Soybean Saponin Content Detection Based on Spectral and Image Information Combination
Soybean saponin is a natural antioxidant and is anti-inflammatory. Hyperspectral analysis technology was applied to detect soybean saponin content rapidly and nondestructively in this paper. Firstly, spectral preprocessing methods were studied, and standard normal variable (SNV) was used to remove n...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2024/7599132 |
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| _version_ | 1850174047391842304 |
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| author | Hongmin Sun Xifan Meng Yingpeng Han Xiao Li Xiaoming Li Yongguang Li |
| author_facet | Hongmin Sun Xifan Meng Yingpeng Han Xiao Li Xiaoming Li Yongguang Li |
| author_sort | Hongmin Sun |
| collection | DOAJ |
| description | Soybean saponin is a natural antioxidant and is anti-inflammatory. Hyperspectral analysis technology was applied to detect soybean saponin content rapidly and nondestructively in this paper. Firstly, spectral preprocessing methods were studied, and standard normal variable (SNV) was used to remove noise information. Secondly, a two-step hybrid variable selection approach based on synergy interval partial least squares (SiPLS) and iteratively retains informative variables (IRIV) was proposed to extract characteristic variables. Then, the ensemble learning model was constructed by back propagation neural network (BPNN), deep forest (DF), partial least squares regression (PLSR), and extreme gradient boosting (EXG). Finally, image information was combined into spectral data to improve model accuracy. The prediction coefficient of determination (R2) of the final model reached 0.9216. It can provide rapid, nondestructive, and accurate detection technology of soybean saponin content. A combination of spectral and image information will provide a new idea for application of hyperspectral. |
| format | Article |
| id | doaj-art-c734eafd459d45738e36e6052202af1a |
| institution | OA Journals |
| issn | 2314-4939 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Spectroscopy |
| spelling | doaj-art-c734eafd459d45738e36e6052202af1a2025-08-20T02:19:44ZengWileyJournal of Spectroscopy2314-49392024-01-01202410.1155/2024/7599132Soybean Saponin Content Detection Based on Spectral and Image Information CombinationHongmin Sun0Xifan Meng1Yingpeng Han2Xiao Li3Xiaoming Li4Yongguang Li5School of Electrical and InformationSchool of Electrical and InformationSchool of AgricultureChina Agriculture PressSchool of Electrical and InformationSchool of AgricultureSoybean saponin is a natural antioxidant and is anti-inflammatory. Hyperspectral analysis technology was applied to detect soybean saponin content rapidly and nondestructively in this paper. Firstly, spectral preprocessing methods were studied, and standard normal variable (SNV) was used to remove noise information. Secondly, a two-step hybrid variable selection approach based on synergy interval partial least squares (SiPLS) and iteratively retains informative variables (IRIV) was proposed to extract characteristic variables. Then, the ensemble learning model was constructed by back propagation neural network (BPNN), deep forest (DF), partial least squares regression (PLSR), and extreme gradient boosting (EXG). Finally, image information was combined into spectral data to improve model accuracy. The prediction coefficient of determination (R2) of the final model reached 0.9216. It can provide rapid, nondestructive, and accurate detection technology of soybean saponin content. A combination of spectral and image information will provide a new idea for application of hyperspectral.http://dx.doi.org/10.1155/2024/7599132 |
| spellingShingle | Hongmin Sun Xifan Meng Yingpeng Han Xiao Li Xiaoming Li Yongguang Li Soybean Saponin Content Detection Based on Spectral and Image Information Combination Journal of Spectroscopy |
| title | Soybean Saponin Content Detection Based on Spectral and Image Information Combination |
| title_full | Soybean Saponin Content Detection Based on Spectral and Image Information Combination |
| title_fullStr | Soybean Saponin Content Detection Based on Spectral and Image Information Combination |
| title_full_unstemmed | Soybean Saponin Content Detection Based on Spectral and Image Information Combination |
| title_short | Soybean Saponin Content Detection Based on Spectral and Image Information Combination |
| title_sort | soybean saponin content detection based on spectral and image information combination |
| url | http://dx.doi.org/10.1155/2024/7599132 |
| work_keys_str_mv | AT hongminsun soybeansaponincontentdetectionbasedonspectralandimageinformationcombination AT xifanmeng soybeansaponincontentdetectionbasedonspectralandimageinformationcombination AT yingpenghan soybeansaponincontentdetectionbasedonspectralandimageinformationcombination AT xiaoli soybeansaponincontentdetectionbasedonspectralandimageinformationcombination AT xiaomingli soybeansaponincontentdetectionbasedonspectralandimageinformationcombination AT yongguangli soybeansaponincontentdetectionbasedonspectralandimageinformationcombination |