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Record W2296570943 · doi:10.5376/ija.2015.05.0035

The Effect of Two Commercial and On-farm Made Aquafeeds on Growth and Survival Rate of <i>Oreochromis niloticus</i> (Nile Tilapia) Reared in Hapa

2016· article· en· W2296570943 on OpenAlexvenueno aff
M. C. Rodney, G. M. Confred

Bibliographic record

VenueInternational Journal of Aquaculture · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsOreochromisNile tilapiaFisheryBiologyTilapiaAnimal scienceFish <Actinopterygii>Growth rateZoology

Abstract

fetched live from OpenAlex

An experiment was conducted for 12 weeks to determine the effect of two commercial and on-farm made aqua feeds on the growth and survival rate of Oreochromis niloticus reared in 2×4 hapas mounted in a concrete sided pond. A total of 90 fish with stocking rates of 15 fish (average wt 10.5g/fish) per hapa were used, replicated twice. Feeds with 30% crude protein were administered to the fish twice per day at 5% of biomass determined at the previous sampling. Growth of fish was monitored fortnightly. Body weights and lengths were measured after 24 hours of fasting. Results indicated that total body length and specific growth rate increased with advancement of the experimental period, while weight gain/day and length values were almost similar in all the groups. However, all the tested growth parameters favoured those fed on Diet 3 compared to those given Diets 2 and 1 respectively.  A similar pattern was equally observed on final mean weights and survival rates, which ranged from: 29.2g and 93% for fish fed Diet 3, 22.9g and 87% for fish fed Diet 2 and 21.6g and 78% for fish given Diet 1, across all treatments. The highest mean daily and cumulative feed intake was observed in a treatment with mean growth of 29.2g/fish. This study has therefore, proved without doubt that Diet 3 had enhanced the overall growth performance and survival rate of Oreochromis niloticus .

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 score0.670
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.245
Teacher spread0.235 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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