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Published VersionCC BY-NC-ND V4.0, Open Access
Journal article
Metrics to assess pulse grains for protein enrichment potential in air classification
Food Research International, Vol.214, pp.1-13
2025
PMID: 40467189
Abstract
Optimisation of grain milling and air classification to maximise the protein enrichment efficiency (PEE) is tedious. Powder flow properties such as caking strength, influenced by particle interlocking and underlying cohesive forces, are determined in the dry ingredient industry to optimise operations such as filling and storage. Caking strength, apart from the moisture and fat contents, is determined by particle size & shape. Since protein fraction via air classification is also dependent upon particle size & shape, it is hypothesised that caking strength can predict PEE.
In this study, metrics were developed to assess pulse grains for protein enrichment potential in air classification based on caking strength of jet-milled pulse flours. The effect of the operational settings controlling the particle size in conventional pre-milling and jet-milling is also investigated. An inverse correlation (R2 = 0.94, p < 0.001) between the PEE and caking strength was found. Imaging and microscopic analyses of jet-milled flours based on the graphic and data analytics, revealed size and shape information practically explained the differences in caking strength. Starch granule and fibre circularity and convexity (surface smoothness) are useful measures of the shape in optimising milling and maximising PEE in air classification without compromising the yield of the protein fraction.
By measuring the caking strength of pulse flours, PEE in air classification may potentially be predicted. Therefore, this rapid measure may find use in both the i) prediction of protein enrichment of pulses fractionated in commercial dry fractionation plants, and ii) development of new pulse varieties tailored to improved enrichment of protein into fine fractions.
Details
- Title
- Metrics to assess pulse grains for protein enrichment potential in air classification
- Authors
- Vishal Ratanpaul (Corresponding Author) - CSIRO Agriculture and Food (Australia)Philip Hands - CSIRO Agriculture and Food (Australia)Regine Stockmann - CSIRO Agriculture and Food (Australia)
- Publication details
- Food Research International, Vol.214, pp.1-13
- Publisher
- Elsevier Ltd
- Date published
- 2025
- DOI
- 10.1016/j.foodres.2025.116505
- ISSN
- 1873-7145; 0963-9969
- PMID
- 40467189
- Copyright note
- © 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).
- Data Availability
- The authors do not have permission to share data.
- Grant note
- This project was funded and supported by the CSIRO Impossible Without You program.
- Organisation Unit
- School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 991212980902621
- Output Type
- Journal article
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