ArticleSensors (Basel, Switzerland)2017
Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 48 citations in OpenAlex.
- Classification of different gluten wheat varieties based on hyperspectral preprocessing, feature screening, and machine learning.Food chemistry: X · 2025Article
- Can Electronic Nose Replace Human Nose?-An Investigation of E-Nose Sensor Responses to Volatile Compounds in Alcoholic Beverages.ACS omega · 2023Article
- A Machine Learning Method for the Quality Detection of Base Liquor and Commercial Liquor Using Multidimensional Signals from an Electronic Nose.Foods (Basel, Switzerland) · 2023Article
- Qualitative and Quantitative Detection of Food Adulteration Using a Smart E-Nose.Sensors (Basel, Switzerland) · 2022Article
- A Study on Consumers' Visual Image Evaluation of Wrist Wearables.Entropy (Basel, Switzerland) · 2021Article
- Establishment of Landslide Groundwater Level Prediction Model Based on GA-SVM and Influencing Factor Analysis.Sensors (Basel, Switzerland) · 2020Article
- Bulk and Surface Acoustic Wave Sensor Arrays for Multi-Analyte Detection: A Review.Sensors (Basel, Switzerland) · 2019Review
- Bionic Electronic Nose Based on MOS Sensors Array and Machine Learning Algorithms Used for Wine Properties Detection.Sensors (Basel, Switzerland) · 2018Article
- Support Vector Machine Optimized by Genetic Algorithm for Data Analysis of Near-Infrared Spectroscopy Sensors.Sensors (Basel, Switzerland) · 2018Article
- Development of Organic-Inorganic Hybrid Optical Gas Sensors for the Non-Invasive Monitoring of Pathogenic Bacteria.Sensors (Basel, Switzerland) · 2018Article
- Identification of Tequila with an Array of ZnO Thin Films: A Simple and Cost-Effective Method.Sensors (Basel, Switzerland) · 2017Article
- Selectivity Enhancement in Electronic Nose Based on an Optimized DQN.Sensors (Basel, Switzerland) · 2017Article
- Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose.Sensors (Basel, Switzerland) · 2017Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This paper presents a pattern recognition system for classifying ten brands of Chinese liquors based on multidimensional scaling (MDS) and support vector machine (SVM) algorithms in a quartz crystal microbalance (QCM)-based electronic nose (e-nose) we designed. We evaluated the comprehensive performance of the MDS-SVM classifier that predicted all ten brands of Chinese liquors individually. The prediction accuracy (98.3%) showed superior performance of the MDS-SVM classifier over the back-propagation artificial neural network (BP-ANN) classifier (93.3%) and moving average-linear discriminant analysis (MA-LDA) classifier (87.6%). The MDS-SVM classifier has reasonable reliability, good fitting and prediction (generalization) performance in classification of the Chinese liquors. Taking both application of the e-nose and validation of the MDS-SVM classifier into account, we have thus created a useful method for the classification of multiple Chinese liquors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.