ArticleSensors (Basel, Switzerland)2022
Freshness Identification of Oysters Based on Colorimetric Sensor Array Combined with Image Processing and Visible Near-Infrared Spectroscopy.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 21 citations in OpenAlex.
- Integration of Colorimetric Sensing Dyes and Multi-Substrate Arrays for Food Quality and Safety Monitoring: Design, Optimization, and Analysis.Comprehensive reviews in food science and food safety · 2026Review
- Investigating potential freshness indicators for packaged oysters through multivariate statistical analysis.Food science and biotechnology · 2025Article
- Intelligent Evaluation and Dynamic Prediction of Oyster Freshness with Electronic Nose Based on the Distribution of Volatile Compounds Using GC-MS Analysis.Foods (Basel, Switzerland) · 2024Article
- The Research Field of Meat Preservation: A Scientometric and Visualization Analysis Based on the Web of Science.Foods (Basel, Switzerland) · 2023Review
- rGO-PDMS Flexible Sensors Enabled Survival Decision System for Live Oysters.Sensors (Basel, Switzerland) · 2023Article
- Preparation of Mesoporous Silica Nanosphere-Doped Color-Sensitive Materials and Application in Monitoring the TVB-N of Oysters.Foods (Basel, Switzerland) · 2022Article
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5 authors at 2 institutions in 1 country.
Funding
Abstract
Volatile organic compounds (VOCs) could be used as an indicator of the freshness of oysters. However, traditional characterization methods for VOCs have some disadvantages, such as having a high instrument cost, cumbersome pretreatment, and being time consuming. In this work, a fast and non-destructive method based on colorimetric sensor array (CSA) and visible near-infrared spectroscopy (VNIRS) was established to identify the freshness of oysters. Firstly, four color-sensitive dyes, which were sensitive to VOCs of oysters, were selected, and they were printed on a silica gel plate to obtain a CSA. Secondly, a charge coupled device (CCD) camera was used to obtain the "before" and "after" image of CSA. Thirdly, VNIS system obtained the reflected spectrum data of the CSA, which can not only obtain the color change information before and after the reaction of the CSA with the VOCs of oysters, but also reflect the changes in the internal structure of color-sensitive materials after the reaction of oysters' VOCs. The pattern recognition results of VNIS data showed that the fresh oysters and stale oysters could be separated directly from the principal component analysis (PCA) score plot, and linear discriminant analysis (LDA) model based on variables selection methods could obtain a good performance for the freshness detection of oysters, and the recognition rate of the calibration set was 100%, while the recognition rate of the prediction set was 97.22%. The result demonstrated that the CSA, combined with VNIRS, showed great potential for VOCS measurement, and this research result provided a fast and nondestructive identification method for the freshness identification of oysters.
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