Non-destructive and Rapid Prediction of Moisture Content in Red Pepper (Capsicum annuum L.) Powder Using Near-infrared Spectroscopy and a Partial Least Squares Regression Model

Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated int...

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Veröffentlicht in:Journal of biosystems engineering 2014-09, Vol.39 (3), p.184-193
Hauptverfasser: Lim, Jongguk, Mo, Changyeun, Kim, Giyoung, Kang, Sukwon, Lee, Kangjin, Kim, Moon S, Moon, Jihea
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container_end_page 193
container_issue 3
container_start_page 184
container_title Journal of biosystems engineering
container_volume 39
creator Lim, Jongguk
Mo, Changyeun
Kim, Giyoung
Kang, Sukwon
Lee, Kangjin
Kim, Moon S
Moon, Jihea
description Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of RV2, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ±0.487% wb, and 10.00, respectively. Conclusions: These results demonstrated that NIR spectroscopy and a PLSR model could be useful techniques for measuring rapidly and non-destructively the moisture content in red pepper powder.
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Powder Using Near-infrared Spectroscopy and a Partial Least Squares Regression Model</title><source>EZB-FREE-00999 freely available EZB journals</source><source>KoreaScience</source><creator>Lim, Jongguk ; Mo, Changyeun ; Kim, Giyoung ; Kang, Sukwon ; Lee, Kangjin ; Kim, Moon S ; Moon, Jihea</creator><creatorcontrib>Lim, Jongguk ; Mo, Changyeun ; Kim, Giyoung ; Kang, Sukwon ; Lee, Kangjin ; Kim, Moon S ; Moon, Jihea</creatorcontrib><description>Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of RV2, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ±0.487% wb, and 10.00, respectively. 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Powder Using Near-infrared Spectroscopy and a Partial Least Squares Regression Model</title><title>Journal of biosystems engineering</title><addtitle>Journal of biocystems Engineering</addtitle><description>Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated into three groups based on their particle sizes using a standard sieve. Each product was prepared, and the expected moisture content range was divided into six or seven levels from 3 to 21% wb with 3% wb intervals. The NIR reflectance spectra acquired in the wavelength range from 1,100 to 2,300 nm were used for the development of prediction models of the moisture content in red pepper powder. Results: The values of RV2, SEP, and RPD for the best PLSR model to predict the moisture content in red pepper powders of varying particle sizes below 1.4 mm were 0.990, ±0.487% wb, and 10.00, respectively. 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source EZB-FREE-00999 freely available EZB journals; KoreaScience
subjects AOTF-NIR spectroscopy
Moisture content
Non-destructive
PLSR
Red pepper powder
title Non-destructive and Rapid Prediction of Moisture Content in Red Pepper (Capsicum annuum L.) Powder Using Near-infrared Spectroscopy and a Partial Least Squares Regression Model
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