http://scholars.ntou.edu.tw/handle/123456789/22072
Title: | Predictive models for the growth of Salmonella spp., Listeria spp., and Escherichia coli in lettuce harvested on Taiwanese farms | Authors: | Ndraha, Nodali Goh, Ai Ping Gia Dieu Tran Chen, Cheng-quan Hsiao, Hsin-, I |
Keywords: | predictive model;food safety;vegetable;foodborne pathogen;lettuce | Issue Date: | 4-Jul-2022 | Publisher: | WILEY | Source: | JOURNAL OF FOOD SCIENCE | Abstract: | This study aimed at developing predictive models for Salmonella, Listeria, and E. coli in lettuce iceberg (Lactuca sativa) locally grown in Taiwan. The models were developed under constant temperature levels (5, 10, 15, 20, and 25 degrees C) and validated under dynamic temperature conditions (18 degrees C for 4 h, 7 degrees C for 48 h, 23 degrees C for 4 h). The result showed that (1) all strains were unable to grow at 5 degrees C except for standard strain of Listeria obtained from the BCRC and (2) the growth rate of locally isolated strains of Salmonella and Listeria was higher than the standard one at certain temperature levels and lower than the growth rates of E. coli. The findings in this study enhance our understanding about the growth variability between Salmonella, Listeria, and E. coli strains on vegetables locally grown in Taiwan and may be used to improve the management of proper storage temperature in the lettuce supply chain in this country. Considering the temperature recommendation for refrigerated food in Taiwan, the findings in this study therefore recommend that fresh vegetables (e.g., lettuce) should be stored at 5 degrees C or lower to prevent the rapid growth of these microorganisms. Finally, the developed models can be used in the assessment of the microbiological risk of Salmonella, Listeria, and E. coli contamination in lettuce locally grown in Taiwan. Practical Application This study developed predictive models describing the growth of Salmonella, Listeria, and E. coli in lettuce locally grown in Taiwan. The models developed in this study can be used in quantitative microbial risk assessment. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/22072 | ISSN: | 0022-1147 | DOI: | 10.1111/1750-3841.16236 |
Appears in Collections: | 食品科學系 |
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