Genetic variability in elite barley genotypes based on the agro-morphological characteristics evaluated under irrigated system
Bibliographic record
Abstract
ABSTRACT Recently, researches have shown that the Brazilian savannah has a great potential to supply the demand for barley grains. The purpose of this study was to assess the genetic variability in 39 elite barley (Hordeum vulgare L.) genotypes based on the agro-morphological traits of a crop irrigated in the savannah system. An irrigation experiment in the design of complete randomized block with four replicates was conducted at Federal District - Brazil. The evaluated traits were: distance from the last knot to the rachis, distance from the flag leaf to rachis, spike length, number of grains by ear, flag leaf area, plant height, silking, lodging, grain yield, thousand-seed weight, protein content and grain commercial classification. After using analysis of variance the means were used to estimate the genetic dissimilarity among all genotypes pairs based on the Mahalanobis’ generalized distance. Cluster analysis using genetic distance matrix was performed having Unweighted Pair Group Method using Arithmetic Means method (UPGMA) as the criteria. Highly significant differences were found among the genotypes for all traits evaluated. The high coefficient of genetic variation indicates the possibility of having genetic gains for all traits. The traits that most contributed to the variability were the flag leaf area and silking, while the protein content and lodging were the traits that contributed the least. Based on the cluster analysis, at least three major groups of similarity were found. There was a clustering trend of two and six-rowed materials. The most divergent genotypes were PFC 2005123, Antártica-1, Nandi and FM 404.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".