Leaf-Face <i>Dendrobium</i> Classifier Based on an Integrated Electrochemical Tongue and Machine Learning

Botanical sourcing seriously impacts the safety and potency of herbal medicines, restricting the development of the traditional Chinese medicinal industry. Rapid and convenient identification of plant resources is important to address this problem. Herein, we innovated a portable, intelligent, and integrated platform, termed the Smart Electronic Tongue (SET), for right recognizing <i>Dendrobium</i> bonsai of different subspecies and origins. The device is miniaturized with a hollow microneedle array for leaf-face extraction, a press-pumping pipeline for on-demand sample sap suction, plus a five-electrode chip for electrochemical readout. Differential pulse voltammograms on three simplexes of self-assembled monolayers as well as their multiplexed configurations are specialized to generate high-dimensional fingerprinting of <i>Dendrobium</i> subtypes. Taking advantage of machine learning algorithms, the platform achieves automatic authentication over eight varieties with a discriminatory accuracy of 95%. Given this, we anticipate that such a bionic sensing setup would offer a versatile solution toward the classification of diverse officinals at the point of need.

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Publication Details

Journal
ACS Sensors
Published
2025-02-04
DOI
https://doi.org/10.1021/acssensors.4c02887
Citations
5
Primary Topic
Biological and pharmacological studies of plants
Type
article
Field-Weighted Citation Impact
6.97
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article

Leaf-Face Dendrobium Classifier Based on an Integrated Electrochemical Tongue and Machine Learning

Yaqi Huang, Yuhao Piao, Shengyuan Deng, Kelan Yan et al.
5 citations
ACS Sensors
Biological and pharmacological studies of plants
6.97
article

Leaf-Face Dendrobium Classifier Based on an Integrated Electrochemical Tongue and Machine Learning

Yaqi Huang, Yuhao Piao, Shengyuan Deng, Kelan Yan, Fulin Zhu, Tiantian Man, Ying Wan, Yueyu Wang, Jie Chen, Yan Su, Yuxiao He
article en
5 citations

Abstract

Botanical sourcing seriously impacts the safety and potency of herbal medicines, restricting the development of the traditional Chinese medicinal industry. Rapid and convenient identification of plant resources is important to address this problem. Herein, we innovated a portable, intelligent, and integrated platform, termed the Smart Electronic Tongue (SET), for right recognizing <i>Dendrobium</i> bonsai of different subspecies and origins. The device is miniaturized with a hollow microneedle array for leaf-face extraction, a press-pumping pipeline for on-demand sample sap suction, plus a five-electrode chip for electrochemical readout. Differential pulse voltammograms on three simplexes of self-assembled monolayers as well as their multiplexed configurations are specialized to generate high-dimensional fingerprinting of <i>Dendrobium</i> subtypes. Taking advantage of machine learning algorithms, the platform achieves automatic authentication over eight varieties with a discriminatory accuracy of 95%. Given this, we anticipate that such a bionic sensing setup would offer a versatile solution toward the classification of diverse officinals at the point of need.

ACS SensorsVol. 10(2)
Nanjing University of Science and Technology (CN), Ministry of Industry and Information Technology (CN)
Quality Education
Openalex Percentile: Top 3%
Biological and pharmacological studies of plants
6.97
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Leaf-Face <i>Dendrobium</i> Classifier Based on an Integrated Electrochemical Tongue and Machine Learning — Yaqi Huang, Yuhao Piao, et al. · ACS Sensors (2025) | TGRS Research Map | TGRS