this method has many logistic problems, making it very hard to apply along all the yard, especially the big ones. In this study, the Predawn Leaf Water Potential (PLWP) is daily predicted by Machine Learning models using data such as grapes variety, soil characteristics, irrigation schedules, and meteorological data. The benefits of these techniques are the reduction of the manual work of measuring PLWP and the capacity to implement those models on a larger scale by predicting PLWP up to 7 days which should enhance the ability to optimize the irrigation plan while the quantity and quality of the crop are under control.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12