Classification of Tea Aromas Using Multi-Nanoparticle Based Chemiresistor Arrays

Tuo Gao; Yongchen Wang; Chengwu Zhang; Zachariah A Pittman; Alexandra M Oliveira; Kan Fu; Jing Zhao; Ranjan Srivastava; Brian G Willis

doi:10.3390/s19112547

Classification of Tea Aromas Using Multi-Nanoparticle Based Chemiresistor Arrays

Sensors (Basel). 2019 Jun 4;19(11):2547. doi: 10.3390/s19112547.

Authors

Tuo Gao¹, Yongchen Wang², Chengwu Zhang³, Zachariah A Pittman⁴, Alexandra M Oliveira⁵, Kan Fu⁶, Jing Zhao^{7

8}, Ranjan Srivastava⁹, Brian G Willis^{10

11

12}

Affiliations

¹ Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. tuo.gao@uconn.edu.
² Department of Chemistry, University of Connecticut, Storrs, CT 06269, USA. yongchen.wang@uconn.edu.
³ Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. chengwu.zhang@uconn.edu.
⁴ Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. zachariah.pittman@uconn.edu.
⁵ Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. alexandra.oliveira@uconn.edu.
⁶ Department of Materials Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. kan.fu@uconn.edu.
⁷ Department of Chemistry, University of Connecticut, Storrs, CT 06269, USA. jing.zhao@uconn.edu.
⁸ Institute of Materials Science, University of Connecticut, Storrs, CT 06269, USA. jing.zhao@uconn.edu.
⁹ Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. ranjan.srivastava@uconn.edu.
¹⁰ Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. brian.willis@uconn.edu.
¹¹ Department of Materials Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. brian.willis@uconn.edu.
¹² Institute of Materials Science, University of Connecticut, Storrs, CT 06269, USA. brian.willis@uconn.edu.

Abstract

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.

Keywords: chemiresistor array; gold nanoparticles (AuNPs); linear discriminant analysis (LDA); pattern recognition; tea aroma sensing.

Grants and funding

N00014-16-1-2279/Office of Naval Research