Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size
Apples are widely cultivated in the Republic of Korea and are preferred by consumers for their sweetness. Soluble solid content (SSC) is measured non-destructively using near-infrared (NIR) spectroscopy; however, the SSC measurement error increases with the change in apple size since the distance be...
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| Format: | Article |
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MDPI AG
2024-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/2/316 |
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| author | Doo-Jin Song Seung-Woo Chun Min-Jee Kim Soo-Hwan Park Chi-Kook Ahn Changyeun Mo |
| author_facet | Doo-Jin Song Seung-Woo Chun Min-Jee Kim Soo-Hwan Park Chi-Kook Ahn Changyeun Mo |
| author_sort | Doo-Jin Song |
| collection | DOAJ |
| description | Apples are widely cultivated in the Republic of Korea and are preferred by consumers for their sweetness. Soluble solid content (SSC) is measured non-destructively using near-infrared (NIR) spectroscopy; however, the SSC measurement error increases with the change in apple size since the distance between the light source and the near-infrared sensor is fixed. In this study, spectral characteristics caused by the differences in apple size were investigated. An optimal SSC prediction model applying partial least squares regression (PLSR) to three measurement conditions based on apple size was developed. The three optimal measurement conditions under which the Vis/NIR spectrum is less affected by six apple size levels (Levels I–VI) were selected. The distance from the apple center to the light source and that to the sensor were 125 and 75 mm (Distance 1), 123 and 75 mm (Distance 2), and 135 and 80 mm (Distance 3). The PLSR model applying multiplicative scatter correction pretreatment under Distance 3 measurement conditions showed the best performance for Level IV-sized apples (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mi mathvariant="normal">p</mi><mi mathvariant="normal">r</mi><mi mathvariant="normal">e</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula> = 0.91, RMSEP = 0.508 °Brix). This study shows the possibility of improving the SSC prediction performance of apples by adjusting the distance between the light source and the NIR sensor according to fruit size. |
| first_indexed | 2024-03-08T09:47:53Z |
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| language | English |
| last_indexed | 2024-03-08T09:47:53Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-91411a0d9da54d37b4cbdf55f78d0be62024-01-29T14:12:44ZengMDPI AGSensors1424-82202024-01-0124231610.3390/s24020316Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple SizeDoo-Jin Song0Seung-Woo Chun1Min-Jee Kim2Soo-Hwan Park3Chi-Kook Ahn4Changyeun Mo5Department of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon-si 24341, Republic of KoreaDepartment of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon-si 24341, Republic of KoreaAgriculture and Life Sciences Research Institute, Kangwon National University, Chuncheon-si 24341, Republic of KoreaDepartment of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon-si 24341, Republic of KoreaKorea Agriculture Technology Promotion Agency, Iksan-si 54667, Republic of KoreaDepartment of Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon-si 24341, Republic of KoreaApples are widely cultivated in the Republic of Korea and are preferred by consumers for their sweetness. Soluble solid content (SSC) is measured non-destructively using near-infrared (NIR) spectroscopy; however, the SSC measurement error increases with the change in apple size since the distance between the light source and the near-infrared sensor is fixed. In this study, spectral characteristics caused by the differences in apple size were investigated. An optimal SSC prediction model applying partial least squares regression (PLSR) to three measurement conditions based on apple size was developed. The three optimal measurement conditions under which the Vis/NIR spectrum is less affected by six apple size levels (Levels I–VI) were selected. The distance from the apple center to the light source and that to the sensor were 125 and 75 mm (Distance 1), 123 and 75 mm (Distance 2), and 135 and 80 mm (Distance 3). The PLSR model applying multiplicative scatter correction pretreatment under Distance 3 measurement conditions showed the best performance for Level IV-sized apples (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mi mathvariant="normal">p</mi><mi mathvariant="normal">r</mi><mi mathvariant="normal">e</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow></semantics></math></inline-formula> = 0.91, RMSEP = 0.508 °Brix). This study shows the possibility of improving the SSC prediction performance of apples by adjusting the distance between the light source and the NIR sensor according to fruit size.https://www.mdpi.com/1424-8220/24/2/316apple sizesoluble solid contentvisible near-infrared spectroscopypartial least squares regressionoptimal distance |
| spellingShingle | Doo-Jin Song Seung-Woo Chun Min-Jee Kim Soo-Hwan Park Chi-Kook Ahn Changyeun Mo Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size Sensors apple size soluble solid content visible near-infrared spectroscopy partial least squares regression optimal distance |
| title | Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size |
| title_full | Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size |
| title_fullStr | Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size |
| title_full_unstemmed | Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size |
| title_short | Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size |
| title_sort | performance improvement of partial least squares regression soluble solid content prediction model based on adjusting distance between light source and spectral sensor according to apple size |
| topic | apple size soluble solid content visible near-infrared spectroscopy partial least squares regression optimal distance |
| url | https://www.mdpi.com/1424-8220/24/2/316 |
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