Breeding black oats: scientiometric analysis, hybridation, segregant advance and seed dormance
Bibliographic record
Abstract
Black oat (Avena strigosa S.) is a winter cereal used for animal feed, ground cover, forage production, silage and hay. However, black oat presents high heterogeneity in its crops, despite its numerous advantages, due to the low amount of research on the species, especially regarding production, chemical composition and seed dormancy. Thus, the objective of the present work was to verify the generation, advancement of segregants and dormancy of black oat seeds obtained from mutant strains. The project was conducted at the Universidade Tecnológica Federal do Paraná, Campus Dois Vizinhos, next to the Experimental Station, at the Teaching and Research Unit of Annual Cultures and at the Didactic Laboratory of Seed Analysis. First, a scientometric review was carried out on the study of the species through the search for data on the Web of Sciense. Then, using lines obtained from an induced mutation in seeds of the IAPAR 61 cultivar, F4 generation, the advancement of segregating lines and hybridization with commercial materials was carried out. For this, crossing blocks were organized in a greenhouse and in the field. From these hybridizations, seeds were obtained and their multiplication was carried out to advance the generation. In the laboratory, tests were carried out to evaluate the physiological quality of the seeds obtained through the mutant lines, to verify the overcoming of dormancy. The results of the analysis of publications related to the genetic improvement of oats indicated a trend of growth in the number of publications, over the years and in the number of citations. The countries with the highest number of publications are the United States and Canada. The two areas with the highest number of publications were “Agriculture” and “Plant Science”. In addition, it was verified that the artificial hybridization of black oat requires an environment with controlled temperature and humidity, for a higher settling index of the crosses. After carrying out all the steps, it was possible to reach the end of the project with seeds in the F2 generation, from the crosses UPFAxP444 and BRSxUPFA. And, seeds in the F3 generation, from the IAPARxP253 cross. The germination test, soon after harvest, showed efficiency to obtain genetic gain on the dormancy character, evidenced by black oat seeds. Showing slight differences regarding dormancy overcoming, between commercial cultivars and mutated lines.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".