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Simultaneous estimation of amylose,resistant, and digestible starch in pea flour by visible and near-infrared reflectance spectroscopy
Authors:Lingjie Zeng
Affiliation:1. College of Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, China;2. Eastern Agricultural Research Center, Montana State University, Sidney, MT, USA
Abstract:Due to its health benefits, resistant starch (RS) has received increasing attention from the public, and there is a need to develop methods to measure the amylose and RS concentration in pea (Pisum sativum L.) flour. The aim of this study was to develop a visible and near-infrared reflectance (vis–NIR) model for the simultaneous determination of amylose, RS, and digestible starch (DS) in pea flour. A total of 123 dry pea samples consisting of different pea varieties grown in different environments were collected, and ground to flour, and then the vis–NIR spectra were scanned. The amylose, RS, and DS contents of the pea flours were also measured by an enzymatic colorimetric assay. The spectra data were calibrated with the enzymatic colorimetric-assayed values. Results showed that amylose, RS, and DS in the pea flours can be simultaneously estimated using the vis–NIR spectra. Instead of using the full spectrum (300–2300 nm), we found the most efficient wave bands lying in the visible region between 370 and 560 nm and the NIR spectra in the range of 1600–1800 nm. Using the stepwise regression with backward elimination method, the multiple linear regression (MLR) models were developed from the most efficient wavelengths. The MLR models had the determination coefficients R2 of 0.95, 0.76, 0.80, and 0.88 for amylose, RS, DS, and total starch, respectively. The correlation coefficients between model estimated and the enzymatic colorimetric assayed values were 0.97, 0.80, 0.85, and 0.93 for amylose, RS, DS, and total starch, respectively.
Keywords:Pea (Pisum sativum L.)  vis–NIR  amylose  resistant starch  modeling
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