Assessment of genetic diversity in chinese hulless barley accessions for qualitative traits
Bibliographic record
Abstract
Cultivated barley (Hordeum vulgare L.) has been proven to be an economically important model plant and having large genetic diversity among the species. The effective exploitation of qualitative characters in barley can be measured by its genetic diversity and interrelationship. This study aims to determine the assessment of genetic diversity in Chinese hulless barley accessions for qualitative traits. Presently, in this study, the genetic diversity of 208 Chinese hulless barley from different Provinces of China, 111 genotypes were from the Tibet plateau, 30 Sichuan, 2 USA, 1 Canada, 12 Gansu, 51 Qinghai, 1 Yunnan was investigated; collected. Almost all the qualitative traits including crude protein, fiber, starch, neutral detergent fiber, and acid detergent fiber exhibited significantly high variability (p≤0.0001) among the cultivars. The data were analyzed using Statistics 8.1. In this study, significantly high variation was observed between starch content and neutral detergent fiber (23.64% and 11.54%). However, the highest diversity is based on the magnitude of the coefficient of variation exhibited in crude protein (13.82%), starch (12.87%), and fiber (12.17%). There was a significantly positive correlation between fiber, acid detergent fiber, and neutral detergent fiber except for starch content with crude protein and fiber that exhibited a significant negative correlation (r= -0.38*** and r= -0.92***). A large genetic diversity was observed through cluster analysis among all the 208 barley accessions, distance coefficient ranging between 0.28 and 75.86. The histogram revealed that frequency distributions of 208 different genotypes of hulless barley crop with all five different characters, crude protein, fiber, starch, neutral detergent fiber, and acid detergent fiber, showed normal distribution. It is concluded that this hulless barley study showed genetic diversity among the accessions and confirmed genetic diversity in various traits used.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".