ArticleSensors (Basel, Switzerland)2018
THz Spectroscopic Investigation of Wheat-Quality by Using Multi-Source Data Fusion.
Article in Sensors (Basel, Switzerland), 2018. 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, 21 citations in OpenAlex.
- Identification of Defective Maize Seeds Using Hyperspectral Imaging Combined with Deep Learning.Foods (Basel, Switzerland) · 2022Article
- The Application of Terahertz Time-Domain Spectroscopy to Identification of Potato Late Blight and Fusariosis.Pathogens (Basel, Switzerland) · 2021Article
- Non-destructive Detection of Insect Foreign Bodies in Finishing Tea Product Based on Terahertz Spectrum and Image.Frontiers in nutrition · 2021Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
In order to improve the detection accuracy for the quality of wheat, a recognition method for wheat quality using the terahertz (THz) spectrum and multi-source information fusion technology is proposed. Through a combination of the absorption and the refractive index spectra of samples of normal, germinated, moldy, and worm-eaten wheat, support vector machine (SVM) and Dempster-Shafer (DS) evidence theory with different kernel functions were used to establish a classification fusion model for the multiple optical indexes of wheat. The results showed that the recognition rate of the fusion model for wheat samples can be as high as 96%. Furthermore, this approach was compared to the regression model based on single-spectrum analysis. The results indicate that the average recognition rates of fusion models for wheat can reach 90%, and the recognition rate of the SVM radial basis function (SVM-RBF) fusion model can reach 97.5%. The preliminary results indicated that THz-TDS combined with DS evidence theory analysis was suitable for the determination of the wheat quality with better detection accuracy.
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Registered trials
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