ArticleCurrent research in food science2023
Mathematical modeling for freshness/spoilage of chicken breast using chemometric analysis.
Article in Current research in food science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Chitosan-PVA composite films incorporated with roselle anthocyanins: Colorimetric smart sensor for real-time monitoring of meat and seafood freshness.Food chemistry: X · 2026Article
- Utilizing drip metabolites and predictive modeling for non-destructive freshness assessment in pork loin.NPJ science of food · 2025Article
- Combination model for freshness prediction of pork using VIS/NIR hyperspectral imaging with chemometrics.Animal bioscience · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chicken meat spoilage is a significant concern for food safety and quality, and this study aims to predict the spoilage point of chicken breast meat through various attributes and metabolites. Chicken meat was stored in anaerobic packaging at 4 °C for 13 days, and various meat quality attributes (pH, drip loss, color, volatile basic nitrogen [VBN], total aerobic bacteria [TAB], and metabolites) were examined. First, the spoiled point (VBN >20 mg/100 g and/or TAB >7 log CFU/g) of the chicken breast meat was determined. Using univariate and multivariate analyses, twenty-four candidate metabolites were identified. A receiver operating characteristic (ROC) analysis was used to validate the obtained binary logistic regression model using nine metabolites (proline, methionine, glutamate, threonine, acetate, uridine 5'-monophosphate, hypoxanthine, glycine, and glutamine). The results showed a high area under the ROC curve value (0.992). Thus, this study confirmed the predictability of spoilage points in chicken breast meat through these nine metabolites.
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