Spawning induction for Latin American fishes
Bibliographic record
Abstract
Abstract Aquaculture offers solutions to meet the growing global demand for fish, and reports from the UN‐FAO indicate that aquaculture production in Latin America (LA) has grown at rates above the world average in recent years. One of the major constraints in the diversification of LA aquaculture is the control of reproduction in several popular native fish species for which difficulties in captive propagation have not yet been sufficiently overcome. This article reviews the use of hormone treatments to promote reproduction in females of these native fish species. LA has played a key role in the history of development of hormone administration, including the first hormonally induced spawning. That contribution is included in a historical overview of the discovery of the major hormones used in fish culture. The review provides a summary of difficulties to propagate females of various native fishes and the effects of administering hormones to enhance reproduction. Induced spawning of certain freshwater species was mainly achieved with pituitary extracts or human chorionic gonadotropin (hCG), although gonadotropin‐releasing hormone analogues (GnRHa) treatments are being researched, and successful studies suggest that low doses may be more effective. Research on new and emerging aquaculture species has applied both gonadotropins (Gths) and GnRHa‐based treatments, and GnRHa treatments have shown potential for marine species. However, native marine species new to aquaculture have also been conditioned to spawn spontaneously without hormones. Finally, we proposed future lines of research to examine reproductive strategies and GnRHa‐based hormone treatments to improve reproductive control for economically important fish species of LA.
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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 | 0.001 | 0.001 |
| 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) | 0.006 | 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".