Successful Organic Production Practices in the Southern Cone
Bibliographic record
Abstract
The growth of demand of organic products has increased the interest of growers all around the World. To reach a sustainable organic production system, growers have to go through a long and difficult process. Eighty-one successful organic production systems in the Southern Cone of America were evaluated regarding management practices, such as disease control, soil fertility, and biodiversity management. The aim of the study was to determine associations between production techniques, farmer training, experience in organic agriculture, yields obtained, and the contribution of organic production to the profitability of farmers. A multivariate analysis was performed to characterize the variability between systems, correlate the management variables and explain economic sustainability. The economic sustainability of farmers was highly correlated with self-production of fungicides and insecticides, use of permitted commercial fertilizers, organic matter application, the use of natural enemies, commercially permitted fungicides and insecticides and the implementation of preventive practices for disease management. Pest monitoring correlated significantly with farmer training and sustainable practices implementation. Farmer’s perception on the importance of crop diversity in organic production correlated with the importance of external inputs independence, green manure, cover crop, and the experience of farmers in organic production. Farmers who implemented more management practices had yield losses below 20% of total production and a gross margin of organic farming of more than 1.5 times the minimum wage of the country than farmers that implemented few or no management practices.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".