Millets for Food and Nutrition Security in India: Determinants and Policy Implications
Bibliographic record
Abstract
Background: Food security has been a target in India since its independence; the primary aim of food security is to ensure enough staple food for the entire population. Although substantial progress was made through the adoption of green revolution (GR) technologies and implementation of the food public distribution system (PDS), desirable food and nutrition security, as defined by the food and agriculture organization (FAO), is far from being realized. This paper scrutinized the potential contribution of millets in achieving food and nutrition security in India. Methods: The present study was conducted based on the secondary data obtained from FAO Corporate Statistical Database and published literature on food and nutrition security. The impact of the GR technologies and the PDS on food and nutrition security was examined using 58 years of acreage, production, and yield of rice, wheat, and millet, as well as comprehensive information on relevant issues including climate. Results: Both GR technologies and PDS unduly favored two principal crops, namely rice and wheat, marginalizing all other crops cultivated for thousands of years to meet the food and nutrition requirement of mostly developing countries including India. Millets constitute one such neglected group of crops in India, which have tremendous potential for contributing to food and nutrition security. Conclusions: Millets are to be included in the PDS alongside rice and wheat so that they receive an appropriate Minimum Price Support. Appropriate implementation of relevant regulations, continued research and development, and adequate support for cultivation and marketing of millets are necessary in this regard.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".