Evaluation of winter-tolerant oat lines for yield and yield components
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Bibliographic record
Abstract
Food use of oat grain has recently begun to increase mainly in breakfast cereals, snack products, or in bran form. Oat is the most winter tender of the winter cereals. There are not a lot of succes in improvement of winter oats (Veisz et all. 1996). Due to the lack of reliable winter cultivars, the area of oat production in Turkey is relatively small. Therefore, it is necessary to convey winter-tolerant cultivars to farmers. In this study, one hundred and thirty five oat lines from the Quaker Nursery were sown at Urkutlu experiment location (in Burdur province, Turkey) outside the University campus (37o 19' N, 30o 17' E and 850 m from sea level) in the last week of October 1999 and 2001. Twenty three genotypes were selected from this nursery for winter tolerance in the second year of the experiment. The experimental material was sown in a randomised complete blocks design with three replications in a farmers field at Kýzýlkaya village (in Burdur province, Turkey) in the fourth week of February 2003 because of the heavy rainfalls, which restrict earlier sowing. Grain yield (g), 1000-grain weight (g), plant height (cm), biomass (g), days to heading and harvest index (%) were recorded in 23 genotypes selected for winter tolerance and a local variety. Data obtained were analyzed using the MINITAB software. There were statistically significant differences among genotypes selected for winter tolerance for grain yield, 1000-grain weight, plant height, biomass and days to heading. Some lines in Quaker nursery showed high agronomic performance over the local check. In case farmers are provided winter tolerant oat varieties for semi dry conditions for fall sowing, it may be expected that oat production will improve. Veisz, O. B., Bedo, Z., Lang, L., Szunics, L. and Stehli, L. 1996. V. International Oat Conference & VII. International Barley Genetics Symposium, Saskatoon, Canada, July-August 29-06 1996.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 it