Effect of Extraction Time on Chemical, Physical and Organoleptic Characteristics of South Asian Applesnail (Pila ampullacea) Protein Concentrate
Bibliographic record
Abstract
This research aims to investigate the effect of protein extraction time using 90% ethanol on the protein concentrate product's physical, chemical, and organoleptic characteristics. The findings of this study could promote the use of protein concentrate developed from SAA. The study was conducted from April to June 2024, utilizing SAA collected from rice fields in the PALI (Penukal Abab Lematang Ilir) Regency, South Sumatra Province, Indonesia. A completely randomized design was employed, using different extraction times of proteins from SAA with 90% ethanol. Four extraction time levels were tested: 0 hours (P0 or control), 24 hours (P1), 28 hours (P2), and 32 hours (P3), each with three repetitions. Data were analyzed using ANOVA, followed by a post-hoc test employing Duncan's multiple range test, utilizing SPSS version 20.0. Results have shown that the optimal protein extraction time was P2 (28 hours), yielding a protein concentration of 51.6% on a dry basis. Additionally, protein profile analysis conducted via SDS-PAGE revealed the presence of histone proteins and an antibacterial protein derived from snail mucus in SAA. Treatment P2 exhibited five distinct protein bands with molecular weights of 17 kDa, 20 kDa, 25 kDa, 35 kDa, and over 48 kDa respectively. On the other hand, treatments P1 and P3 displayed only three protein bands that are 20 kDa, 35 kDa, and over 48 kDa. Results from the organoleptic analysis indicated that protein isolates with suitable attributes in terms of color and aroma were obtained from treatment P1 (24-hour extraction). This study has potential applications in the 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 | 0.001 | 0.001 |
| 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".