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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #310875
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

Author
item LIM, JONGGUK - National Academy Of Agricultural Science
item MO, CHANGYEUN - National Academy Of Agricultural Science
item KIM, GIYOUNG - National Academy Of Agricultural Science
item KANG, SUKWON - National Academy Of Agricultural Science
item LEE, KANGGJIN - National Academy Of Agricultural Science
item Kim, Moon
item MOON, JIHEA - National Academy Of Agricultural Science

Submitted to: Journal of Biosystems Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/1/2014
Publication Date: 3/1/2014
Citation: Lim, J., Mo, C., Kim, G., Kang, S., Lee, K., Kim, M.S., Moon, J. 2014. 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. Journal of Biosystems Engineering. 39:184-193.

Interpretive Summary: Near infrared spectroscopy technologies have been widely used to evaluate various quality parameters of agricultural commodities. A study was conducted to predict moisture content in red pepper powder, a major food ingredient in Korean cuisine, using near-infrared spectroscopy in the wavelength range from 1100 to 2300 nm. The results show that the moisture contents of red pepper powders can be nondestructively predicted with 99% accuracy. The method presented in this research can be used to provide a rapid means to assess moisture contents of food ingredients and is beneficial to food technologists and the food ingredient industry.

Technical Abstract: 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 R2, 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.