A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy
The objective of this research was to classify the geographical origin of durians (cv. Monthong) based on geographical identification (GI) and regions (R) using near infrared (NIR). The samples were scanned with an FT-NIR spectrometer (12,500 to 4000 cm<sup>−1</sup>). The NIR absorbance...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/12/20/3844 |
| _version_ | 1797573827393224704 |
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| author | Kingdow Chanachot Wanphut Saechua Jetsada Posom Panmanas Sirisomboon |
| author_facet | Kingdow Chanachot Wanphut Saechua Jetsada Posom Panmanas Sirisomboon |
| author_sort | Kingdow Chanachot |
| collection | DOAJ |
| description | The objective of this research was to classify the geographical origin of durians (cv. Monthong) based on geographical identification (GI) and regions (R) using near infrared (NIR). The samples were scanned with an FT-NIR spectrometer (12,500 to 4000 cm<sup>−1</sup>). The NIR absorbance differences among samples that were collected from different parts of the fruit, including intact peel with thorns (I-form), cut-thorn peel (C-form), stem (S-form), and the applied synthetic minority over-sampling technique (SMOTE), were also investigated. Models were developed across several classification algorithms by the classification learner app in MATLAB. The models were optimized using a featured wavenumber selected by a genetic algorithm (GA). An effective model based on GI was developed using SMOTE-I-spectra with a neural network; accuracy was provided as 95.60% and 95.00% in cross-validation and training sets. The test model was provided with a testing set value of %accuracy, and 94.70% by the testing set was obtained. Likewise, the model based on the regions was developed from SMOTE-ICS-form spectra, with the ensemble classifier showing the best result. The best result, 88.00FF% accuracy by cross validation, 86.50% by training set, and 64.90% by testing set, indicates the classification model of East (E-region), Northeast (NE-region), and South (S-region) regions could be applied for rough screening. In summary, NIR spectroscopy could be used as a rapid and nondestructive method for the accurate GI classification of durians. |
| first_indexed | 2024-03-10T21:14:32Z |
| format | Article |
| id | doaj.art-42b751f10f244e40845f206400d07d26 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-10T21:14:32Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-42b751f10f244e40845f206400d07d262023-11-19T16:30:38ZengMDPI AGFoods2304-81582023-10-011220384410.3390/foods12203844A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance SpectroscopyKingdow Chanachot0Wanphut Saechua1Jetsada Posom2Panmanas Sirisomboon3Department of Agricultural Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandDepartment of Agricultural Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandDepartment of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, ThailandDepartment of Agricultural Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandThe objective of this research was to classify the geographical origin of durians (cv. Monthong) based on geographical identification (GI) and regions (R) using near infrared (NIR). The samples were scanned with an FT-NIR spectrometer (12,500 to 4000 cm<sup>−1</sup>). The NIR absorbance differences among samples that were collected from different parts of the fruit, including intact peel with thorns (I-form), cut-thorn peel (C-form), stem (S-form), and the applied synthetic minority over-sampling technique (SMOTE), were also investigated. Models were developed across several classification algorithms by the classification learner app in MATLAB. The models were optimized using a featured wavenumber selected by a genetic algorithm (GA). An effective model based on GI was developed using SMOTE-I-spectra with a neural network; accuracy was provided as 95.60% and 95.00% in cross-validation and training sets. The test model was provided with a testing set value of %accuracy, and 94.70% by the testing set was obtained. Likewise, the model based on the regions was developed from SMOTE-ICS-form spectra, with the ensemble classifier showing the best result. The best result, 88.00FF% accuracy by cross validation, 86.50% by training set, and 64.90% by testing set, indicates the classification model of East (E-region), Northeast (NE-region), and South (S-region) regions could be applied for rough screening. In summary, NIR spectroscopy could be used as a rapid and nondestructive method for the accurate GI classification of durians.https://www.mdpi.com/2304-8158/12/20/3844geographical identification (GI)regions classificationnear-infrared spectroscopysynthetic minority over-sampling technique |
| spellingShingle | Kingdow Chanachot Wanphut Saechua Jetsada Posom Panmanas Sirisomboon A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy Foods geographical identification (GI) regions classification near-infrared spectroscopy synthetic minority over-sampling technique |
| title | A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy |
| title_full | A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy |
| title_fullStr | A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy |
| title_full_unstemmed | A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy |
| title_short | A Geographical Origin Classification of Durian (cv. Monthong) Using Near-Infrared Diffuse Reflectance Spectroscopy |
| title_sort | geographical origin classification of durian cv monthong using near infrared diffuse reflectance spectroscopy |
| topic | geographical identification (GI) regions classification near-infrared spectroscopy synthetic minority over-sampling technique |
| url | https://www.mdpi.com/2304-8158/12/20/3844 |
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