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A mathematical model that predicts the decimal reduction time (D72C) of Salmonella Typhimurium (ATTC 13311) as a function of citrus model system (CMS) pH (2.56–4.74), titratable acidity (TA) (0.01–2.76% citric acid) and soluble solids (SS) (4.75–16.85°Brix) was established. The D72C values of the reference strain in different CMS were fitted into a second order model. Regression analysis of variance and goodness-of-fit assessments showed that the model was highly significant (P < 0.0001). The linear influences of pH and SS and quadratic influences of all physicochemical properties on D72C were significant (P < 0.05). The smallest positive D72C resulted in pH, TA and SS levels of 3.00, 2.20% citric acid and 16.85°Brix, respectively. Direct and inverse relationships were established between D72C values and pH and D72C values and at >0.65% citric acid TA, respectively. Survival rates were optimum at the SS value of 11.50°Brix when pH is 3.00 and TA is 2.20% citric acid. PRACTICAL APPLICATIONS

Despite being one of the more effective and cheaper means of food preservation, thermal processing has a limitation of being dependent on intrinsic food properties. Therefore, even similar food products, like fruit juices, but with differing physicochemical properties should be subjected to unique process schedules. As the establishment of specific processes for separate food products can be painstakingly difficult, processors often apply generic thermal processes that result in under- or overprocessing and negatively affect food safety and quality. Therefore, this study tried to address this gap by developing a predictive model that can estimate the 72C decimal reduction time (D72C) of Salmonella Typhimurium (ATCC 13311) from the pH, soluble solid (°Brix) and titrable acidity (% citric acid) of citrus juices. Utilization of the model to establish unique thermal processes for specific citrus juices against the pertinent target pathogen is a convenient alternative to the more traditional but rigorous process.
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Document Type: Research Article

Affiliations: 1: School of StatisticsUniversity of the PhilippinesDiliman, Quezon City, Philippines 2: Department of Food Science and NutritionCollege of Home Economics

Publication date: 2008-10-01

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