Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products
Fermentation is one of the oldest methods to assure the safety and quality of foods, and to prolong their shelf life. However, a successful fermentation relies on the correct kinetics depending on some factors (i.e., ingredients, preservatives, temperature, inoculum of starter cultures). Predictive...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-03-01
|
| Series: | Foods |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2304-8158/11/7/946 |
| _version_ | 1797439351075897344 |
|---|---|
| author | Angela Racioppo Daniela Campaniello Milena Sinigaglia Antonio Bevilacqua Barbara Speranza Maria Rosaria Corbo |
| author_facet | Angela Racioppo Daniela Campaniello Milena Sinigaglia Antonio Bevilacqua Barbara Speranza Maria Rosaria Corbo |
| author_sort | Angela Racioppo |
| collection | DOAJ |
| description | Fermentation is one of the oldest methods to assure the safety and quality of foods, and to prolong their shelf life. However, a successful fermentation relies on the correct kinetics depending on some factors (i.e., ingredients, preservatives, temperature, inoculum of starter cultures). Predictive microbiology is a precious tool in modern food safety and quality management; based on the product characteristics and the conditions occurring in food processing, the inactivation of or increase in microbial populations could be accurately predicted as a function of the relevant intrinsic or extrinsic variables. The main aim of this study was the optimization of the formula of a smoked fermented fish product using predictive modeling tools (tertiary and secondary models) in order to define the role of each factor involved in the formulation and assure a correct course of fermentation. Product optimization was conducted through the software Food Spoilage and Safety Predictor (FSSP), by modeling the growth of lactic acid bacteria (LAB) as a function of some key parameters such as temperature, pH, salt, liquid smoke, carbon dioxide, and nitrites. The variables were combined through a fractional design of experiments (DoE) (3<sup>k-p</sup>), and the outputs of the software, i.e., the maximal growth rate (μ<sub>max</sub>) and the time to attain the critical threshold (t<sub>crit</sub>), were modeled through a multiple regression procedure. The simulation, through FSSP and DoE, showed that liquid smoke is the most critical factor affecting fermentation, followed by temperature and salt. Concerning temperature, fermentation at 20–25 °C is advisable, although a low fermentation temperature is also possible. Other parameters are not significant. |
| first_indexed | 2024-03-09T11:51:35Z |
| format | Article |
| id | doaj.art-7f9f4f8c7a5a4876b035cd689d70bc38 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-09T11:51:35Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-7f9f4f8c7a5a4876b035cd689d70bc382023-11-30T23:14:50ZengMDPI AGFoods2304-81582022-03-0111794610.3390/foods11070946Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish ProductsAngela Racioppo0Daniela Campaniello1Milena Sinigaglia2Antonio Bevilacqua3Barbara Speranza4Maria Rosaria Corbo5Department of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, ItalyDepartment of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, ItalyDepartment of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, ItalyDepartment of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, ItalyDepartment of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, ItalyDepartment of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, 71122 Foggia, ItalyFermentation is one of the oldest methods to assure the safety and quality of foods, and to prolong their shelf life. However, a successful fermentation relies on the correct kinetics depending on some factors (i.e., ingredients, preservatives, temperature, inoculum of starter cultures). Predictive microbiology is a precious tool in modern food safety and quality management; based on the product characteristics and the conditions occurring in food processing, the inactivation of or increase in microbial populations could be accurately predicted as a function of the relevant intrinsic or extrinsic variables. The main aim of this study was the optimization of the formula of a smoked fermented fish product using predictive modeling tools (tertiary and secondary models) in order to define the role of each factor involved in the formulation and assure a correct course of fermentation. Product optimization was conducted through the software Food Spoilage and Safety Predictor (FSSP), by modeling the growth of lactic acid bacteria (LAB) as a function of some key parameters such as temperature, pH, salt, liquid smoke, carbon dioxide, and nitrites. The variables were combined through a fractional design of experiments (DoE) (3<sup>k-p</sup>), and the outputs of the software, i.e., the maximal growth rate (μ<sub>max</sub>) and the time to attain the critical threshold (t<sub>crit</sub>), were modeled through a multiple regression procedure. The simulation, through FSSP and DoE, showed that liquid smoke is the most critical factor affecting fermentation, followed by temperature and salt. Concerning temperature, fermentation at 20–25 °C is advisable, although a low fermentation temperature is also possible. Other parameters are not significant.https://www.mdpi.com/2304-8158/11/7/946predictive microbiologyFSSPDoEsmokefermentationfish |
| spellingShingle | Angela Racioppo Daniela Campaniello Milena Sinigaglia Antonio Bevilacqua Barbara Speranza Maria Rosaria Corbo Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products Foods predictive microbiology FSSP DoE smoke fermentation fish |
| title | Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products |
| title_full | Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products |
| title_fullStr | Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products |
| title_full_unstemmed | Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products |
| title_short | Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products |
| title_sort | use of food spoilage and safety predictor for an a priori modeling of the growth of lactic acid bacteria in fermented smoked fish products |
| topic | predictive microbiology FSSP DoE smoke fermentation fish |
| url | https://www.mdpi.com/2304-8158/11/7/946 |
| work_keys_str_mv | AT angelaracioppo useoffoodspoilageandsafetypredictorforanapriorimodelingofthegrowthoflacticacidbacteriainfermentedsmokedfishproducts AT danielacampaniello useoffoodspoilageandsafetypredictorforanapriorimodelingofthegrowthoflacticacidbacteriainfermentedsmokedfishproducts AT milenasinigaglia useoffoodspoilageandsafetypredictorforanapriorimodelingofthegrowthoflacticacidbacteriainfermentedsmokedfishproducts AT antoniobevilacqua useoffoodspoilageandsafetypredictorforanapriorimodelingofthegrowthoflacticacidbacteriainfermentedsmokedfishproducts AT barbarasperanza useoffoodspoilageandsafetypredictorforanapriorimodelingofthegrowthoflacticacidbacteriainfermentedsmokedfishproducts AT mariarosariacorbo useoffoodspoilageandsafetypredictorforanapriorimodelingofthegrowthoflacticacidbacteriainfermentedsmokedfishproducts |