Estimation of Soluble Solids for Stone Fruit Varieties Based on Near-Infrared Spectra Using Machine Learning Techniques

Estimation of Soluble Solids for Stone Fruit Varieties Based on Near-Infrared Spectra Using Machine Learning Techniques

The quality control for fruit maturity inspection is a key issue in fruit packaging and international trade. The quantification of Soluble Solids (SS) in fruits gives a good approximation of the total sugar concentration at the ripe stage, and on the other hand, SS alone or in combination with acidi...

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Bibliographic Details
Main Authors: Pedro Escárate, Gonzalo Farias, Paulina Naranjo, Juan Pablo Zoffoli
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Sensors
Subjects:
stone fruits
fruit quality
soluble solids
near infrared spectra
visible spectra
convolutional neural networks
Online Access:https://www.mdpi.com/1424-8220/22/16/6081

Internet

https://www.mdpi.com/1424-8220/22/16/6081

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