Effect of Low Tannin Sorghum Based Feed on Physical and Nutritional Quality of Layer Chicken Eggs
Bibliographic record
Abstract
This study was carried out to evaluate the effect of replacing maize with low tannin sorghum (LTS) in layer feed on the physical and nutritional quality of eggs of layers at peak egg production stage. One hundred and twenty, 30-weeks old hens were grouped into three blocks of forty birds per block and were subjected to three different diets: 100%Maize, 50%Maize50%LTS and 100%LTS for 8 weeks. Eggs were collected on the 4th and 8th week of feeding trial. The results showed that eggs had statistically similar weights, amounts of protein, fat, Vitamin E and Vitamin A. The colour of egg yolks increased in lightness and reduced in hue and Chroma significantly across all the dietary blocks with increase in LTS while cholesterol content decreased. The saturated fatty acid content in the albumin and yolk oil extract remained constant irrespective of the period of feeding or variation of Maize and LTS content. The Monounsaturated fatty acid content decreased significantly (P=0.0003) during the whole trial diet period. The Polyunsaturated fatty acid content remained constant for the albumin (P=0.4095) while the yolk showed an increase (P=0.1162) from the initial 15.82±0.57 g/100g on the 4th week to 24.05±7.25 g/100g on the 8th week for diets with 100%Maize. 50%M50%LTS increased from 14.59±0.16 to 21.48±4.19 g/100g and 100%LTS had its Polyunsaturated fatty acid content decline from 13.36±0.31 to 10.71±0.32g/100g. This study indicates that LTS can replace Maize as a source of energy in chicken feeds with no adverse effects on the quality of the eggs.
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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 | 0.000 | 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".