Using hyperspectral imaging technology and machine learning algorithms for assessing internal quality parameters of apple fruits-Reference-Cited by-同舟云学术

Using hyperspectral imaging technology and machine learning algorithms for assessing internal quality parameters of apple fruits

Published:2022-11 Issue: Volume:230 Page:104650
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Çetin Necati,Karaman Kevser,Kavuncuoğlu Erhan,Yıldırım Bekir,Jahanbakhshi Ahmad

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference59 articles.

1. Prediction of firmness and soluble solids content of blueberries using hyperspectral reflectance imaging;Leiva-Valenzuela;J. Food Eng.,2013

2. Real-time grain impurity sensing for rice combine harvesters using image processing and decision-tree algorithm;Chen;Comput. Electron. Agric.,2020

3. Accurate non-destructive prediction of peach fruit internal quality and physiological maturity with a single scan using near infrared spectroscopy;Minas;Food Chem.,2021

4. Integrated spectral and image analysis of hyperspectral scattering data for prediction of apple fruit firmness and soluble solids content;Mendoza;Postharvest Biol. Technol.,2011

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