A Multidisciplinary Approach for Predicting the Microbiological Spoilage of Chicken Breast Fillets due to Cold-Chain Disruption

Cold-chain disruptions during the storage and distribution of raw poultry can significantly reduce product shelf-life and safety. This study evaluated the effects of short-term cyclic temperature abuse (TA) on the retail shelf-life of fresh chicken breast, using a multidisciplinary approach that combined food microbiology, machine learning (ML), metagenomics, and volatile compound (VC) analysis. Boneless, skinless chicken breast trays (n = 450) were obtained from a commercial poultry processor and transported under refrigeration (4 °C) to Auburn University. In three independent trials, trays were randomly assigned to one of three treatments: (1) Control at 4 °C for 24 h; (2) TA Cycle 1: alternating 30 min at 4 °C and 1 h at 30 °C; and (3) TA Cycle 2: alternating 30 min at 4 °C and 1 h at 37 °C. TA cycles lasted 7.5 h, after which all trays were stored at 4 °C. Samples were analyzed on days 0, 2, 4, 6, and 8 for aerobic, facultative anaerobic, and lactic acid bacteria (LAB) counts, and for VCs using an electronic nose. Rinsates from Trial 3 were stored at -80 °C for metagenomic analysis. TA Cycle 2 resulted in the highest spoilage rates, followed by TA Cycle 1. A neural network model moderately predicted bacterial growth (R<sup>2</sup> = 0.65-0.75 for aerobic and facultative anaerobic microorganisms; lower for LAB). Metagenomics demonstrated a shift toward Pseudomonas spp. dominance under TA conditions, while control samples retained microbial diversity. These findings underscore that even short-term TA significantly alters the microbiome and accelerates spoilage in raw poultry, emphasizing the importance of cold-chain integrity. Practical Relevance. This study shows that short, high-temperature abuse events from refrigeration failure, handling delays, or other supply chain disruptions can accelerate spoilage in raw chicken. By combining rapid spoilage-detection tools with predictive models, poultry producers and retailers may better monitor these events, helping to maintain cold-chain integrity and reduce losses.

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Publication Details

Journal
Journal of Food Protection
Published
2026-03-12
DOI
https://doi.org/10.1016/j.jfp.2026.100754
Primary Topic
Meat and Animal Product Quality
Type
article
Field-Weighted Citation Impact
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article

A Multidisciplinary Approach for Predicting the Microbiological Spoilage of Chicken Breast Fillets due to Cold-Chain Disruption

Kate Trout, Laura J. Garner, Katherine Paternina-Sierra, Sungeun Cho et al.
Journal of Food Protection
Meat and Animal Product Quality
article

A Multidisciplinary Approach for Predicting the Microbiological Spoilage of Chicken Breast Fillets due to Cold-Chain Disruption

Kate Trout, Laura J. Garner, Katherine Paternina-Sierra, Sungeun Cho, Jodie M. Jones, Cameron Smith, Payten Leeds, Jakob Doster, Madison Sirmon, Zhen Jia, Mahmoud Almasri, Telah Black, Joe Hanna, Amit Morey, Haitao Li, Vianca Maite Tashiguano
article en

Abstract

Cold-chain disruptions during the storage and distribution of raw poultry can significantly reduce product shelf-life and safety. This study evaluated the effects of short-term cyclic temperature abuse (TA) on the retail shelf-life of fresh chicken breast, using a multidisciplinary approach that combined food microbiology, machine learning (ML), metagenomics, and volatile compound (VC) analysis. Boneless, skinless chicken breast trays (n = 450) were obtained from a commercial poultry processor and transported under refrigeration (4 °C) to Auburn University. In three independent trials, trays were randomly assigned to one of three treatments: (1) Control at 4 °C for 24 h; (2) TA Cycle 1: alternating 30 min at 4 °C and 1 h at 30 °C; and (3) TA Cycle 2: alternating 30 min at 4 °C and 1 h at 37 °C. TA cycles lasted 7.5 h, after which all trays were stored at 4 °C. Samples were analyzed on days 0, 2, 4, 6, and 8 for aerobic, facultative anaerobic, and lactic acid bacteria (LAB) counts, and for VCs using an electronic nose. Rinsates from Trial 3 were stored at -80 °C for metagenomic analysis. TA Cycle 2 resulted in the highest spoilage rates, followed by TA Cycle 1. A neural network model moderately predicted bacterial growth (R<sup>2</sup> = 0.65-0.75 for aerobic and facultative anaerobic microorganisms; lower for LAB). Metagenomics demonstrated a shift toward Pseudomonas spp. dominance under TA conditions, while control samples retained microbial diversity. These findings underscore that even short-term TA significantly alters the microbiome and accelerates spoilage in raw poultry, emphasizing the importance of cold-chain integrity. Practical Relevance. This study shows that short, high-temperature abuse events from refrigeration failure, handling delays, or other supply chain disruptions can accelerate spoilage in raw chicken. By combining rapid spoilage-detection tools with predictive models, poultry producers and retailers may better monitor these events, helping to maintain cold-chain integrity and reduce losses.

Journal of Food ProtectionVol. 89(5)
University of Missouri–St. Louis (US), University of Missouri (US), Auburn University (US)
Zero hunger
Openalex Percentile: Top 23%
Meat and Animal Product Quality
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