Growth Rate and Body Size Mapping of Male Buffaloes during the Fattening Phase
Bibliographic record
Abstract
Background: Buffalo is an animal that really likes water. Generally, buffalo like to soak in muddy waters and swamps around the cage. This behavior appears because buffalo have very few sweat glands. Therefore, if one wants to develop buffalo farming, he/she should look for special habitats or existing buffalo breeding centers. Differences in growth rates are caused by physiological factors and functional demands. Growth in animal body size usually follows an exponential function, with the growth rate varying from one body size to another. An animal's body size that functions earlier will grow faster with a greater growth rate than an animal that functions later. Differences in the growth rate of animal body size are also influenced by the constituent components of these body parts. Body parts composed primarily of bone will develop earlier than those composed of muscle or fat. During fattening, the body size of male buffaloes will have a different growth rate, where this difference indicates the potential for body size. The body size of a buffalo with a high growth rate has relatively large growth potential, while those with a small growth rate have small growth potential, or the body part has stopped growing because it has reached its maximum point. The purpose of this study is to determine the body size growth rate of male buffaloes, which have high potential during fattening. Mapping the body size of male buffaloes during fattening aims to help breeders determine at what age the buffaloes start to be fattened and slaughtered for meat production purposes so that they are economically quite profitable. Methodology: Data was collected using a saturated sampling technique, in which the livestock taken were all buffaloes kept by the Sumber Sari Livestock Group in Kalianget village, Seririt District, Buleleng Regency, Bali, which met the requirements in terms of their health and physical condition. The data obtained were analyzed using the power model regression analysis to determine the growth rate of the body size of the buffaloes. To map the growth rate, Biplot analysis was carried out with a Promax rotation of 90, as the variable is the estimated body size of the buffaloes based on the equation of the power regression line, and the object is the age of the male buffaloes. Conclusion: The results showed that the fastest growth rate or the greatest potential was chest width, followed by hip width, chest depth, body length, chest circumference, and shoulder height. At the same time, the slowest part of the lowest potential was the height of the hips. The results of mapping the body size growth rate of male buffalo aged 11-74 months with biplot charts showed that their growth potential was still quite high. However, there was a tendency for male buffalo over 30 months to have a slower growth rate in body size than those under 30 months.
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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) | 0.002 | 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".