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Estimation of Water Stress in Potato Plants Using Hyperspectral Imagery and Machine Learning Algorithms

This work presents quantitative detection of water stress and estimation of the water stress level: none, light, moderate, and severe on potato crops. We use hyperspectral imagery and state of the art machine learning algorithms: random decision forest, multilayer perceptron, convolutional neural...

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Main Authors: Duarte Carvajalino, Julio Martin, Silva Arero, Elías Alexander, Góez Vinasco, Gerardo Antonio, Torres Delgado, Laura Marcela, Ocampo Paez, Oscar Dubán, Castaño Marín, Angela María
Format: Artículo
Language:Español
Published: MDPI 2025
Subjects:
Producción y tratamiento de semillas - F03
Solanum tuberosum
Estrés de sequia
Marchitamiento
Raíces y tubérculos
http://aims.fao.org/aos/agrovoc/c_7221
http://aims.fao.org/aos/agrovoc/c_24993
http://aims.fao.org/aos/agrovoc/c_8390
Online Access:http://hdl.handle.net/20.500.12324/41212
https://doi.org/10.3390/horticulturae7070176

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