Olfactory analysis of oolong tea sensory quality using composite nano-colorimetric sensor array

• Published in: Food research international Vol. 194; p. 114912
• Main Authors: Lin, Hao, Zhang, Kexin, Guo, Jilong, Kwadzokpui, Bridget Ama, Adade, Selorm Yao-Say Solomon, Chen, Quansheng
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2024
• Subjects: Binding mechanism; Colorimetric sensor array; Multivariate data analysis; Oolong tea; Sensory quality; Sensory quality; Oolong tea; Colorimetric sensor array; Binding mechanism; Multivariate data analysis
• ISSN: 0963-9969; 1873-7145; 1873-7145
• DOI: 10.1016/j.foodres.2024.114912

[Display omitted] •A novel Colorimetric sensor array (CSA) for assessing oolong tea sensory quality.•Binding mechanism between pH indicators and metalloporphyrin was developed.•The effectiveness of CSA was assessed by comparing four classification models.•Oolong tea was successfully classified based on flavor intensity and grade level. Chinese oolong tea is famous for its rich and diverse aromas, which is an important indicator for sensor quality evaluation. To accurately and rapidly evaluate sensory quality, a novel colorimetric sensor array (CSA) was developed to detect volatile organic compounds (VOCs) in oolong tea. We further explored the binding mechanism between colorimetric dyes that trigger changes in charge transfer and visible color changes. Based on this, we modified and optimized the CSA to improve the sensitivity by 17.1–234.9% and the stability by 8.7–33.3%. The study also assessed the effectiveness of this method by comparing two linear and two non-linear classification models, with the support vector machine (SVM) model achieving the highest accuracy, identifying different flavor intensity and grades with rates of 100% and 95.83%, respectively. These findings sufficiently demonstrated that the novel CSA, integrated with the SVM model, has promising potential for predicting the sensory quality of oolong tea.