The impact of best practice health and husbandry interventions on smallholder cattle productivity in southern Cambodia
Bibliographic record
Abstract
Future food security has become a major global concern and is particularly important in the Greater Mekong Subregion where several countries have seen rapid urban economic development and increasing demand for red meat. In Cambodia, the majority of livestock producers are subsistence or semi-subsistence rural smallholder farmers using cattle as a source of protein, fertiliser, draught power, and asset storage. Potential income from smallholder cattle is limited by a range of factors that compromise productivity, including endemic diseases, poor nutrition, and lack of knowledge of husbandry techniques and marketing practices. To address the developing opportunities to improve rural incomes from cattle production in Cambodia, a 4-year longitudinal study was conducted to examine ‘best practice’ interventions that could improve productivity and profitability of cattle within smallholder farming systems. The study involved six villages from three provinces, with two villages in each of the provinces of Takeo, Kandal and Kampong Cham paired and designated as either high intervention (HI) or low intervention (LI). A best practice intervention program was introduced to the HI villages to develop the husbandry skills of farmers, including implementation of forage technology, disease prevention through vaccination for foot-and-mouth disease and haemorrhagic septicaemia, deworming, and education in nutrition, biosecurity, disease control, and marketing. Between April 2008 and February 2012, eight repeat-measures capturing data on animal health and production, including cattle weights used to evaluate the impact of interventions on average daily gains, were completed. Cattle in HI villages had significantly (P < 0.01) higher mean liveweight during the last three sampling periods, and average daily gains were 2.4 times higher than in cattle of the LI villages. This study provides evidence that best practice interventions resulted in improved cattle productivity, farmer knowledge and positive impacts on household income over time, offering a pathway that can address food security concerns and more rapidly alleviate rural poverty in the GMS.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".