Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy
The feasibility of the two methodologies was confirmed to compare the results of determining mung bean origins using Raman and Near-Infrared (NIR) spectroscopy. Spectra from mung beans collected in Baicheng City, Jilin Province; Dorbod Mongol Autonomous, Tailai County, Heilongjiang Province; and Sis...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Foods |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2304-8158/14/1/89 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549200977821696 |
|---|---|
| author | Mingming Chen Zhigang Quan Xinyue Sun Yanlong Li Lili Qian Dongjie Zhang |
| author_facet | Mingming Chen Zhigang Quan Xinyue Sun Yanlong Li Lili Qian Dongjie Zhang |
| author_sort | Mingming Chen |
| collection | DOAJ |
| description | The feasibility of the two methodologies was confirmed to compare the results of determining mung bean origins using Raman and Near-Infrared (NIR) spectroscopy. Spectra from mung beans collected in Baicheng City, Jilin Province; Dorbod Mongol Autonomous, Tailai County, Heilongjiang Province; and Sishui County, Shandong Province, China, were analyzed. We established a traceability model using Principal Component Analysis combined with the K-nearest neighbor method to compare the efficacy of these methods in discriminating the origins of the mung beans. The total cumulative variance explained by the first three principal components from the NIR of mung beans from different origins was 99.01%, which is 6.71% higher than that derived from Raman. Additionally, the discrimination rate for mung bean origins based on NIR spectral data reached 98.67%, outperforming the Raman-based approach by 22.67%. These findings indicate that NIR spectroscopy is more effective than Raman spectroscopy is in tracing the provenance of mung beans. |
| format | Article |
| id | doaj-art-1f263e1560754cf2826f2f59358f8c48 |
| institution | Kabale University |
| issn | 2304-8158 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj-art-1f263e1560754cf2826f2f59358f8c482025-01-10T13:17:45ZengMDPI AGFoods2304-81582025-01-011418910.3390/foods14010089Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR SpectroscopyMingming Chen0Zhigang Quan1Xinyue Sun2Yanlong Li3Lili Qian4Dongjie Zhang5College of Food Science, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Food Science, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Food Science, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Food Science, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Food Science, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaCollege of Food Science, Heilongjiang Bayi Agricultural University, Daqing 163319, ChinaThe feasibility of the two methodologies was confirmed to compare the results of determining mung bean origins using Raman and Near-Infrared (NIR) spectroscopy. Spectra from mung beans collected in Baicheng City, Jilin Province; Dorbod Mongol Autonomous, Tailai County, Heilongjiang Province; and Sishui County, Shandong Province, China, were analyzed. We established a traceability model using Principal Component Analysis combined with the K-nearest neighbor method to compare the efficacy of these methods in discriminating the origins of the mung beans. The total cumulative variance explained by the first three principal components from the NIR of mung beans from different origins was 99.01%, which is 6.71% higher than that derived from Raman. Additionally, the discrimination rate for mung bean origins based on NIR spectral data reached 98.67%, outperforming the Raman-based approach by 22.67%. These findings indicate that NIR spectroscopy is more effective than Raman spectroscopy is in tracing the provenance of mung beans.https://www.mdpi.com/2304-8158/14/1/89mung beanRamannear-infrared spectroscopyorigin traceabilityK-nearest neighbor |
| spellingShingle | Mingming Chen Zhigang Quan Xinyue Sun Yanlong Li Lili Qian Dongjie Zhang Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy Foods mung bean Raman near-infrared spectroscopy origin traceability K-nearest neighbor |
| title | Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy |
| title_full | Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy |
| title_fullStr | Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy |
| title_full_unstemmed | Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy |
| title_short | Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy |
| title_sort | discriminating mung bean origins using pattern recognition methods a comparative study of raman and nir spectroscopy |
| topic | mung bean Raman near-infrared spectroscopy origin traceability K-nearest neighbor |
| url | https://www.mdpi.com/2304-8158/14/1/89 |
| work_keys_str_mv | AT mingmingchen discriminatingmungbeanoriginsusingpatternrecognitionmethodsacomparativestudyoframanandnirspectroscopy AT zhigangquan discriminatingmungbeanoriginsusingpatternrecognitionmethodsacomparativestudyoframanandnirspectroscopy AT xinyuesun discriminatingmungbeanoriginsusingpatternrecognitionmethodsacomparativestudyoframanandnirspectroscopy AT yanlongli discriminatingmungbeanoriginsusingpatternrecognitionmethodsacomparativestudyoframanandnirspectroscopy AT liliqian discriminatingmungbeanoriginsusingpatternrecognitionmethodsacomparativestudyoframanandnirspectroscopy AT dongjiezhang discriminatingmungbeanoriginsusingpatternrecognitionmethodsacomparativestudyoframanandnirspectroscopy |