Data underlying the research on: Protein enrichment of oat flour by fine milling and air classification

This dataset was generated as part of a research project focused on the dry fractionation of oat flours using milling and air classification techniques to obtain protein-enriched fractions. The overarching goal of the project is to explore the processing conditions of a sustainable, dry-based processing method to enhance the nutritional and functional properties of oat-derived ingredients, with a particular emphasis on increasing protein concentration without the use of water. The dataset includes multiple types of data collected to evaluate and optimize dry fractionation conditions for protein enrichment in oat flours. It contains Scanning Electron Microscope (SEM) images of oat flours and fractions, particle size distribution (PSD) curves, and key quantifiers such as D10, D50, and D90 values for the flours. It also includes indicators of fractionation efficiency, such as protein enrichment and protein recovery, which were calculated based on measured protein contents and mass yields of the resulting fractions. Additionally, the dataset provides detailed compositional analyses (e.g., protein, starch, fiber, and fat) of selected oat fractions from two oat cultivars, as well as two commercial oat protein concentrates. These compositional profiles offer insights into the nutritional and techno-functional potential of the fractions, supporting their future applications as plant-based food ingredients. Potential users of this dataset include food scientists, grain processing researchers, and ingredient technologists interested in alternative proteins, sustainable processing methods, or cereal microstructure. The dataset can be used to model or optimize dry fractionation techniques aimed at increasing the protein content of cereal flours. Additionally, parts of the dataset may be relevant for further research on oat-based food ingredients, including studies on their techno-functional properties, digestibility, and potential health benefits. For any questions, comments, or feedback, please contact Danny Tagle-Freire at [email protected].