Abstract

Abstract The inactivation of pectin methylesterase (PME) in pineapple puree was studied within the domain of 0.1–600 MPa/30–70 °C/1 s–40 min. The combined effect of pressure-build up and decompression, as characterized by pulse inactivation (PI value), was modeled by the artificial neural network (ANN) through a tan-sigmoidal function of target pressure, target temperature, compression, and decompression time. Besides, nth order kinetic model was fitted during the isobaric-isothermal hold period. The extent of pulse inactivation of PME ranged from 15% (200 MPa/30 °C) to 67% (600 MPa/70 °C) and it increased at a higher temperature and/or pressure. The inactivation orders (n) during thermal (0.1 MPa/30–70 °C) and high pressure (100–600 MPa/30–70 °C) treatments were 1.15 and 1.3, respectively. The rate constant (k) ranged within 4.0 to 71.2 × 10−3 Un−1·min−1. A nonlinear model considering the pressure dependency of activation energy, and temperature dependency of activation volume was developed which adequately described the inactivation behavior of PME within the domain. Industrial relevance Pectin methylesterase (PME) in the pineapple puree results in a product with a modified texture and consistency that is usually not entertained by the consumer. Therefore, pineapple puree has to be processed to inactivate PME to avoid the cloud loss. Now-a-days, high-pressure processing is being used for fruit products to retain the heat sensitive nutrients. In this sense, a model capable of predicting the exact inactivation behavior of PME during the treatment is very much obligatory for process design. This combined model developed in the study will help the food industry to come-up with the exact pressure-temperature-holding time combination achieving a certain degree of PME inactivation.

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