Features of studying of introduced soy samples (Glycine max. (L.) Merr.) in the conditions of irrigation of the south of Ukraine
Bibliographic record
Abstract
Goal. The study of introduced soybean samples to isolate genetic sources of the main biological and economically valuable traits for further use in the breeding process. Results and Discussion. The article highlights the results of research for 2016-2018. study of introduced soybean samples for a complex of economically valuable traits. The samples origin from Ukraine (17), Canada (.), Australia, France (2 each) and the USA (1 sample). According to the results of the research, the sources of valuable economic traits were identified: with very short growing season, seedlings-full ripeness (98 days) –Marysia (UKR), short (101 – 120 days) – 14 samples; yield excess in relation to the standard – 6 samples. Among the varieties studied in 2018 for ultra-ripeness and yield, the Samorodok and Zhemchuzhyna varieties were stood out. The level of relationships between the main elements of sample productivity has been established. Common to all varieties was the closest connection between the number of seeds per plant and productivity, which was within r = 0.76 – 0.97, exept Triada varietiy. A close correlation between productivity and the number of nodes (r = 0.91) was established for the Samorodok variety, between productivity and the diameter of the first interstice (r = 0.93) – for the Feieriia variety. The established level of links between the main elements of the productivity of samples, which are planned to be used later in the breeding work, for the development of a model of varieties. Conclusions. Attraction of new soybean samples to the collection, their study and application in the selection process is the way to create high-yielding, adapted to irrigated growing conditions, resistant to diseases and the occurrence of soybean varieties that meet the requirements of producers.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".