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Optimization of the Frying Process for Maximizing Crispiness of Scallop (<i>Patinopecten yessoensis)</i> Adductor Muscle Snacks Using Vacuum Low-Temperature Fryingopen access

Authors
Park, Sun-YoungKang, Sang-InKim, JinAn, Young-HyunLee, Ga-BinPark, Si-HyeongLee, Jung-Suck
Issue Date
Dec-2024
Publisher
MDPI AG
Keywords
scallops; <italic>Patinopecten yessoensis</italic>; vacuum low-temperature frying; crispy snack; optimized; temperature; time
Citation
Foods, v.13, no.24
Indexed
SCIE
SCOPUS
Journal Title
Foods
Volume
13
Number
24
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/75615
DOI
10.3390/foods13244091
ISSN
2304-8158
2304-8158
Abstract
Scallops, an economically important seafood, are popular as fried snacks. Vacuum low-temperature frying creates crispy, healthier foods that meet consumer demand for nutritious snacks with excellent texture. However, research on vacuum frying for shellfish products remains limited. This study aimed to optimize the process for developing a healthy, crispy snack that retains the original shape of the Yesso scallop (Patinopecten yessoensis) adductor muscle using vacuum low-temperature frying technology. The effects of various frying methods on the scallops were analyzed. The vacuum low-temperature frying process was optimized based on evaluations of physical, chemical, and sensory properties. Frying conditions were optimized using response surface methodology, with temperature (X1: 90.1-109.9 degrees C) and time (X2: 186-774 s) as variables. Based on moisture (5.6 +/- 0.1 g/100 g), hardness (1470 +/- 5.0 g/cm2), and sensory chewiness (7.6 +/- 0.2 points) analyses, 99.9 degrees C and 480 s were identified as the optimal conditions. Validation was conducted through sensory evaluation by 30 trained panelists. Scallops produced under these optimal frying conditions exhibited low water activity (aw) (0.46), desirable texture (1428 g/cm2), palatability (7.9 points), and high protein content (45.6 g/100 g). The predicted and experimental values for frying temperature and time showed strong agreement, validating the reliability of the optimization model.
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