STUDI MIKROENKAPSULASI MINYAK IKAN KAYA ASAM LEMAK OMEGA-3 DARI LIMBAH CAIR INDUSTRI PENGALENGAN IKA.N LEMURU (LEMURU PRECOOK OIL):
Bibliographic record
Abstract
industry which has very low economic value. The oil mostly used on paint and vernis industries, also as additive for feed. The oil contain omega-3 fatty acid about 19-23 % (Setiabudi, 1990 and Riyanto, 1995). The usage oflemuru precook oil on food industries has not been studied. Aim of this research was to study the usage ofliquid waste or by-product oflemuru canning industry for high value food product i.e. microencapsulation ofomega-3 rich fish oil and its consumers prefer• ence test. Experiment design used in the research was Randomized Block Design (RBD) with two factors treatments; encapsulant proponion gelatin-maltodekstrin (E)ofl : I, 1 : 2,2: 1 and 2: 3 (w/ w), and lemuru fish oil and encapsulants proportions (M) of 1 : 2 and I : 4 (v/w). The lemuru fish oil was prepared using method of Elizabeth (l 992), and its microencapsulation using method of'Kartika (2003). Variables observed were; water-content, total-oil, capsulated-oil content, uncapsulated• oil, FFA, Omega-3 fatty acid content, peroxide-number, microenkapsulation efficiency, yield, microenkapsule performance (textur), and consumers preference test (flavor and aftertaste ofoil). The physico-chemical data was analyzed using F Test and DMRTTest 5%, and the preference Test data analyzed using Friedman Test and Multiple Comparison Test (Dannie!, 1999). The best treat· ments combination was determined using effective Index Test (DeGarmo, Canada and Sullivan, 1998). Result of the research showed that treatment combination ofE4M I; i.e. treatments of proportion of2 : 3 (w/w) gelatin-maltodekstrin, and proportion of I : 2 (w/v) fish oil-encapsulant produced meicroencapsule with the best physico-chemical properties. The product has characteristics of: Omega-3 fatty acid content of20,95 percents (0,34 percents, linolenat acid, 3,35 per• cents, EPA, and 17 ,26 percents, DHA), total-oil of 18,376 percents, uncapsulated-oil of2,3 I 8 percents, microencapsulation efficiency of36,857 percents, water-content ofS,273 percents, FFA of3,249 percents, peroxide-number of 1,265 (meq/k.g), and yield of98,23 l percents. Based on the results, suggested that the advantage of encapsulation using freeze drier technique produce fish oil microencapsule with relatively low inwater content ( < 5 percents), and low Omega-3 fatty acid degradation (1-2 percents), however, its FFA content still high and sensory properties still not preferencesby consummers.
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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) | 0.002 | 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".