3D-CNN detection of systemic symptoms induced by different Potexvirus infections in four Nicotiana benthamiana genotypes using leaf hyperspectral imaging

3D-CNN detection of systemic symptoms induced by different Potexvirus infections in four Nicotiana benthamiana genotypes using leaf hyperspectral imaging

Abstract Purpose Hyperspectral imaging combined with machine learning offers a promising, cost-effective alternative to invasive chemical analysis for early plant disease detection. In this study, the use of 3D Convolutional Neural Networks (3D-CNNs) was explored to detect presymptomatic viral infec...

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Bibliographic Details
Main Authors: Rizos-Theodoros Chadoulis, Ioannis Livieratos, Ioannis Manakos, Theodore Spanos, Zeinab Marouni, Christos Kalogeropoulos, Constantine Kotropoulos
Format: Article
Language:English
Published: BMC 2025-02-01
Series:Plant Methods
Subjects:
Artificial intelligence
Convolutional neural networks
Dimensionality reduction
Hyperspectral imaging
Early plant disease detection
Online Access:https://doi.org/10.1186/s13007-025-01337-0
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https://doi.org/10.1186/s13007-025-01337-0

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