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Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method

SIMPLE SUMMARY: The quality of chilled meat is difficult to predict because many quality indexes need to be considered. The waste of meat resources caused by improper storage has caused huge economic losses in the meat industry. The entropy weight method (EWM) was widely used as an effective method...

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Autores principales: Zhao, Songsong, Lin, Hengxun, Li, Shuangqing, Liu, Chenghao, Meng, Junhong, Guan, Wenqiang, Liu, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179921/
https://www.ncbi.nlm.nih.gov/pubmed/35681879
http://dx.doi.org/10.3390/ani12111415
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author Zhao, Songsong
Lin, Hengxun
Li, Shuangqing
Liu, Chenghao
Meng, Junhong
Guan, Wenqiang
Liu, Bin
author_facet Zhao, Songsong
Lin, Hengxun
Li, Shuangqing
Liu, Chenghao
Meng, Junhong
Guan, Wenqiang
Liu, Bin
author_sort Zhao, Songsong
collection PubMed
description SIMPLE SUMMARY: The quality of chilled meat is difficult to predict because many quality indexes need to be considered. The waste of meat resources caused by improper storage has caused huge economic losses in the meat industry. The entropy weight method (EWM) was widely used as an effective method of infusion of multiple attributes into a single index of food quality. In this study, the model based on the entropy weight method was used to predict and comprehensively evaluate the quality changes in chilled pork, and the relative error range between the measured and predicted shelf life was lower than 11%. The modeling based on EWM integrates the information from each quality index and provides accurate quality prediction, which will enable the food industry to enhance accurate judging of the shelf life and safety of meat. ABSTRACT: The entropy weight method (EWM) was developed and used to integrate multiple quality indexes of pork to generate a comprehensive measure of quality. The Arrhenius equation and chemical kinetic reaction were used to fit and generate the shelf life prediction model. The pork was stored at the temperatures of 7 °C, 4 °C, 1 °C and −1 °C. Quality indexes, such as drip loss, color, shear force, pH, TAC, TVB-N and TBARS were measured. The results show that low temperatures effectively delay microbial growth and lipid oxidation. The regression coefficients (R(2)) for the comprehensive scores at each temperature were greater than 0.973 and the activation energy Ea was 9.7354 × 104 kJ mol(−1). The predicted shelf life of pork stored at 7 °C, 4 °C, 1 °C and −1 °C was 4.35 d, 6.85 d, 10.88 d and 14.90 d, respectively. In conclusion, EWM is an effective method to predict the shelf life of chilled/supercooled pork.
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spelling pubmed-91799212022-06-10 Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method Zhao, Songsong Lin, Hengxun Li, Shuangqing Liu, Chenghao Meng, Junhong Guan, Wenqiang Liu, Bin Animals (Basel) Article SIMPLE SUMMARY: The quality of chilled meat is difficult to predict because many quality indexes need to be considered. The waste of meat resources caused by improper storage has caused huge economic losses in the meat industry. The entropy weight method (EWM) was widely used as an effective method of infusion of multiple attributes into a single index of food quality. In this study, the model based on the entropy weight method was used to predict and comprehensively evaluate the quality changes in chilled pork, and the relative error range between the measured and predicted shelf life was lower than 11%. The modeling based on EWM integrates the information from each quality index and provides accurate quality prediction, which will enable the food industry to enhance accurate judging of the shelf life and safety of meat. ABSTRACT: The entropy weight method (EWM) was developed and used to integrate multiple quality indexes of pork to generate a comprehensive measure of quality. The Arrhenius equation and chemical kinetic reaction were used to fit and generate the shelf life prediction model. The pork was stored at the temperatures of 7 °C, 4 °C, 1 °C and −1 °C. Quality indexes, such as drip loss, color, shear force, pH, TAC, TVB-N and TBARS were measured. The results show that low temperatures effectively delay microbial growth and lipid oxidation. The regression coefficients (R(2)) for the comprehensive scores at each temperature were greater than 0.973 and the activation energy Ea was 9.7354 × 104 kJ mol(−1). The predicted shelf life of pork stored at 7 °C, 4 °C, 1 °C and −1 °C was 4.35 d, 6.85 d, 10.88 d and 14.90 d, respectively. In conclusion, EWM is an effective method to predict the shelf life of chilled/supercooled pork. MDPI 2022-05-30 /pmc/articles/PMC9179921/ /pubmed/35681879 http://dx.doi.org/10.3390/ani12111415 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhao, Songsong
Lin, Hengxun
Li, Shuangqing
Liu, Chenghao
Meng, Junhong
Guan, Wenqiang
Liu, Bin
Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method
title Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method
title_full Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method
title_fullStr Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method
title_full_unstemmed Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method
title_short Modeling of Chilled/Supercooled Pork Storage Quality Based on the Entropy Weight Method
title_sort modeling of chilled/supercooled pork storage quality based on the entropy weight method
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179921/
https://www.ncbi.nlm.nih.gov/pubmed/35681879
http://dx.doi.org/10.3390/ani12111415
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