Growth Performance of Three Nile Tilapia (<i>Oreochromis niloticus</i> L., 1758) Populations in Pond System
Bibliographic record
Abstract
A 120 days study was conducted to evaluate the growth performances of juvenile Oreochromis niloticus from different lakes (Chamo, Tana and Hashengie) in pond culture system. Fingerlings of average weights 16.7, 15 and 16.9 g for O. niloticus from Lake Chamo, Lake Tana and Lake Hshengie, respectively were stocked at stocking density of 2 fish/m 2 with three replicates each. The treatment groups were fed formulated feed with 29% crude protein at 5% of their body weight per day. Final mean weight of Nile tilapia was highest ( p <0.05) for Lake Chamo (59.6 g) followed by Lake Hashengie (46 g) and Lake Tana (39.4). Daily growth rate (0.4 g per day), Specific growth rate (1.1% per day) and Food conversion ratio (2.5) of O. niloticus from Lake Chamo were significantly ( p <0.05) different from O. niloticus of Lake Tana and Lake Hashengie. On the other hand, O. niloticus from Lake Tana and Lake Hashengie had 0.2 g per day and 0.8% per day daily growth rate and specific growth rate, respectively. O. niloticus from Lake Hashengie was also significantly ( p <0.05) higher in its final mean weight (46 g) and mean weight gain (29.1 g) than O. niloticus from Lake Tana. On the other hand, there was no significant difference ( p <0.05) in the Specific Groth Rate and Food conversion ratio between O. niloticus of Lake Tana and Lake Hashengie. In conclusion, the result of the present study revealed that O. niloticus strain from Lake Chamo showed better growth performance compared to those from Lake Tana and Lake Hashengie. Based on the current result, we recommended O. niloticus strain from Lake Chamo can be considered for tilapia stocking and also for further strain selection programs.
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 | 0.000 |
| 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) | 0.001 | 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".