Antinutrient to mineral molar ratios of raw common beans and their rapid prediction using near-infrared spectroscopy. (30th January 2022)

• Record Type: Journal Article
• Authors: Wafula, Elizabeth Nakhungu; Onduso, Mercyline; Wainaina, Irene Njoki; Buvé, Carolien; Kinyanjui, Peter Kahenya; Githiri, Stephen Mwangi; Saeys, Wouter; Sila, Daniel Ndaka; Hendrickx, Marc
• Is Part Of: Food chemistry. Volume 368(2022)
• Publication Date: 2022-01-30
• Subjects: iPLS Interval partial least squares -- MRs molar ratios -- NIR Near-infrared -- PLS-R Partial least squares regression -- RMSEC Root mean square error of calibration -- RMSECV Root mean square error of cross validation -- RMSEP Root mean square error of prediction -- R2C coefficient of determination in calibration -- R2CV coefficient of determination in cross validation -- R2P coefficient of determination in test set prediction -- LV latent variables -- MC mean centering -- SNV standard normal variate -- OSC orthogonal signal correction; Common beans -- Near-infrared spectroscopy -- Antinutrients -- Minerals -- Molar ratios; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2021.130773
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Bean type had a significant effect on tannins contents. Phytate to iron and phytate to zinc molar ratios of raw beans were high. NIR spectroscopy predicted antinutrient to mineral molar ratios of raw beans. Ability to predict antinutrient influenced prediction of molar ratios using NIR. Abstract: The presence of antinutrients in common beans negatively affects mineral bioavailability. Therefore, this study aimed to predict the antinutrient to mineral molar ratios (proxy-indicators of in vitro mineral bioavailability) of a wide range of raw bean types, using near-infrared (NIR) spectroscopy. Iron, zinc, phytate and tannin concentrations and, antinutrient to mineral molar ratios were determined. Next, model calibration using NIR spectra from milled beans was performed. This entailed wavelength selection, pre-processing and partial least squares regression. Bean type had a significant effect on tannin content. The average values of phytate to iron (Phy:Fe), phytate to zinc (Phy:Zn), tannins to iron (Tan:Fe) and phytate and tannins to iron (Phy + Tan:Fe) MRs were 27.6, 61.7, 16.0 and 43.6, respectively. With determination coefficients for test set prediction above 75%, the PLS-R models for Phy:Zn, Tan:Fe and Phy + Tan:Fe molar ratios are useful for screening purposes.