Smart and accurate: A new tool to identify stressed soybean seeds based on multispectral images and machine learning models

Smart and accurate: A new tool to identify stressed soybean seeds based on multispectral images and machine learning models

Extreme environmental conditions have been recurrent during the last few years and have impacted crop seed quality worldwide, mainly but not limited to, soybeans (Glycine max (L) Merrill). To overcome this, seed companies often demand innovative tools to address seed quality factors. Machine learnin...

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Bibliographic Details
Main Authors: Ana Carolina Picinini Petronilio, Clíssia Barboza Mastrangelo, Thiago Barbosa Batista, Gustavo Roberto Fonseca de Oliveira, Isabela Lopes dos Santos, Edvaldo Aparecido Amaral da Silva
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Smart Agricultural Technology
Subjects:
Environmental stress
Seed quality
Green seed problem
Chlorophyll fluorescence
Reflectance
Seed physical properties
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525002758
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