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Open AccessArticle

Classification of Tea Aromas Using Multi-Nanoparticle Based Chemiresistor Arrays

1
Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA
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Department of Chemistry, University of Connecticut, Storrs, CT 06269, USA
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Department of Materials Science and Engineering, University of Connecticut, Storrs, CT 06269, USA
4
Institute of Materials Science, University of Connecticut, Storrs, CT 06269, USA
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(11), 2547; https://doi.org/10.3390/s19112547
Received: 24 April 2019 / Revised: 29 May 2019 / Accepted: 30 May 2019 / Published: 4 June 2019
(This article belongs to the Special Issue Nanoparticles-Based Gas Sensors)
Nanoparticle based chemical sensor arrays with four types of organo-functionalized gold nanoparticles (AuNPs) were introduced to classify 35 different teas, including black teas, green teas, and herbal teas. Integrated sensor arrays were made using microfabrication methods including photolithography and lift-off processing. Different types of nanoparticle solutions were drop-cast on separate active regions of each sensor chip. Sensor responses, expressed as the ratio of resistance change to baseline resistance (ΔR/R0), were used as input data to discriminate different aromas by statistical analysis using multivariate techniques and machine learning algorithms. With five-fold cross validation, linear discriminant analysis (LDA) gave 99% accuracy for classification of all 35 teas, and 98% and 100% accuracy for separate datasets of herbal teas, and black and green teas, respectively. We find that classification accuracy improves significantly by using multiple types of nanoparticles compared to single type nanoparticle arrays. The results suggest a promising approach to monitor the freshness and quality of tea products. View Full-Text
Keywords: tea aroma sensing; gold nanoparticles (AuNPs); chemiresistor array; linear discriminant analysis (LDA); pattern recognition tea aroma sensing; gold nanoparticles (AuNPs); chemiresistor array; linear discriminant analysis (LDA); pattern recognition
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Gao, T.; Wang, Y.; Zhang, C.; Pittman, Z.A.; Oliveira, A.M.; Fu, K.; Zhao, J.; Srivastava, R.; Willis, B.G. Classification of Tea Aromas Using Multi-Nanoparticle Based Chemiresistor Arrays. Sensors 2019, 19, 2547.

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