Phenotypic and genetic characterization of an Avena sativa L. germplasm collection of diverse origin: implications for food-oat breeding in Chile
Bibliographic record
Abstract
Oats are known for their nutritional value and also for their beneficial properties on human health, such as the reduction of cholesterol levels and risk of coronary heart disease; they are an important export product for Chile. During the last decade (2010-2022) over 90% of the oat cultivated area in Chile has been covered with Avena sativa L. cv. Supernova INIA. This lack of genetic diversity in a context of climate change could limit the long-term possibility of growing oats in Chile. The present study is a phenotypic and genetic analysis of 132 oat cultivars and pure lines of diverse origin that can be considered as potential breeding material. The germplasm was evaluated for 28 traits and analyzed with 14 SSR markers. The effects of genotypes on phenotype were significant over all traits (P ≤ 0.05). Most traits exhibited moderate to high broad-sense heritability with exceptions such as yield (H2 = 0.27) and hulls staining (H2 = 0.32). Significant undesirable correlations between traits were generally of small biological importance, which is auspicious for achieving breeding objectives. Some of the heritability data and correlations provided here have not been previously reported. The overall phenotypic diversity was high (H’ = 0.68 ± 0.18). The germplasm was grouped into three phenotypic clusters, differing in their qualities for breeding. Twenty-six genotypes outperforming Supernova INIA were identified for breeding of conventional food-oats. The genetic diversity of the germplasm was moderate on average (He = 0.58 ± 0.03), varying between 0.32 (AM22) and 0.77 (AME178). Two genetic subpopulations supported by the Structure algorithm exhibited a genetic distance of 0.24, showing low divergence of the germplasm. The diversity and phenotypic values found in this collection of oat genotypes are promising with respect to obtaining genetic gain in the short term in breeding programs. However, the similar genetic diversity, higher phenotypic diversity, and better phenotypic performance of the germplasm created in Chile compared to foreign germplasm suggest that germplasm harboring new genetic diversity will be key to favor yield and quality in new oat cultivars in the long term.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".