Determinants of Crossbreeding Practices by Cattle Farmers in South Benin, West Africa: Implications for the Sustainable Use of the Indigenous Lagune Cattle Population
Bibliographic record
Abstract
While it is widely acknowledged that the small-sized West African Shorthorn taurine Lagune cattle is being increasingly crossbred with and replaced by large-sized zebus, little is known about the factors that influence farmers’ crossbreeding decisions and selection practices. But this information is necessary for the development of strategies towards a rationale use and conservation of this unique African genetic resource. To fill this knowledge gap, we conducted, between September and November 2016, a questionnaire survey in the belt of this breed in South Benin. One hundred seventy-three cattle farms were surveyed. The binomial logistic regression approach was used to predict the likelihood of a Lagune cattle farmer to be willing to introduce zebus in his herd. The herds were composed of either Lagune only (82.1%), zebu only (4.0%), crossbred Lagune x zebu (1.2%), Lagune and zebu (9.2%) or Lagune and crossbred Lagune x zebu (3.5%). The low productivity of the Lagune cattle and the market demand for large-sized animals were the main farmers’ motivations for crossbreeding. Farmers raising large herds of Lagune cattle under control mating system were more likely to adopt crossbreeding. The risk of dilution of the Lagune breed could be reduced by increasing awareness among farmers, improving their technical skills in herd management and empowering them to develop legal institutions, by-laws and collective actions for sustainable breed management. Farmers who have already adopted crossbreeding should be provided with appropriate services and technical assistance, whereas breed conservation initiatives should mainly focus on small purebred herds kept under control mating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".