Evaluation of physicochemical and functional properties of spray‐dried protein hydrolysate from non‐penaeid shrimp (<i>Acetes indicus</i>)
Bibliographic record
Abstract
Abstract BACKGROUND Protein hydrolysate powder was prepared from non‐penaeid shrimp ( Acetes indicus ) by enzymatic hydrolysis using Alcalase enzyme. Extraction conditions such as pH (6.5, 7.5 and 8.5), enzyme to substrate ratio (1.0, 1.5 and 2.0) and temperature (40, 50 and 60 °C) were optimized against the degree of hydrolysis using response surface methodology. RESULTS Protein hydrolysate comprised of 740 g kg −1 protein, 150 g kg −1 ash and 90 g kg −1 fat contents. The amino acid score showed superior attributes with 56% essential amino acids. Furthermore, the functional properties of spray‐dried protein hydrolysates were evaluated. Protein solubility was found to be the 90.20% at pH 2 and 96.92% at pH 12. Emulsifying properties were found to vary with the concentration of protein hydrolysates and the highest emulsifying capacity (26.67%) and emulsion stability (23.33%) were found at a concentration of 20 mg mL −1 . The highest and the lowest foaming capacity were observed at pH 6 and pH 10 with a concentration of 20 mg mL −1 . The water holding capacity of protein hydrolysate was found to increase with concentration, with a value of 5.4 mL g −1 at a concentration of 20 mg mL −1 . CONCLUSION The results of the present study indicate that the use of A. indicus for the production of protein hydrolysate has good functional properties and nutritional value, rendering it suitable for broad industrial food applications. © 2019 Society of Chemical 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 | 0.000 |
| 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".