Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize Kernels
Aflatoxin B<sub>1</sub> (AFB<sub>1</sub>) is a very strong carcinogen, maize kernels are easily infected by this toxin during storage. Rapid and accurate identification of AFB<sub>1</sub> is of great significance to ensure food safety. In this study, a novel metho...
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MDPI AG
2022-03-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/12/3/385 |
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| author | Quan Zhou Wenqian Huang Xi Tian |
| author_facet | Quan Zhou Wenqian Huang Xi Tian |
| author_sort | Quan Zhou |
| collection | DOAJ |
| description | Aflatoxin B<sub>1</sub> (AFB<sub>1</sub>) is a very strong carcinogen, maize kernels are easily infected by this toxin during storage. Rapid and accurate identification of AFB<sub>1</sub> is of great significance to ensure food safety. In this study, a novel method for classification of AFB<sub>1</sub> in single maize kernels was developed. Four groups of maize kernel samples with different AFB<sub>1</sub> concentrations (10, 20, 50, and 100 ppb) were prepared by artificial inoculation of toxin. In addition, one group of maize kernel samples without AFB<sub>1</sub> were prepared as control, each group with 70 samples. The visible and short wave near-infrared (Vis-SWNIR) region (500–1000 nm) and long wave near-infrared (LWNIR) region (1000–2000 nm) hyperspectral images of all samples were obtained respectively, and the hyperspectral images in 500–2000 nm range was obtained after spectral pretreatment and fusion. Kennard-Stone algorithm was used to divide the samples into calibration set or prediction set. Competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to roughly select the characteristic wavelengths of the calibration set samples, and 25 and 26 effective wavelengths were obtained respectively. Based on the roughly selected wavelengths, a method of fine selection of the characteristic wavelengths was proposed by using the gray-value difference of image (GDI), and a few number of characteristic wavelengths were further selected. Under the LDA classification model, 10 characteristic wavelengths were selected to test the prediction set and the independent verification samples, and the ideal result were obtained with an accuracy of 94.46% and 91.11%, respectively. This study provides a new approach for AFB<sub>1</sub> concentration classification of single maize kernels. |
| first_indexed | 2024-03-09T13:55:29Z |
| format | Article |
| id | doaj.art-df1a04e3c7c24489b95245b97d127d11 |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-09T13:55:29Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-df1a04e3c7c24489b95245b97d127d112023-11-30T20:43:48ZengMDPI AGAgriculture2077-04722022-03-0112338510.3390/agriculture12030385Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize KernelsQuan Zhou0Wenqian Huang1Xi Tian2School of Electronics and Information Engineering, West Anhui University, Lu’an 237000, ChinaIntelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, ChinaIntelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, ChinaAflatoxin B<sub>1</sub> (AFB<sub>1</sub>) is a very strong carcinogen, maize kernels are easily infected by this toxin during storage. Rapid and accurate identification of AFB<sub>1</sub> is of great significance to ensure food safety. In this study, a novel method for classification of AFB<sub>1</sub> in single maize kernels was developed. Four groups of maize kernel samples with different AFB<sub>1</sub> concentrations (10, 20, 50, and 100 ppb) were prepared by artificial inoculation of toxin. In addition, one group of maize kernel samples without AFB<sub>1</sub> were prepared as control, each group with 70 samples. The visible and short wave near-infrared (Vis-SWNIR) region (500–1000 nm) and long wave near-infrared (LWNIR) region (1000–2000 nm) hyperspectral images of all samples were obtained respectively, and the hyperspectral images in 500–2000 nm range was obtained after spectral pretreatment and fusion. Kennard-Stone algorithm was used to divide the samples into calibration set or prediction set. Competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to roughly select the characteristic wavelengths of the calibration set samples, and 25 and 26 effective wavelengths were obtained respectively. Based on the roughly selected wavelengths, a method of fine selection of the characteristic wavelengths was proposed by using the gray-value difference of image (GDI), and a few number of characteristic wavelengths were further selected. Under the LDA classification model, 10 characteristic wavelengths were selected to test the prediction set and the independent verification samples, and the ideal result were obtained with an accuracy of 94.46% and 91.11%, respectively. This study provides a new approach for AFB<sub>1</sub> concentration classification of single maize kernels.https://www.mdpi.com/2077-0472/12/3/385aflatoxin B<sub>1</sub>maize kernelscharacteristic wavelengthsgray-value difference of image |
| spellingShingle | Quan Zhou Wenqian Huang Xi Tian Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize Kernels Agriculture aflatoxin B<sub>1</sub> maize kernels characteristic wavelengths gray-value difference of image |
| title | Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize Kernels |
| title_full | Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize Kernels |
| title_fullStr | Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize Kernels |
| title_full_unstemmed | Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize Kernels |
| title_short | Feature Wavelength Selection Based on the Combination of Image and Spectrum for Aflatoxin B<sub>1</sub> Concentration Classification in Single Maize Kernels |
| title_sort | feature wavelength selection based on the combination of image and spectrum for aflatoxin b sub 1 sub concentration classification in single maize kernels |
| topic | aflatoxin B<sub>1</sub> maize kernels characteristic wavelengths gray-value difference of image |
| url | https://www.mdpi.com/2077-0472/12/3/385 |
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