Modeling the growth/no growth interface of Alicyclobacillus acidoterrestris CRA 7152 in orange juice as a function of pH, temperature, Brix and nisin concentration

• Autores: Peña, Wilmer, Rodríguez, Pilar
• Formato: artículo
• Fecha de Publicación: 2010
• Institución: Universidad Nacional de Trujillo
• Repositorio: Revistas - Universidad Nacional de Trujillo
• Lenguaje: inglés
• OAI Identifier: oai:ojs.revistas.unitru.edu.pe:article/16
• Enlace del recurso: https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/16
• Nivel de acceso: acceso abierto
• Materia: predictive modeling; Alicyclobacillus acidoterrestris; orange juice; nisin; Modelamiento predictivo; jugo de naranja; nisina

The growth probability of Alicyclobacillus acidoterrestris CRA 7152 in orange juice was studied in different product conditions. The microorganism response was monitored until 47 days of storage in different conditions of pH (3 to 5.8), soluble solids (11 to 19°Brix), temperature (20 to 54°C) and nisin concentration (0 to 70 IU/ml). Growth/no growth data were modeled by the polynomial logistics regression model. The concordance of the obtained model was 96.3% indicating good fitting of observed data. The results showed fast growth in the conditions 0 IU nisin/ml juice, pH 4.4 and 15oBrix, at 35oC. For 70 IU nisin/ml there was no growth, pH 4.4, at 37oC, up to 47 days of storage. Simple juices (11°Brix) with pHs between 3.5 to 3.7 can keep stable and withstand abuse temperatures up to 36°C, since added in 70IU nisin/ml, extending its shelf life. With 0.05 growth probability and using the logistics model, high pH critical values can be obtained when 50 IU nisin/ml, at 25oC, are present in the juice, however increases in temperature and decreases in soluble solids concentration make the pH critical values decrease. It is then concluded that nisin incorporation is an alternative for controlling A. acidoterrestris growth in orange juice, as well as the logistics regression model proved to be an important tool for determining the microbial response under critical values of the variables,besides predicting growth probabilities for the different studied conditions.