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An experimental and numerical evaluation of continuous pasteurization of açai pulp with plate heat exchangers on the inactivation of peroxidase and polyphenol oxidase
This work evaluates the thermal inactivation of peroxidase and polyphenol oxidase of açai-berry pulp in a continuous pasteurization using a lab-scale pasteurizer with plate heat exchangers (PHEs). Experiments were carried-out at three different açai flow rates with two different pass arrangements of...
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Published in: | Journal of food engineering 2022-02, Vol.314, p.110799, Article 110799 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This work evaluates the thermal inactivation of peroxidase and polyphenol oxidase of açai-berry pulp in a continuous pasteurization using a lab-scale pasteurizer with plate heat exchangers (PHEs). Experiments were carried-out at three different açai flow rates with two different pass arrangements of the PHEs. The experimental treatments were simulated by CFD and the numerical results were compared to the experimental data. A better performance of the pasteurizer was noted when the PHEs were set in a series flow arrangement. Heating performance predicted by CFD satisfactorily agreed with the experimental data, especially when the PHEs were set in series flow. Conversely, reasonable deviations between numerical and experimental results of the residual activities of the enzymes occurred, mainly in a series-parallel flow arrangement. Accurately predicting inactivation of thermally-sensitive enzymes is quite difficult in the numerical simulation of complex processes and the reasons why these deviations occurred have been discussed.
•HTST processing of açai pulp was evaluated in relation to POD and PPO inactivation.•Two countercurrent flow arrangements were evaluated in the plate heat exchangers.•Experimental and simulated results of temperature, POD, PPO activity were compared.•CFD showed a large potential in predicting enzyme inactivation in food processing. |
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ISSN: | 0260-8774 1873-5770 |
DOI: | 10.1016/j.jfoodeng.2021.110799 |