Gum Karaya: A Potential Supplement Fish Meal (SFM) For Enhancing Growth And Health In Labeo Rohita (Rohu Fish)
Bibliographic record
Abstract
Gum Karaya, is a natural plant-derived polysaccharide used as a mixed blend supplementary fish meal (SFM) in 7 different concentration (1%-7%) with the natural fish meal to enhance the growth and health of Labeo rohita (Rohu fish). At the end of the feeding period (21 days) growth performance, body composition, hematological and biochemical parameters of rohu fish were evaluated. The findings reveal a remarkable dose-dependent enhancement in growth performance, exemplified by specific growth rate (SGR), Relative Growth Rate (RGR), and daily weight gain, concomitant with a reduction in feed conversion ratio (FCR). Optimal growth, with a peak RGR of 34.05%, is observed at 5% Gum Karaya supplementation. Fish fed with 5% Gum Karaya exhibited the highest SGR, indicating an optimal supplementation level for maximum growth. Hematological assessments demonstrate a positive dose-dependent response in red blood cell count (RBC), white blood cell count (WBC), and hemoglobin (Hb) levels, which indicate stimulation of immune responses. Moreover, Gum Karaya supplementation led to favorable alterations in the biochemical constituents of fish muscles, including an increase in protein content and a decrease in lipid content. KSFM modulates various physiochemical parameters, including glucose, total protein, cholesterol, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels, suggesting enhanced metabolic health. While biological health indices, such as the Gonadosomatic Index (GSI), show promise for improving reproductive health, Hepatosomatic Index (HSI) and Spleenosomatic Index (SSI) exhibit minor variations. This experiment is first time report on the multifaceted benefits of Gum Karaya in enhancing the physiological and metabolic aspects of Labeo rohita, with significant implications for aquaculture practices and selective breeding strategies
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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 | 0.000 |
| 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) | 0.001 | 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".