A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains

The high perishability of fresh meat results in short sales and consumption periods, which can lead to high amounts of food waste, especially when a fixed best-before date is stated. Thus, the aim of this study was the development of a real-time dynamic shelf-life criterion (DSLC) for fresh pork fil...

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Autores principales:	Antonia Albrecht, Maureen Mittler, Martin Hebel, Claudia Waldhans, Ulrike Herbert, Judith Kreyenschmidt
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	predictive microbiology dynamic shelf-life meat quality meat spoilage sensory modeling food waste prevention Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/02a4ceb1ead0402f8995a42639cc4099
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id	oai:doaj.org-article:02a4ceb1ead0402f8995a42639cc4099
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spelling	oai:doaj.org-article:02a4ceb1ead0402f8995a42639cc40992021-11-25T17:35:00ZA Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains10.3390/foods101127402304-8158https://doaj.org/article/02a4ceb1ead0402f8995a42639cc40992021-11-01T00:00:00Zhttps://www.mdpi.com/2304-8158/10/11/2740https://doaj.org/toc/2304-8158The high perishability of fresh meat results in short sales and consumption periods, which can lead to high amounts of food waste, especially when a fixed best-before date is stated. Thus, the aim of this study was the development of a real-time dynamic shelf-life criterion (DSLC) for fresh pork filets based on a multi-model approach combining predictive microbiology and sensory modeling. Therefore, 647 samples of ma-packed pork loin were investigated in isothermal and non-isothermal storage trials. For the identification of the most suitable spoilage predictors, typical meat quality parameters (pH-value, color, texture, and sensory characteristics) as well as microbial contamination (total viable count, <i>Pseudomonas</i> spp., lactic acid bacteria, <i>Brochothrix thermosphacta</i>, Enterobacteriaceae) were analyzed at specific investigation points. Dynamic modeling was conducted using a combination of the modified Gompertz model (microbial data) or a linear approach (sensory data) and the Arrhenius model. Based on these models, a four-point scale grading system for the DSLC was developed to predict the product status and shelf-life as a function of temperature data in the supply chain. The applicability of the DSLC was validated in a pilot study under real chain conditions and showed an accurate real-time prediction of the product status.Antonia AlbrechtMaureen MittlerMartin HebelClaudia WaldhansUlrike HerbertJudith KreyenschmidtMDPI AGarticlepredictive microbiologydynamic shelf-lifemeat qualitymeat spoilagesensory modelingfood waste preventionChemical technologyTP1-1185ENFoods, Vol 10, Iss 2740, p 2740 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	predictive microbiology dynamic shelf-life meat quality meat spoilage sensory modeling food waste prevention Chemical technology TP1-1185
spellingShingle	predictive microbiology dynamic shelf-life meat quality meat spoilage sensory modeling food waste prevention Chemical technology TP1-1185 Antonia Albrecht Maureen Mittler Martin Hebel Claudia Waldhans Ulrike Herbert Judith Kreyenschmidt A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains
description	The high perishability of fresh meat results in short sales and consumption periods, which can lead to high amounts of food waste, especially when a fixed best-before date is stated. Thus, the aim of this study was the development of a real-time dynamic shelf-life criterion (DSLC) for fresh pork filets based on a multi-model approach combining predictive microbiology and sensory modeling. Therefore, 647 samples of ma-packed pork loin were investigated in isothermal and non-isothermal storage trials. For the identification of the most suitable spoilage predictors, typical meat quality parameters (pH-value, color, texture, and sensory characteristics) as well as microbial contamination (total viable count, <i>Pseudomonas</i> spp., lactic acid bacteria, <i>Brochothrix thermosphacta</i>, Enterobacteriaceae) were analyzed at specific investigation points. Dynamic modeling was conducted using a combination of the modified Gompertz model (microbial data) or a linear approach (sensory data) and the Arrhenius model. Based on these models, a four-point scale grading system for the DSLC was developed to predict the product status and shelf-life as a function of temperature data in the supply chain. The applicability of the DSLC was validated in a pilot study under real chain conditions and showed an accurate real-time prediction of the product status.
format	article
author	Antonia Albrecht Maureen Mittler Martin Hebel Claudia Waldhans Ulrike Herbert Judith Kreyenschmidt
author_facet	Antonia Albrecht Maureen Mittler Martin Hebel Claudia Waldhans Ulrike Herbert Judith Kreyenschmidt
author_sort	Antonia Albrecht
title	A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains
title_short	A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains
title_full	A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains
title_fullStr	A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains
title_full_unstemmed	A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains
title_sort	multi-model approach to implement a dynamic shelf life criterion in meat supply chains
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/02a4ceb1ead0402f8995a42639cc4099
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A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains

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