Regeneration features of some verieties of Rosa L. genus representatives in vitro
Bibliographic record
Abstract
Работа посвящена усовершенствованию методики культивирования in vitro сортов роз из различных садовых групп. Показана возможность получения асептической культуры представителей рода Rosa L. при использовании гипохлорита натрия в концентрации 5% при экспозиции 7-9 мин. Подобран оптимальный минеральный состав питательной среды, установлено влияние углеводного состава питательных сред на рост и развитие регенерантов. У большинства исследуемых генотипов независимо от принадлежности к садовой группе наибольший коэффициент размножения был получен при культивировании на питательной среде MS, содержащей 6-BAP (0,5 мг/л). Для предотвращения фенольной экссудации в питательную среду добавляли аскорбиновую кислоту (100 мг/л). Замена в питательной среде сахарозы на глюкозу (3%) оказала положительное влияние на регенерацию микропобегов. Наиболее восприимчивым к источнику углевода сортом оказался канадский шраб Hope for Humanity. Выявлены особенности длительности субкультивирований на коэффициент размножения роз. Максимальный коэффициент размножения (9,5±0,3) и положительная динамика роста были характерны для сорта Hope for Humanity. The work is devoted to the improvement of in vitro cultivation technique of rose varieties from different garden groups. The optimal sterilization result was achieved with the use of sodium hypochlorite at a 5% concentration and exposure for 7-9 min. The optimal mineral composition of the nutrient medium was chosen, the carbohydrate composition eff ect of the nutrient medium on the growth and development of regenerants was established. In the majority of the studied genotypes, irrespective of their belonging to the garden group, the highest multiplication factor was obtained on MS medium containing 6-BAP (0,5 mg/l). Ascorbic acid (100 mg/l) was added to the nutrient medium to prevent phenolic exudation. Substitution of sucrose for glucose in the nutrient medium (3%) had a positive eff ect on the microshoots regeneration. The most susceptible to the carbohydrate source variety was the Canadian scrub Hope for Humanity. The features of the subcultures duration on the roses multiplication factor are revealed. Variety Hope for Humanity were characterized by the maximum multiplication factor (9,5 ± 0.3) and positive growth dynamics.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".