Non-destructive detection of freshness in crayfish (Procambarus clarkii) based on near-infrared spectroscopy combined with deep learning-Reference-Cited by-同舟云学术

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Non-destructive detection of freshness in crayfish (Procambarus clarkii) based on near-infrared spectroscopy combined with deep learning

Published:2025-02 Issue: Volume:168 Page:110858
ISSN:0956-7135
Container-title:Food Control
language:en
Short-container-title:Food Control

Author:

Han Qing-li,Lu Jian-feng^ORCID,Zhu Jiao-jiao,Lin Lin,Zheng Zhi,Jiang Shao-tong

Funder

Earmarked Fund for China Agriculture Research System

Publisher

Elsevier BV

Reference46 articles.

1. Deep learning modelling techniques: Current progress, applications, advantages, and challenges;Ahmed;Artificial Intelligence Review,2023

2. Shortwave infrared hyperspectral imaging system coupled with multivariable method for TVB-N measurement in pork;Baek;Food Control,2021

3. Non-destructive determination of chemical composition in intact and minced pork using near-infrared hyperspectral imaging;Barbin;Food Chemistry,2013

4. Rapid measurement of sardine freshness by using visible and near infrared spectroscopy;Cayuela-Sánchez;Journal of Food Composition and Analysis,2024

5. A comparison of eating safety and quality of live and dead freshwater crayfish (Procambarus clarkii) at different stages;Chen;Food Research International,2022

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