Characterization and quantification of the taste profiles of black garlic via a novel multi-channel colorimetric sensor array and chemometrics

IF 4 2区 农林科学 Q2 CHEMISTRY, APPLIED
Shanshan Yu , Xingyi Huang , Yuena Wang , Li Wang , Xianhui Chang , Yi Ren , Xiaorui Zhang
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引用次数: 0

Abstract

Taste profiles are crucial for the market success of black garlic, yet investigations into its physicochemical constituents closely related to taste quality remain limited. Additionally, the development of prediction models for taste sensory quality has not been extensively explored. This study aims to develop a cost-effective colorimetric sensor array (CSA) capable of simultaneously and quantitatively predicting the key physicochemical constituents and taste sensory quality of black garlic, integrated with chemometric algorithms. A multi-channel taste visualization sensor array was designed based on pH indicator color changes, indicator displacement assay (IDA), and silver nanoparticles. To establish quantitative prediction models, chemometric algorithms including partial least squares regression (PLSR) and support vector machine regression (SVR) were employed. The results revealed that nonlinear SVR models outperformed linear PLSR models in predicting reducing sugars, amino acid nitrogen, total acid, and the taste sensory attribute, achieving correlation coefficients for prediction (Rp) of 0.9863, 0.9232, 0.9666, and 0.9170, respectively. These findings highlighted the potential of integrating CSA with appropriate chemometric strategies as a reliable and promising approach for monitoring dynamic changes in key physicochemical constituents during black garlic processing and assessing the taste sensory quality of black garlic and similar food matrices.
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来源期刊
Journal of Food Composition and Analysis
Journal of Food Composition and Analysis 工程技术-食品科技
CiteScore
6.20
自引率
11.60%
发文量
601
审稿时长
53 days
期刊介绍: The Journal of Food Composition and Analysis publishes manuscripts on scientific aspects of data on the chemical composition of human foods, with particular emphasis on actual data on composition of foods; analytical methods; studies on the manipulation, storage, distribution and use of food composition data; and studies on the statistics, use and distribution of such data and data systems. The Journal''s basis is nutrient composition, with increasing emphasis on bioactive non-nutrient and anti-nutrient components. Papers must provide sufficient description of the food samples, analytical methods, quality control procedures and statistical treatments of the data to permit the end users of the food composition data to evaluate the appropriateness of such data in their projects. The Journal does not publish papers on: microbiological compounds; sensory quality; aromatics/volatiles in food and wine; essential oils; organoleptic characteristics of food; physical properties; or clinical papers and pharmacology-related papers.
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