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基于分子感官和可解释机器学习技术的卵形鲳鲹(美味鱼)发酵过程中挥发性化合物变化的研究:不同发酵阶段的比较。

Investigation of fermentation-induced changes in the volatile compounds of Trachinotus ovatus (meixiangyu) based on molecular sensory and interpretable machine-learning techniques: Comparison of different fermentation stages.

机构信息

Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs of The People's Republic of China, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China; College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China.

Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs of The People's Republic of China, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China; Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China; Sanya Tropical Fisheries Research Institute, Sanya 572018, China.

出版信息

Food Res Int. 2021 Dec;150(Pt A):110739. doi: 10.1016/j.foodres.2021.110739. Epub 2021 Oct 11.

DOI:10.1016/j.foodres.2021.110739
PMID:34865758
Abstract

Fermented golden pomfret (Trachinotus ovatus) is appreciated by local consumers owing to its distinct flavor. Electronic nose (E-nose) and gas chromatography-ion mobility spectrometry (GC-IMS) technologies were used to analyze the changes in volatile compounds responsible for evolution of the golden pomfret odor profile during fermentation. Forty-five ion peaks were detected using GC-IMS. Although aldehydes represented the major initial volatile compound group, their levels decreased as fermentation proceeded. Between 3 and 15 days, increased levels of esters contributed to a stable volatile organic compounds profile. After 18 days, high levels of indole and pyrazines were detected. Eleven key volatile compounds were screened based on partial least squares discriminant analysis (PLS-DA). Back propagation artificial neural network (BP-ANN) predicted the fermentation stage enabling the development of better strategies to regulate golden pomfret fermentation. This study provided a theoretical basis for real-time monitoring and quality control of Chinese fermented golden pomfet.

摘要

发酵金鲳鱼(Trachinotus ovatus)因其独特的风味而受到当地消费者的喜爱。本研究采用电子鼻(E-nose)和气相色谱-离子迁移谱(GC-IMS)技术分析了在发酵过程中金鲳鱼气味特征演变过程中负责产生挥发性化合物的变化。GC-IMS 检测到 45 个离子峰。虽然醛类最初是主要的挥发性化合物,但随着发酵的进行,其含量逐渐降低。在 3 至 15 天之间,酯类的增加水平导致稳定的挥发性有机化合物图谱。18 天后,检测到吲哚和吡嗪的高含量。基于偏最小二乘判别分析(PLS-DA)筛选出 11 种关键挥发性化合物。反向传播人工神经网络(BP-ANN)预测了发酵阶段,从而制定出更好的金鲳鱼发酵调控策略。该研究为中国发酵金鲳鱼的实时监测和质量控制提供了理论依据。

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