Evaluation of grain yield, and quality characteristics of some bread wheat cultivars in different agro-ecological regions of Türkiye
Bibliographic record
Abstract
Climate change and recurrent droughts challenge wheat production and yield, necessitating careful selection and plant breeding research. "Value for Cultivation and Use" experiments are crucial for assessing genetic gains and providing information about potential pathways to alleviate production losses under specific environmental conditions. The goal of the study was to compare the grain yield and quality characteristics of 46 registered bread wheat cultivars in 5 out of 7 agro-ecological regions of Türkiye between 2016-2017 and 2017–2018. The registered wheat cultivars were also characterized in terms of high molecular weight glutenin subunits (HMW-GS) and the relationships between quality traits and band patterns. Genotype × environment interaction was found statistically significant ( p < 0.05) for grain yield and the stability of the cultivars as explained on biplot graphs. The Mediterranean and the Central Anatolian region had the highest and the lowest average grain yield of 8137 kg ha −1 and 4260 kg ha −1 respectively under the rainfed conditions. The average thousand kernel weight of the cultivars was 35.3–39.9 g, with test weight of 77.2–79.2 kg hL −1 , protein content of 13.4–14.7 %, Zeleny sedimentation of 39.2–53.3 mL, and alveograph energy value varied between 191.2-276.4 × 10 −4 J. The most common subunits in cultivars were 2∗ at Glu-A1 , 7 + 8 and 7 + 9 at Glu-B1 , and 5 + 10 at Glu-D1 . It is concluded that high-quality new varieties are developed by high-molecular-weight glutenin subunits oriented crosses and selections in Turkish wheat breeding programs.
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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 | 0.001 |
| 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) | 0.000 | 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 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".