Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral System
The variety of characteristics of red pepper makes it difficult to analyze at the production field through hyperspectral imaging. The importance of pretreatment to adjust the moisture content (MC) in the process of predicting the quality attributes of red pepper powder through hyperspectral imaging...
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MDPI AG
2022-12-01
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Online Access: | https://www.mdpi.com/2304-8158/11/24/4086 |
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author | Ji-Young Choi Jeong-Seok Cho Kee Jai Park Jeong Hee Choi Jeong Ho Lim |
author_facet | Ji-Young Choi Jeong-Seok Cho Kee Jai Park Jeong Hee Choi Jeong Ho Lim |
author_sort | Ji-Young Choi |
collection | DOAJ |
description | The variety of characteristics of red pepper makes it difficult to analyze at the production field through hyperspectral imaging. The importance of pretreatment to adjust the moisture content (MC) in the process of predicting the quality attributes of red pepper powder through hyperspectral imaging was investigated. Hyperspectral images of four types of red pepper powder with different pungency levels and MC were acquired in the visible near-infrared (VIS-NIR) and short-wave infrared (SWIR) regions. Principal component analysis revealed that the powders were grouped according to their pungency level, color value, and MC (VIS-NIR, Principal Component 1 = 95%; SWIR, Principal Component 1 = 91%). The loading plot indicated that 580–610, 675–760, 870–975, 1020–1130, and 1430–1520 nm are the key wavelengths affected by the presence of O-H and C-H bonds present in red pigments, capsaicinoids, and water molecules. The R<sup>2</sup> of the partial least squares model for predicting capsaicinoid and free sugar in samples with a data MC difference of 0–2% was 0.9 or higher, and a difference of more than 2% in MC had a negative effect on prediction accuracy. The color value prediction accuracy was barely affected by the difference in MC. It was demonstrated that adjusting the MC is essential for capsaicinoid and free sugar analysis of red pepper. |
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language | English |
last_indexed | 2024-03-09T16:39:46Z |
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spelling | doaj.art-0e7598e4dfce40cbb6a30af422c13fe12023-11-24T14:52:13ZengMDPI AGFoods2304-81582022-12-011124408610.3390/foods11244086Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral SystemJi-Young Choi0Jeong-Seok Cho1Kee Jai Park2Jeong Hee Choi3Jeong Ho Lim4Food Safety and Distribution Research Group, Korea Food Research Institute, Wanju 55365, Republic of KoreaFood Safety and Distribution Research Group, Korea Food Research Institute, Wanju 55365, Republic of KoreaSmart Food Manufacturing Project Group, Korea Food Research Institute, Wanju 55365, Republic of KoreaFood Safety and Distribution Research Group, Korea Food Research Institute, Wanju 55365, Republic of KoreaFood Safety and Distribution Research Group, Korea Food Research Institute, Wanju 55365, Republic of KoreaThe variety of characteristics of red pepper makes it difficult to analyze at the production field through hyperspectral imaging. The importance of pretreatment to adjust the moisture content (MC) in the process of predicting the quality attributes of red pepper powder through hyperspectral imaging was investigated. Hyperspectral images of four types of red pepper powder with different pungency levels and MC were acquired in the visible near-infrared (VIS-NIR) and short-wave infrared (SWIR) regions. Principal component analysis revealed that the powders were grouped according to their pungency level, color value, and MC (VIS-NIR, Principal Component 1 = 95%; SWIR, Principal Component 1 = 91%). The loading plot indicated that 580–610, 675–760, 870–975, 1020–1130, and 1430–1520 nm are the key wavelengths affected by the presence of O-H and C-H bonds present in red pigments, capsaicinoids, and water molecules. The R<sup>2</sup> of the partial least squares model for predicting capsaicinoid and free sugar in samples with a data MC difference of 0–2% was 0.9 or higher, and a difference of more than 2% in MC had a negative effect on prediction accuracy. The color value prediction accuracy was barely affected by the difference in MC. It was demonstrated that adjusting the MC is essential for capsaicinoid and free sugar analysis of red pepper.https://www.mdpi.com/2304-8158/11/24/4086red pepper powderhyperspectral imagingmultivariate analysismoisture adjustment |
spellingShingle | Ji-Young Choi Jeong-Seok Cho Kee Jai Park Jeong Hee Choi Jeong Ho Lim Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral System Foods red pepper powder hyperspectral imaging multivariate analysis moisture adjustment |
title | Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral System |
title_full | Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral System |
title_fullStr | Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral System |
title_full_unstemmed | Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral System |
title_short | Effect of Moisture Content Difference on the Analysis of Quality Attributes of Red Pepper (<i>Capsicum annuum</i> L.) Powder Using a Hyperspectral System |
title_sort | effect of moisture content difference on the analysis of quality attributes of red pepper i capsicum annuum i l powder using a hyperspectral system |
topic | red pepper powder hyperspectral imaging multivariate analysis moisture adjustment |
url | https://www.mdpi.com/2304-8158/11/24/4086 |
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