Modeling the Time to Fail of Peach Nectars Formulated by Hurdle Technology

Publication date: 2016 Source:Procedia Food Science, Volume 7 Author(s): M.E. González-Miguel, N. Ramírez-Corona, E. Palou, A. López-Malo The use of regression with life-data is helpful to observe whether one or more factors affect the failure time (spoilage) of a product, obtaining a model that predicts the time to fail (TTF). TTF models link kinetic (lag time) and probabilistic (growth /no-growth prediction) models for selected formulation/storage conditions. Our objective was to assess the individual and combined effects of pH, aw, and the incorporation of potassium sorbate (KS) or sodium benzoate (BNa) at selected concentrations on the microbial stability of peach nectar during storage at 25°C, in order to model and predict TTF. Peach nectars were formulated with 40% fruit pulp and the necessary sucrose syrup and citric acid to attain aw 0.96, 0.97, or 0.98 and pH 3.0, 3.5, or 4.0; while 0, 500, or 1000ppm of KS or BNa were added. Nectars were stored for 180 days in glass jars at 25°C, and periodically analyzed (standard plate as well as yeast and mould counts). The experimental design and analyses were replicated three times. Storage times that revealed microbial populations higher than 104 CFU/mL and signs of spoilage were registered to model TTF by survival analysis. From the 54 combinations tested, 9 formulations (without antimicrobials) exhibited early spoilage (<5 days). For the combinations formulated with 500ppm of BNa, spoilage was detected afte...
Source: Procedia Food Science - Category: Food Science Source Type: research