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Fundamental characterization of wheat gluten - Springer Therefore, we analyzed the content of crude protein, starch, lipids and ash, oil and water absorption capacity, particle size distribution, gluten pro-tein composition and spectroscopic properties of 39 vital gluten samples from 6 diferent suppliers
Effects of Physical and Chemical Factors on the Structure of . . . Additionally, effect of above mentioned factors can be determined in a common wheat dough, model dough (prepared from reconstituted flour containing only wheat starch and wheat gluten), gluten dough (lack of starch), and in gliadins and glutenins
An Intuitive Tutorial to Gaussian Process Regression Abstract—This tutorial aims to provide an intuitive introduction to Gaussian process regression (GPR) GPR models have been widely used in machine learning applications due to their representation flexibility and inherent capability to quantify uncertainty over predictions
Machine Learning-Based Terahertz Spectroscopy for Starch . . . Terahertz (THz) spectroscopy has emerged as a powerful, non-invasive tool for material characterization This study explores the integration of THz spectroscopy and machine learning for accurately quantifying maize starch adulteration in bioplastics derived from potato starch
Comprehensive study on gluten composition and baking quality . . . Parameters of the gluten aggregation test allowed a prediction of gluten, gliadin 6 0 mg g and 3 2 mg g, respectively, using PLS-regression Starch gelatinization temperature had an effect on gluten aggregation Conclusions The gluten aggregation test was suitable to predict gluten, gliadin and glutenin content