Pengaruh Jenis Medium Terhadap Kecepatan Penetrasi Panas dan Daya Terima Produk Kalengan Ikan Tuna Skipjack (Katsuwonus pelamis)
Bibliographic record
Abstract
Tuna fish has high content of protein. The purpose of food processing is to make a well preserve product, improving the taste and increasing economic value. Sterilization of canned tuna is an example of food processing to achieve the above purpose. A well preserve product must be free from the possibility of proliferation of microorganisms. The objective of this study was to investigate and evaluate the impact of medium used in canned tuna product on heat penetration speed during sterilization and to know the preference level by consumer.Determination of F0 value in this research refers to the protocol of Canadian Food Inspection Agency (CFIA) by using general method to analyse data, protein analysis followed Kjeldahl method and organoleptic examination used Friedman test. Analysis of effectiveness index was conducted to determine the best treatment. The experimental design used randomized single design with three kinds of treatments which were repeated 3 times for each observation. Results indicated that the fastest heat penetration was obtained by in brine product with 46 minutes sterilizatiion time, followed by in oil product with 62 minutes, then in brine + oil product with 65 minutes. Analysis of variance showed that treatment of medium usage provides a very significant impact on heat penetration (F count larger than F table 5 % and 1 %). Heat treatment also provides a significant impact on protein content (F count larger than F table 5 % and 1 %). Organoleptic examination showed that treatment gave significant effect on flavour and odor (F count larger than F table), but not significant on color (F count is smaller than F table). In conclusion, the fastest heat penetration was obtained by in brine product with 46 minutes sterilization time, followed by in oil product 62 minutes, then in brine + oil product with 65 minutes. Consumer preference and the best treatment in this research was obtained by in brine + oil product, followed by in oil product, then in brine product.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".