UV‐C Inactivation of Target Bacteria and Fungi Screened via Selenium‐Sand Melon Surface Metagenomics With Modeling of Fungal Inactivation Kinetics

ABSTRACT Selenium‐sand melon (SSM), a unique melon variety rich in selenium, is an economically and nutritionally significant crop, which is very suitable for processing into juice, but microbial inactivation is the biggest challenge in its processing. In order to address this problem, in this study, an innovative combination of metagenomic analysis, inactivation assay, and kinetic modeling techniques was used to first screen 7 bacterial and 5 fungal strains as target strains from the results of macro genomic analysis of SSM and soil samples. Then, after inoculating these microorganisms into SSJ respectively, we applied the liquid food UV‐C sterilization equipment over a wide irradiation dose range of 28–168 J/mL to comprehensively cover the inactivation study of bacteria and fungi, and focused on constructing an inactivation model of fungi in selenium sapodilla juice. The results showed that UV‐C exhibited significant bactericidal effects, and bacteria population decreased by approximately 7 log 10 at 56 J/mL, while fungal loads were reduced by nearly 5 log 10 at 168 J/mL. Fungal inactivation kinetics were modeled using multiple mathematical approaches. Among them, SWeibull2 model provided the best fit ( R 2 ≥ 0.999, lowest RMSE, AIC, and BIC values, and smallest D ‐value), outperforming the Allometric1 model and Linear models. Notably, resistance to UV‐C varied across fungal species, with Mortierella circinelloides demonstrating stronger resistance. This study highlights UV‐C as a viable nonthermal alternative for SSJ processing, validating SWeibull2 as reliable for predicting fungal inactivation kinetics under UV‐C.

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Publication Details

Journal
Food Frontiers
Published
2025-10-24
DOI
https://doi.org/10.1002/fft2.70162
Primary Topic
Listeria monocytogenes in Food Safety
Type
article
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article

UV‐C Inactivation of Target Bacteria and Fungi Screened via Selenium‐Sand Melon Surface Metagenomics With Modeling of Fungal Inactivation Kinetics

Zhao‐Jun Wei, Jian‐Guo Zhang, Run‐Hui Ma, Kiran Thakur et al.
Food Frontiers
Listeria monocytogenes in Food Safety
article

UV‐C Inactivation of Target Bacteria and Fungi Screened via Selenium‐Sand Melon Surface Metagenomics With Modeling of Fungal Inactivation Kinetics

Zhao‐Jun Wei, Jian‐Guo Zhang, Run‐Hui Ma, Kiran Thakur, Zhi‐Jing Ni, Lili Li, Yang Liu, Jun Chen, M. Z. Fan, Song‐Po Shen
article en

Abstract

ABSTRACT Selenium‐sand melon (SSM), a unique melon variety rich in selenium, is an economically and nutritionally significant crop, which is very suitable for processing into juice, but microbial inactivation is the biggest challenge in its processing. In order to address this problem, in this study, an innovative combination of metagenomic analysis, inactivation assay, and kinetic modeling techniques was used to first screen 7 bacterial and 5 fungal strains as target strains from the results of macro genomic analysis of SSM and soil samples. Then, after inoculating these microorganisms into SSJ respectively, we applied the liquid food UV‐C sterilization equipment over a wide irradiation dose range of 28–168 J/mL to comprehensively cover the inactivation study of bacteria and fungi, and focused on constructing an inactivation model of fungi in selenium sapodilla juice. The results showed that UV‐C exhibited significant bactericidal effects, and bacteria population decreased by approximately 7 log 10 at 56 J/mL, while fungal loads were reduced by nearly 5 log 10 at 168 J/mL. Fungal inactivation kinetics were modeled using multiple mathematical approaches. Among them, SWeibull2 model provided the best fit ( R 2 ≥ 0.999, lowest RMSE, AIC, and BIC values, and smallest D ‐value), outperforming the Allometric1 model and Linear models. Notably, resistance to UV‐C varied across fungal species, with Mortierella circinelloides demonstrating stronger resistance. This study highlights UV‐C as a viable nonthermal alternative for SSJ processing, validating SWeibull2 as reliable for predicting fungal inactivation kinetics under UV‐C.

Food FrontiersVol. 7(1)
Nanchang University (CN), Hefei University of Technology (CN), North Minzu University (CN), State Key Laboratory of Food Science and Technology (CN)
Openalex Percentile: Top 67%
Listeria monocytogenes in Food Safety
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