Development of Microbiological Prediction Models for Hamburger Patties prepared with Mealworm (Tenebrio molitor) Powder as Meat Partial Substitute
Year: 2024
Type: article
Abstract: This study aims to develop and evaluate two predictive microbial growth models for hamburger patties prepared with different levels of Tenebrio molitor powder (0%, 4%, and 8%). The number of total aerobic bacteria and Escherichia coli was measured during 20 days of refrigerated storage at 4±1°C. The Baranyi and modified Gompertz models were applied to the observed data on total aerobic bacteria to develop, compare, and validate microbial growth predictions. The number of total aerobic bacteria was not changed during 3 storage days (p<0.05), while it was increased after 7 storage days (p<0.05). However, E. coli was not detected in the all hamburger patties during all storage days. In the patties prepared without T. molitor powder, the Baranyi model’s Bf and Af are close to 1 which means the model performed well. The Baranyi model showed a better statistical fit than the modified Gompertz model in the patties prepared with 8% T. molitor powder. However, when the patties were prepared with 4% T. molitor powder, the modified Gompertz model performed well in all statistical analyses. These results indicate that the Baranyi model is more suitable for hamburger patties without T. molitor powder, as well as those prepared with 4% T. molitor powder. However, using the modified Gompertz model for hamburger patties prepared with 8% T. molitor powder is more appropriate. Future studies should investigate the reasons for this variation by developing secondary models with a wider range of T. molitor powder levels in hamburger patties.
Source: Resources Science Research
Authors: Hyun Uk Cho, Chemin Nam, Seohyeon Jeon, Yejin Kim, Heeyoung Lee, Hae In Yong
Institutions: Chungnam National University, Korea Food Research Institute
Language: English
Subfield: Animal Science and Zoology
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W4407071815