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Effects of Garlic (Alliumsativum) and chloramphenicol on growth performance, physiological parameters and survival of Nile tilapia (Oreochromis niloticus)

2006· article· en· W1964543478 on OpenAlexaff
A. M. Shalaby, Yassir Khattab, A. M. Abdel Rahman

Bibliographic record

Venue˜The œJournal of venomous animals and toxins including tropical diseases · 2006
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsAllium sativumOreochromisBiologyNile tilapiaChloramphenicolAnimal scienceFeed conversion ratioSativumAntibioticsBotanyBody weightFish <Actinopterygii>BiochemistryEndocrinologyFishery

Abstract

fetched live from OpenAlex

We studied and compared the effects of chloramphenicol antibiotic and garlic (Allium sativum), used as immunostimulants and growth promoters, on some physiological parameters, growth performance, survival rate, and bacteriological characteristics of Nile tilapia (Oreochromis niloticus). Fish (7±1g/fish) were assigned to eight treatments, with three replicates each. Treatment groups had a different level of Allium sativum (10, 20, 30, and 40g/kg diet) and chloramphenicol (15, 30, and 45mg/kg diet) added to their diets; the control group diet was free from garlic and antibiotic. Diets also contained 32% crude protein (CP) and were administered at a rate of 3% live body weight twice daily for 90 days. Results showed that the final weight and specific growth rate (SGR) of O. niloticus increased significantly with increasing levels of Allium sativum and chloramphenicol. The highest growth performance was verified with 30g Allium sativum / kg diet and 30mg chloramphenicol / kg diet. The lowest feed conversion ratio (FCR) was observed with 30g Allium sativum / kg diet and 30mg chloramphenicol / kg diet. There were significant differences in the protein efficiency ratio (PER) with all treatments, except with 45mg chloramphenicol / kg diet. No changes in the hepatosomatic index and survival rate were observed. Crude protein content in whole fish increased significantly in the group fed on 30g Allium sativum / kg diet, while total lipids decreased significantly in the same group. Ash of whole fish showed significantly high values with 30g Allium sativum and 15mg chloramphenicol / kg diet while the lowest value was observed in the control group. Blood parameters, erythrocyte count (RBC), and hemoglobin content in fish fed on diets containing 40g Allium sativum and all levels of chloramphenicol were significantly higher than in control. Significantly higher hematocrit values were seen with 30 and 45mg chloramphenicol / kg diet. There were no significant differences in the mean corpuscular volume (MCV) and mean corpuscular hemoglobin concentration (MCHC). Plasma glucose decreased significantly with increasing levels of Allium sativum but increased significantly with increasing levels of chloramphenicol. Total lipids were significantly reduced with diets containing 40g Allium sativum and 30mg chloramphenicol / kg diet, while total plasma protein content was significantly higher in fish fed on diets containing 10, 20, and 30g Allium sativum, and 30 and 45mg chloramphenicol / kg diet. Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) activities in plasma decreased significantly with increasing levels of Allium sativum and chloramphenicol. All Allium sativum and chloramphenicol levels decreased total bacteria and coliforms in water, muscles and intestine when compared to the control group. Treated groups had lower mortality rate than the control group during the challenge test. In conclusion, it can be suggested that adding 3% Allium sativum to fish diet can promote growth, reduce total bacteria, and improve fish health.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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 designObservational
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

Citations287
Published2006
Admission routes1
Has abstractyes

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