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

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 RV 2 , 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.

Design and Fabrication of a Real-Time Measurement System for the Capsaicinoid Content of Korean Red Pepper (Capsicum annuum L.) Powder by Visible and Near-Infrared Spectroscopy

“…They are widely grown in tropical to temperate climates and have been important crop in Korea for a long time. Red pepper powders made by drying and grinding red-ripened red peppers are the main ingredient in Korean traditional foods such as Kimchi (fermented cabbage) and Gochujang (spicy red pepper paste) [ 1 , 2 ]. The pungent components in red pepper are collectively called capsaicinoids, and such pungent components are regarded to cause a feeling of pain when the taste nerve is strongly stimulated, rather than a sense of taste; these components can cause severe pain when they come in contact with skin [ 3 ].…”

“…Examples of such assays are the high performance liquid chromatography (HPLC), gas chromatography (GC), high performance liquid chromatography-mass spectrometry (HPLC-MS), and gas chromatography–mass spectrometry (GC–MS) [ 11 , 12 , 13 , 14 ]. However, these methods have the disadvantages that they require tedious sample preprocessing, take a long time for analysis, and only professional operators can perform analyses by this method [ 2 ].…”

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

“…In the PLS model, actually measured concentration information were used as dependent variables to develop a linear regression model with spectrum data, which are independent variables, and to predict actual concentration values [ 24 , 25 , 26 , 27 ]. PLS-DA is based on the classical partial least squares regression to construct prediction models [ 28 ].…”

Non-Destructive Prediction of Moisture Content of Philippine Coffea arabica and Coffea liberica Green Beans Using Locally-Developed NIR Spectroscopy Instrument

“…A rapid and non-destructive technique in determining the internal or external qualities of agricultural products, NIRS requires minimal sample preparation, needs no reagents and produces no waste (Qiao et al, 2015;Tolessa, et al, 2016). Norris (1964) first used NIRS in agriculture to rapidly measure the MC in grains including the protein and fat in agricultural products (Davies and Grant, 1987;Nicolaï et al, 2007;Lim et al, 2014). Many studies have also presented the potential of NIRS as an alternative technique in coffee quality analysis.…”