Analysis of seed chain and its implication in rapeseed-mustard (Brassica spp.) production in India
Why this work is in the frame
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Bibliographic record
Abstract
India is ranked third after Canada and China sharing about 11.0% of the global rapeseed-mustard production (72.41 mt) and 24.7% and 29.4% in terms of area and production, respectively, of oilseeds in India during 2018-19. Of the projected demand of 82-101 m t of oilseeds by 2030, contribution of rapeseed-mustard is projected at 16.4-20.5 m t, considering its share of 20%-25% in production. Near doubling the production of rapeseed-mustard from its current production of 9.26 m t within 10 years is a daunting challenge necessitating multi-pronged strategy. First and foremost approach would be to bridge the exploitable yield reservoir (EP II) of 57.2% in rapeseed-mustard. Seed is the technological carrier and facilitates the realization of potential of variety and crop management technologies. The present paper reviews global scenario ofrapeseed-mustard production and Indian scenario ofseed sector, seed systems, seed production chain, seed status and its implication in production ofrapeseed-mustard. India has a very robust seed systemcomprising both public sector institutions and private seed companies; this systemacts as a driver of growth in agriculture. Of the three seed systems prevalent in India, viz., formal, informal and integrated, formal system wherein guiding principles are to maintain varietal identity, purity and to produce seed of optimal physical, physiological and phyto-sanitary qualityis predominant. Seed chain ofrapeseed-mustard during 2019-20 was maintained with 55 varieties comprising 35 of Indian mustard, 11 of toria, 5 of yellow sarson and 2 each of gobhi sarson and taramira. Varietal mismatches in the breeder seed production was only 5.6% during 2019-20. Breeder seed production was higher by two to three folds than the indents during the last 11 years (2009-10 to 2019-20). During the last 10 years there has been a surge in seed requirement from 2.20 lakh q to 2.64 lakh q. Seed availability during this period was always higher by 2.3%-27.8% than the requirement, except during 2016-17 when a marginal deficit (0.8%) was observed. The seed replacement rate (SRR) is above the threshold level (33% for self- and 50% for cross-pollinated crops) and varietal replacement rate (VRR) is also high as contribution of old and obsolete varieties (released up to 1993) has substantially reduced from 49.4% (2014-15) to 1.7% (2019-20) for Indian mustard; 81.1% (2014-15) to 25.1% (2019-20) for toria and 64.0% (2014-15) to 18.9% (2019-20) for yellow sarson. Increased availability of seed, adequate SRR with high VRR are some of the contributing factors for enhanced yield from 1143 kg/ha to 1511 kg/ha during 2008-09 to 2018-19 in rapeseed-mustard. This paper also highlights some of the issues and strategies for quality breeder seed production.
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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 | 0.006 |
| 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 it