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A Reliable Method to Recognize Soybean Seed Maturation Stages Based on Autofluorescence-Spectral Imaging Combined With Machine Learning Algorithms

In recent years, technological innovations have allowed significant advances in the diagnosis of seed quality. Seeds with superior physiological quality are those with the highest level of physiological maturity and the integration of rapid and precise methods to separate them contributes to better...

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Detalles Bibliográficos
Autores principales: Batista, Thiago Barbosa, Mastrangelo, Clíssia Barboza, de Medeiros, André Dantas, Petronilio, Ana Carolina Picinini, Fonseca de Oliveira, Gustavo Roberto, dos Santos, Isabela Lopes, Crusciol, Carlos Alexandre Costa, Amaral da Silva, Edvaldo Aparecido
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237540/
https://www.ncbi.nlm.nih.gov/pubmed/35774807
http://dx.doi.org/10.3389/fpls.2022.914287