Jumlah Konsumsi Pakan, Efisiensi dan Laju Pertumbuhan Relatif Ikan Bawal (Colossoma macropomum) yang Diberi Pakan Buatan Berbahan Tepung Lemna minor Fermentasi
Bibliographic record
Abstract
Pakan merupakan faktor penting dalam kegiatan budidaya ikan secara intensif. Penggunaan Lemna minor sebagai bahan baku pakan karena mudah didapat dan mengandung nutrisi yang baik. Adanya kandungan serat yang tinggi pada Lemna minor sehingga sulit untuk dicerna dan memerlukan proses fermentasi. Penelitian ini bertujuan untuk mengetahui pemanfaatan pakan tepung Lemna minor fermentasi terhadap pertumbuhan ikan bawal. Metode Rancangan Acak Lengkap (RAL) dengan 4 perlakuan dan 3 ulangan, terdiri dari A tanpa tepung Lemna minor fermentasi, B tepung Lemna minor fermentasi 10%, C tepung Lemna minor fermentasi 20% dan D tepung Lemna minor fermentasi 30%. Data yang diamati yaitu jumlah konsumsi pakan (JKP), efisiensi pemanfaatan pakan (EPP), Laju pertumbuhan relatif (RGR) dan sintasan. Hasil menunjukkan bahwa perlakuan C (tepung Lemna minor fermentasi 20%) mampu menghasilkan rata-rata JKP sebesar 287,33 g, EPP sebesar 0,052%, RGR sebesar 0,090%/hari dan SR sebesar 100%Feed is an important factor in intensive fish aquaculture activities. Use Lemna minor as a feed raw material because it is easily available and contains good nutrition. The composition of high fiber in Lemna makes it difficult to digest and requires a fermentation process. This study aims to learn how to use Lemna fermentation flour on the growth of pomfret. Method used was completely randomiza design with 4 treatments and 3 replications, consisting of A without Lemna flour fermented, B Lemna flour fermented 10%, C Lemna flour 20% fermentation and D Lemna flour 30% fermentation. Interesting data are the amount of feed consumption, increased feed efficiency (EPP), relative growth rate (RGR) and survival rate. The results showed that the treatment of C (Lemna minor flour fermentation of 20%) was able to produce an average JKP of 287.33 g, EPP of 0.052%, RGR of 0.090%/day and SR of 100%
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".