INTERNATIONAL COLLABORATION OF VIR AS AN IMPORTANT FACTOR OF REPLENISHING THE COLLECTION OF GRAIN LEGUME GENETIC RESOURCES
Bibliographic record
Abstract
The percentage of foreign material in the VIR collection of grain legumes varies from 42% (vetch) to 96-97% (cowpea, chickpea). For most crops, this indicator is between 75-86%. It depends either on the agroclimatic needs of the crops reflecting the areas of their cultivation and growth over the world or on their centers of origin as well as on the scale of their production and breeding in different countries. The main way of receiving new crop material from abroad is VIR's international cooperation which was initiated by N. I. Vavilov. Since then, interaction of the Institute with foreign partners has not lost its relevance and traditions. The sources of foreign material are international collecting expeditions, the exchange of scientists, requests for germplasm to international genebanks, national botanical gardens, breeding organizations, specialized research institutions and universities. The most important tool for obtaining foreign material was and still is the exchange of germplasm samples. This article provides an overview of the ways by which foreign material has entered the VIR collection of grain legumes over the last 20 years. During this period, the total of 7552 foreign accessions has been added to the collection, which makes 16% of its overall volume. The main sources of such material are international genebanks and national centers working with plant genetic resources. For the collections containing crop wild relatives (CWR), botanical gardens remain important suppliers of material. The main partner countries that have participated in mutually beneficial partnerships and germplasm exchange with VIR are Syria, China, the USA, Canada, Ukraine, Belarus, France, and Australia. International expeditions have been and remain a fruitful source of local varieties and CWR. Of undoubted interest, along with the modern and local varieties coming from abroad, are wild species of such crops as soybean, chickpea and lentil whose areas of distribution lie beyond the borders of this country. Such species are promising for introgressive breeding. The study of new foreign accessions within VIR's network made it possible to identify sources of economically valuable traits for the main trends of crop breeding.
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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 | 0.011 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".