ArticleScientific reports2019
Quality evaluation based on color grading: quality discrimination of the Chinese medicine Corni Fructus by an E-eye.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Artificial intelligence and synthetic biology in traditional Chinese medicine: revolutionizing public health applications.Frontiers in plant science · 2026Review
- Applications of Electronic Nose, Electronic Eye and Electronic Tongue in Quality, Safety and Shelf Life of Meat and Meat Products: A Review.Sensors (Basel, Switzerland) · 2023Review
- Exploration on Varying Patterns of Morphological Features and Quality of Armeniacae Semen Amarum in Rancid Process Based on Colorimeter, Electronic Nose, and GC/MS Coupled With Human Panel.Frontiers in pharmacology · 2022Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
'Quality evaluation based on color grading' is one of the features used in Chinese medicine discrimination. In order to assess the feasibility of electronic eye (E-eye) in implementing 'quality evaluation based on color grading', the present study applied an IRIS VA400 E-eye to test 58 batches of Corni Fructus samples. Their optical data were acquired and combined with their corresponding classes. A total of four quality discrimination models were produced according to discrimination analysis (DA), least squares support vector machine (LS-SVM), partial least squares-discrimination analysis (PLS-DA), and principal component analysis-discrimination analysis (PCA-DA). The accuracy rate of the aforementioned 4 cross evaluation models were 86.21%, 89.66%, 81.03% and 91.38%, respectively. Therefore, the PCA-DA method was used to build the final discrimination model for classifying Corni Fructus or discriminating its quality.
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