Restoring Rice Paddies and Rice Agro-Ecosystem Services Through a Participatory Seed Conservation and Exchange Programme
Bibliographic record
Abstract
Until the 1960s, Kerala, the southernmost state of India, was home to a rich diversity of cultivated traditional rice, expanding to more than 200 varieties. However, with subsequent agricultural intensification and a descending trend in paddy cultivation, the area witnessed a decline in this diversity, and cultivation had become limited to only a few selected varieties. This chapter discusses the efforts of the M S Swaminathan Research Foundation, MSSRF, in addressing the risks related to erosion of rice crop genetic diversity and the resultant weakened capacity of smallholder rice farming families to adapt to extreme weather variations. Interventions also addressed the growing issue of undernutrition amongst rice farmers of tribal communities in the Wayanad district of Kerala, South India. The intervention adopted a rice ecosystem-based adaptation approach (REbA) that combined ecological, social, and economic principles and integrated crop and soil biodiversity in the rice production system. The major component of the REbA was the Rice Seed Village (RSV) that fostered conservation, cultivation, and consumption of specialty rice varieties and protection of the ecosystem services of the rice agro-ecosystem. RSVs consisted of smallholder farm families engaged in on-farm conservation through cultivation of both improved traditional and modern paddy varieties. The major activity of RSVs was seed quality improvement for traditional rice diversity through training, seed exchange networks, and facilitating linkages amongst stakeholders. Training on yield enhancement, quality seed production, and successful seed storage, along with sensitisation in rice value chain development, enabled the RSV families to raise their income, recover or retain many of the traditional varieties, revive cultivation of rice-allied crops like legumes, bananas and leafy vegetables, and maintain several wild plant genetic resources associated with the rice agro-ecosystem. Through the RSVs, strong seed exchange networks were formed that facilitated linkages amongst various stakeholders in paddy seed conservation, cultivation, marketing, and consumption, primarily the farmers, marketing channels, agricultural officers, consumers, and other stakeholders. RSVs helped to build assets for food and nutrition security, improve resilience, and reduce climate and market-related shocks and vulnerabilities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".