Insights on the astringency of non alcoholic beverages: fruit, vegetable & plantation based perspective

SHANKER, M. Anjaly, KRISHNAN, Reshma, KUMAR, Gopika S., MOHAMMED, Thasniya, HYMAVATHI, Arunima Suresh, ROSAMMA, RAGESH, Nivedya, GEORGE, Sony, RANA, Sandeep Singh and ABDULLAH, S. (2024). Insights on the astringency of non alcoholic beverages: fruit, vegetable & plantation based perspective. Food Chemistry Advances, 4: 100630. [Article]

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Abstract
Sensory parameters of food and beverages secured much importance with mounting changes in diet preferences. The taste and flavour of these food groups are largely affected by astringency which in turn influence the sensory experience. Derived from Latin, astringency deals with the sensation of extreme dryness, roughness or puckering involving the secretions of salivary glands. Accountable astringent clusters majorly revolving around the presence of tannins in food trailed by the incidence of salts of multivalent cations like Al, Zn, Cr etc, and dehydrating agents like mineral acids, alcohol etc. To augment the sensory feeling and to broaden the marketing possibilities related to beverages, it is important to accomplish techniques to reduce or control the development of these sensations. De-astringency practices performed in foods can be broadly catalogued into thermal and non-thermal treatments. While the former majorly included hot water, steam and microwave treatment, the latter concentrated mainly on innovative techniques like high hydrostatic pressure, pulsed electric field, thermo-sonication, ultrasonication etc. The effectiveness of these procedures is largely dependent on the mechanisms associated with the development of astringency feelings in foods. Understanding the mechanism underlying astringency sensation is still in a nascent stage and needs more exploration to state the explicit reason behind the process. This review chiefly covers the explanation of astringency, the mechanism involved and the different de-astringency techniques as per the prevailing astringency models.
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