Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat-Reference-Cited by-同舟云学术

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Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat

Published:2016-10 Issue: Volume:72 Page:322-329
ISSN:0023-6438
Container-title:LWT - Food Science and Technology
language:en
Short-container-title:LWT - Food Science and Technology

Author:

Cheng Weiwei,Sun Da-Wen^ORCID,Pu Hongbin,Liu Yuwei

Funder

International S&T Cooperation Program of China

National Key Technologies R&D Program

International S&T Cooperation Projects of Guangdong Province

Natural Science Foundation of Guangdong Province

Key Projects of Administration of Ocean and Fisheries of Guangdong Province

Collaborative Innovation Major Special Projects of Guangzhou City

Publisher

Elsevier BV

Subject

Food Science

Reference66 articles.

1. Variable selection in regression –a tutorial;Andersen;Journal of Chemometrics,2010

2. The successive projections algorithm for variable selection in spectroscopic multicomponent analysis;Araújo;Chemometrics and Intelligent Laboratory Systems,2001

3. Near-infrared hyperspectral imaging for grading and classification of pork;Barbin;Meat Science,2012

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

5. Non-destructive assessment of microbial contamination in porcine meat using NIR hyperspectral imaging;Barbin;Innovative Food Science & Emerging Technologies,2013

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