A Comparative Study between Response Surface Methodology and Genetic Algorithm in Optimization and Extraction of Leaf Protein Concentrate from Diplazium esculentum of Assam
Bibliographic record
Abstract
Fern is a seedless vascular plant that reproduces via spores and has various usefulness.This study was carried out to optimize the conditions of leaf protein concentrate extraction using ultrasound from defatted fern type Diplazium esculentum.The extraction of defatted fern protein was conducted using ultrasound.Rotatable central composite design (RCCD) of response surface methodology was used for identification of the best condition and extraction yield optimization.An attempt with genetic algorithm optimization was also carried out and revealed that optimized results were of highest desirability as compared to response surface methodology.The final optimum results, by using genetic algorithm was observed to be 21.12 min of sonication time, 56.88 °C temperature, 7.59 pH and 66.2 ml of solvent for an optimum protein yield of 33.79% where desirability value was 1.00.UHPLC analysis of the sample revealed the presence of all the essential amino acids, except tryptophan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".