Associations of Local Wheat Varieties (Triticum Spp.) Grown in
Bibliographic record
Abstract
Wheat is the most important cereal crop in Ethiopia ranking third in terms of area after teff and maize and second in terms of production after maize. Six local wheat varieties commonly cultivated in South Gondar, one of the eleven zones found in Amhara region, were collected from the local farmers to study their variability and associations of yield and yield related traits using twelve agro-morphological traits. The studied genotypes were grown in main rain season of 2014/15 at Farta district in a complete randomized block design with three replications. Analysis of variance indicated the presence of highly significant difference among the studied genotypes which revealed the presence of high genetic variability of wheat in the study area. Highest yield was recorded from the local variety Ferno with 1957 kg/ha followed by Chekole (1588.33kg) and Canada Sendie (1580.7kg). Higher value of GCV and PCV were recorded in most of the studied traits indicating selection may be effective from these traits and phenotypic expression would be good indication of the genotypic potential. Broad sense heritability estimates were very high for most traits signifying the possibility of success in selection. Correlation study revealed that number of tillers per plant, number of seeds per plant and harvest index had positive and highly significant correlation with grain yield. The present investigation will guide in planning
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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) | 0.001 | 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".