Striped catfish farming in the Mekong Delta, Vietnam: a tumultuous path to a global success
Bibliographic record
Abstract
Abstract The striped catfish (Pangasianodon hypophthalmus) (Sauvage), also referred to as tra catfish or sutchi catfish, farming sector is an icon of aquaculture development in Vietnam and globally. Over a decade it has developed from a humble backyard operation to one that currently accounts for the production of over one million tonnes, employing over 180 000 rural poor, and generating an export income exceeding US$ 1.4 billion (2010). It accounts for the highest average production, ranging from 200 to 400 t ha−1 crop, ever recorded for the primary production sector. The system is integrated and incorporates seed production, fry to fingerling rearing and grow‐out, and is concentrated in a few provinces in the Mekong Delta (8°33′–10°55′N, 104°30′–106°50′E), along two branches of the Mekong River. In essence, perhaps, the initial trade restrictions on catfish exports to the USA provided the impetus and then the associated developments from 2002 to 2005 of the sector to a great extent in seeking new markets. The explosion of tra catfish farming has resulted in many competitive sectors challenging this ‘tra catfish’ invasion into a globalized market. These confrontations still exist with many instances of attempts to discredit the sector and discourage international consumers. However, the Vietnamese catfish sector is resilient and has managed to withstand such pressures and continues to thrive. This paper reviews the development of catfish farming in the Mekong Delta, its current status and what is required to sustain it as a major food source and livelihood provider.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".