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Production performance of sutchi catfish Pangasianodon hypophthalmus S. in restricted feeding regime: effects on gut, liver and meat quality

2011· article· en· W1597819987 on OpenAlexaff
A.K.M. Rohul Amin ., Md. Ashraful Islam, Md. Abdul Kader, Mahbuba Bulbul, Mostafa Ali Reza Hossain, M.E. Äzim

Bibliographic record

VenueAquaculture Research · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsCatfishBiologyAnimal scienceWeight gainBody weightFish <Actinopterygii>FisheryEndocrinology

Abstract

fetched live from OpenAlex

The experiment was carried out to evaluate the production performance of sutchi catfish, Pangasianodon hypophthalmus in restricted feeding regimes and their effects on gut and liver indices and body composition. Four feeding regimes were evaluated: fed to satiation twice per day (treatment daily feeding); 1-day food deprivation and 1-day feeding (treatment 1D-1F), 2-day deprivation and 2-day feeding (treatment 2D-2F) and 5-day deprivation and 5-day feeding (treatment 5D-5F). Fingerlings (mean weight 37 ± 3 g, mean total length 18 ± 2 cm) were stocked in replicated earthen ponds at a density of 25 000 ha−1 and cultured for 18 weeks during which commercial diet (33% crude protein) were delivered to apparent satiation on the feeding day according to the treatment. Results showed that the daily feeding and 1D-1F treatments resulted in similar individual weight gain (515–536 g) and net fish production (10 954–11 387 kg ha−1) as compared with treatment 2D-2F (weight gain 309 g; net production 6700 kg ha−1) or treatment 5D-5F (weight gain 251 g; net production 5651 kg ha−1). While fish body protein levels were not affected by food deprivation, lipid contents were lowest in treatments 2D-2F and 5D-5F. The study concluded that sutchi catfish could be cultured in alternate-day feeding regime without any negative effects on production and meat quality of fish resulting in a net profit of USD 2750 ha−1 pond.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.115
GPT teacher head0.314
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2011
Admission routes1
Has abstractyes

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