EFFECT OF HIGH‐PRESSURE HOMOGENIZATION ON THE FUNCTIONAL PROPERTY OF PEANUT PROTEIN
Bibliographic record
Abstract
ABSTRACT The effect of high‐pressure homogenization (HPH) at 0.1 (control), 40 or 80 MPa on the denatured peanut protein were investigated. Solubility, emulsifying property, foaming property, differential scanning calorimetry (DSC) characteristic, water‐holding capacity (WHC) and scanning electron microscope (SEM) analysis of the peanut protein isolates (PPIs) from the peanut flour after various HPH treatments were analyzed. Increased solubility of the denatured peanut protein by HPH treatment depended on the pH value. In the range of pH 4−7, the HPH‐treated peanut protein exhibited a higher solubility than the non‐HPH‐treated protein, but the HPH treatment did not affect significantly the solubility in the range of pH 8−10. HPH treatment improved the emulsifying activity index (EAI) and foaming capacity (FC) but reduced the emulsifying stability index and foaming stability. In addition, HPH treatment markedly improved the WHC but slightly affected the DSC parameter. Based on the observation of SEM, many irregular fine crackles in the peanut protein after HPH treatment appeared, which showed that the treatment resulted in the change in the surface microstructure of the protein. These results indicated that the HPH treatment led to the modification of the microstructure of peanut protein and, thus, improved its functional properties such as EAI, FC and WHC. PRACTICAL APPLICATIONS Functional properties of plant and animal proteins are important in food processing and production formulation. Peanut exhibits an excellent potential as a source of plant proteins. Improvement of functional or nutritional properties of proteins can help produce some novel food products in food industry. The use of high‐pressure homogenization (HPH) is one of the most efficient means to improve the functional properties of plant proteins. The study exhibited that application of HPH treatment resulted in the changed the microstructure of peanut protein and, thus, improved its functional properties such as the emulsifying activity index, foam capacity and water‐holding capacity, which might be utilized in food industry.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".