Status and perspective of canola quality rapeseed-mustard cultivation in India : a review.
Bibliographic record
Abstract
Rapeseed-mustard (Brassica spp.) constitutes an important source of edible oil and meal. However, traditional rapeseed-mustard varieties accumulate high amount of erucic acid and glucosinolate in their seeds. These quantitatively inherited anti-nutritional factors drastically reduce the quality of rapeseed-mustard seed oil and meal for consumption purposes. Development of rapeseed-mustard varieties with low erucic acid and glucosinolate content, therefore, has been an important breeding objective worldwide. Breeding programmes for developing canola quality (<2% erucic acid in oil and <30 µmoles of glucosinolate/g of oil-free seed meal) rapeseed began in Canada as early as 1956. In India, however, the major efforts were made in the 1970’s with the launch of Indo-Swedish and Indo-Canadian collaborative projects (1979–94) to improve rapeseedmustard oil and meal quality and consequently varieties low in erucic acid and/or glucosinolate were developed. However, the existence of a significant yield gap between potential yield and the yield obtained in frontline demonstrations indicates the need for further refinement in technology packages for these varieties. In addition, it is also important to educate the masses about the health benefits of canola quality oil. This paper reviews the status and perspective of breeding and cultivation of canola quality rapeseed-mustard varieties, besides highlighting the impact of technology on profitability, strategies, policies, and future outlook for canola quality oil promotion in India.
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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 | 0.001 |
| 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 | 0.000 | 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".