Profiling and Characterization of Seed Storage Proteins From Borage ( <i>Borago officinalis</i> L.) Pressed Cake as a Novel Plant‐Based Protein Source
Bibliographic record
Abstract
ABSTRACT Borage pressed cake, a by‐product of borage oil extraction, currently remains an underutilized resource despite its high protein content (~32%, w/w). Scientific knowledge on borage seed proteins remains limited; therefore, this study aimed to characterize the composition and properties of borage seed proteins to address this gap and explore their potential as a novel protein source. Protein fractionation based on Osborne's classification identified glutelin as the predominant protein class, while a substantial proportion of the protein remained insoluble under standard Osborne extraction conditions, indicating the presence of structurally complex or aggregated protein forms. Polypeptide profile analysis using SDS‐PAGE revealed polypeptides characteristic of 2S‐albumin, 11S‐globulin, 7S‐globulin, and glutelin‐like proteins. Borage proteins demonstrated high thermal stability, with denaturation peaks at 109°C–110°C. Protein solubility was low across pH 2–10, with a minimum between pH 4–6 and a notable increase at pH 12. Functional assessments indicated water holding capacity of 0.59–0.67 g/g and oil holding capacity of 1.03–1.14 g/g. Lysine was found as the limiting amino acid in borage protein, with moderate digestibility resulting from in vitro protein digestibility corrected amino acid score (IVPDCAAS). Comparative analyses between laboratory‐prepared and commercially processed pressed‐cakes revealed differences in protein structure, functionality, and digestibility, likely due to processing variations. These findings highlight the nutritional and functional properties of borage pressed cake. However, this is the first scientific study focused on borage seed proteins. Further investigations are necessary to develop borage as a novel and sustainable protein source for plant‐based protein applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".