Hyperspectral image control of the heat-treatment process of oat flour to model composite bread properties

Abstract

A hyperspectral image analysis was used to characterize heat treatment in oat flour, performed by treating oat flour at 80, 100 and 130 °C for 30 min. Images from both original oat and treated flours were captured, and hyperspectral information was collected. Oat flours were used to obtain composite flours based on two different substitution levels (10 and 20%) of wheat flour. Composite breads were produced from the obtained flours. A battery of analyses was run to characterize them in terms of physical properties. The hyperspectral information of oat flours was analyzed by multivariate statistics and a pattern evolution-depending temperature was observed. Similarly, a set of the physical properties of breads was analyzed based on multivariate statistics, and a pattern of temperature-dependent evolution, in addition to the substitution level, was also recognized. Multivariate non linear regressions were done between both data sets to study their relationship and high values in the calibration and cross-validation results obtained. The changes undergone by oat flour during treatment were characterized with hyperspectral information, which could represent a non destructive monitoring tool to then regulate it until oat flours are obtained that confer composite bread adequate properties.