Citation
Abstract
Next-Generation Sequencing (NGS) technology was applied to evaluate Food Safety Management System (FSMS) performance in seafood-processing factories by exploring microbiome diversity alongside traditional methods for detecting foodborne pathogens. A total of 210 environmental swabs collected from processing zones in six factories underwent 16S rRNA amplicon sequencing. FSMS-certified factories exhibited significantly higher species richness, with alpha diversity p-values of 0.0036 for observed ASVs, 0.0026 for Faith’s PD and 0.032 for Shannon. Beta diversity analysis also revealed significant differences, with p-values of 0.001 for Bray–Curtis, unweighted UniFrac and Jaccard. Pathogens like Listeria monocytogenes, Salmonella spp. and Bacillus cereus were present in “uncertified” factories but absent in the “certified” factories. The “certified” factories had a significantly higher proportion of lactic acid bacteria (LAB) genera (70.22%) compared to “uncertified” factories (29.78%). The LAB genera included Streptococcus, Lactococcus, Lactobacillus and others. NGS has demonstrated superior capability by providing comprehensive microbiome detection, including the unculturable microorganisms and insights into microbial diversity, so it lacks the limitations that come with traditional culturing. These findings highlight the potential for leveraging beneficial microbes in bioremediation and pathogen control to enhance FSMS effectiveness in seafood-processing environments.
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Official URL or Download Paper: https://www.mdpi.com/2304-8158/14/9/1517
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Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Agriculture Faculty of Engineering |
| DOI Number: | https://doi.org/10.3390/foods14091517 |
| Publisher: | Multidisciplinary Digital Publishing Institute |
| Keywords: | Food safety; Food safety management system (FSMS); Food-contact surfaces; Foodborne; Hazard analysis critical control point (HACCP); MeSTI |
| Depositing User: | Ms. Nur Faseha Mohd Kadim |
| Date Deposited: | 19 Nov 2025 07:19 |
| Last Modified: | 19 Nov 2025 07:19 |
| Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/foods14091517 |
| URI: | http://psasir.upm.edu.my/id/eprint/121846 |
| Statistic Details: | View Download Statistic |
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