Effect of pre-sowing γ-irradiation of sea buckthorn seeds on the content and fatty acid composition of total lipids in the seeds of the first plant generation
Bibliographic record
Abstract
Absolute content and FA-composition of sea buckthorn ( Hippophaë rhamnoides L.) seed lipids were studied. The seeds of cvs. Vitaminnaya and Zyryanka belonging to the Siberian climatype and also the seeds of the first generation (M 1 ) plants grown from the seeds subjected to pre-sowing γ-irradiation ( 60 Co) at the doses of 50 and 100 Gy (cv. Vitaminnaya) and 100, 250, and 500 Gy (cv. Zyryanka) were used in analyses. In all treatments, irradiation resulted in the reduced seed weight in M 1 plants, which was sharper in cv. Vitaminnaya. In contrast, oil content declined strongly in cv. Zyryanka seeds, especially after irradiation with 500 Gy, whereas this index remained almost unchanged in cv. Vitaminnaya. Control and treated plants were close by their FA qualitative composition and by the total content of unsaturated FAs (88–90%). Pre-sowing seed irradiation resulted in the rise of the unsaturation index of lipids and linolenic acid concentration; at lower irradiation doses, this rise was more pronounced. With the increase of irradiation dose, the content of linolenic acid reduced in both cultivars, whereas the content of linoleic acid increased. As distinct from cv. Vitaminnaya, in cv. Zyryanka irradiation increased the content of linoleate and reduction in the level of oleate. The conclusion is that pre-sowing γ-irradiation of sea buckthorn seeds could affect substantially on the basic quantitative indices characterizing seeds of M 1 plants. The range and direction of induced changes depend on both the dose of irradiation and cultivar genotype.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".