The adaptive potential of durum wheat varieties of Saratov breeding in the conditions of the Lower Volga region
Bibliographic record
Abstract
The objects of the study were plants of 14 varieties of durum wheat Triticum durum Desf. A structural analysis of the productivity elements of plants cultivated in the field in 2020, 2021 and 2023 was carried out. The varietal features of the formation of productivity elements of durum wheat varieties of Saratov breeding in different meteorological conditions are revealed. Based on the peculiarities of the formation of the main elements of ear productivity, varieties with a balanced type of morphogenetic systems have been identified. In 2020, the variety with a balanced type of morphogenetic systems in terms of ear productivity elements – the number of spikelets, the number of grains and their weight is the Luch 25 variety, in 2021 – Nikolasha and Zolotaya Volna. In the conditions of 2023, balanced varieties were not found for all elements of ear productivity – the number of cones, the number of grains and their weight. Balanced varieties were determined according to two productivity elements: Nikolasha and Zolotaya Volna varieties are balanced in terms of the number of spikelets and the weight of the grain, the Lilac variety is balanced in terms of the number of grains and the weight of the grain. The values of the breeding indices – Mexican, Canadian, and the index of linear ear density – were determined. A variety was identified in which the values of the breeding indices for the entire period of the study were unchanged – the Saratov 40 variety of the Mexican index. The Elizabethan variety among all 14 varieties is characterized by the minimum values of the linear density index of the ear for three years.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".