Description of Four Dual-Purpose River Buffalo (Bubalus bubalis) Farms in Tropical Wetlands in Mexico. Part 1: Social Aspects, Herd Distribution, Feeding, Reproductive, and Genetic Management
Bibliographic record
Abstract
This article characterizes four dual-purpose river buffalo farms (DPBPS) in south-southeastern Mexico. The objectives were to obtain a broader profile of this system and capture values related to buffalo breeding in that area. The study identified a group of producers with high levels of education (17 ± 1.15 years) and years of experience in agricultural systems (28.75 ± 10.81), especially with buffaloes (9 ± 1.83 years). Land tenure is private, and the average surface area of ranches is 428.75 ± 245.57 hectares, located mainly (92%) in flatlands and floodplains with an average number of animals per hectare 2.03 ± 0.69 AU/h. The area has various vegetable strata (grasses, bushes, trees). Feeding is based on the consumption of vegetable species like Camalote grass (Paspalum fasciculatum), West Indian Azuche grass (Hymenachne amplexicaulis), and Aleman grass (Echinochloa polystachya), complemented with minerals. Production units (PU) 2 and 3 add a low proportion of balanced feed. The average number of animals per PU is 611 ± 50. Dams and calves represent the largest proportions in the herds. The main breed raised in these buffalo production systems is Buffalypso (58% ± 21%), followed by Italian Mediterranean (24% ± 5%) and Murrah (10% ± 14%). The data collected show that the reproduction methods most often utilized, in order of frequency, are fixed-time artificial insemination (FTAI), direct mounting (DM), and estrus-detected artificial insemination (EDAI). Proportions are 61% ± 18%, 24% ± 25% and 14% ± 17%, respectively. The DPBPS studied are distinguished by the presence of owners and managers with high levels of education, extensive experience in agricultural systems, and the capacity and willingness to implement new technologies that permit continuous improvement. However, their experience in buffalo production is still limited, so there is ample room for improvement.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".