Prediction of beef freshness attributes using reflectance spectroscopy-Reference-Cited by-同舟云学术

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Prediction of beef freshness attributes using reflectance spectroscopy

Published:2017-10 Issue:4 Volume:10 Page:243-248
ISSN:1881-8366
Container-title:Engineering in Agriculture, Environment and Food
language:en
Short-container-title:Engineering in Agriculture, Environment and Food

Author:

Choi Chang-Hyun,Lee Dae-Hyun,Kim Yong-Joo,Kim Byung-Sam,Kim Jong-Hun

Funder

Korea Food Research Institute (KFRI)

Publisher

Asian Agricultural and Biological Engineering Association

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,Food Science

Reference26 articles.

1. Chemical and discriminant analysis of bovine meat by near infrared reflectance spectroscopy (NIRS);Alomar;Meat Sci.,2003

2. The use of visible and near infrared reflectance spectroscopy to predict beef M. Longissimus thoracis et lumborum quality attributes;Andrés;Meat Sci.,2008

3. Compendium of Methods for the Microbiological Examination of Foods;APHA,2001

4. Beef quality perception at the point of purchase: a study from Portugal;Banovic;Food Qual. Prefer.,2009

5. Determination of total volatile basic nitrogen (TVB-N) content and Warner–Bratzler shear force (WBSF) in pork using Fourier transform near infrared (FT-NIR) spectroscopy;Cai;Food Chem.,2011

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Revealing the spoilage characteristics of refrigerated prepared beef steak by advanced bioinformatics tools;Journal of the Science of Food and Agriculture;2024-06-25

2. Determination of the total viable count of Chinese meat dishes by near‐infrared spectroscopy: A predictive model;Journal of Food Processing and Preservation;2021-11-06

3. Current Detection Techniques for Monitoring the Freshness of Meat-Based Products: A Review;Journal of Packaging Technology and Research;2021-09-01

4. Rapid detection of freshness of refrigerated grouper (Epinephelus coioides) fillets by near-infrared spectroscopy and quality index method;J APPL SCI ENG;2020

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