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

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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Bibliographic Details
Main Authors: Thiago Barbosa Batista, Clíssia Barboza Mastrangelo, André Dantas de Medeiros, Ana Carolina Picinini Petronilio, Gustavo Roberto Fonseca de Oliveira, Isabela Lopes dos Santos, Carlos Alexandre Costa Crusciol, Edvaldo Aparecido Amaral da Silva
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Plant Science
Subjects:
seed maturity
seed quality
support vector machine
chlorophyll fluorescence
Glycine max
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2022.914287/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2022.914287/full

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