Correlation and Cluster Analysis of Agronomic Characters of 115 Waxy Corn Varieties
Bibliographic record
Abstract
In order to provide basis for high-yield and high-efficiency cultivation and selection and utilization of variety resources of waxy corn, nine agronomic traits of 115 waxy corn varieties were analyzed, and cluster analysis of 115 waxy corn varieties was conducted here. The results showed that ten pairs of agronomic traits showed extremely significant correlation meanwhile six pairs exhibited significant correlation. The genetic diversity analysis showed that the genetic variation of the tested materials was rich, the genetic basis was wide, the coefficient of variation of bald tip length (399.91%) was highest, followed by ear height (15.96%) and rows per ear (10.94%). The genetic diversity index of plant height (2.069) was highest, followed by ear height (2.063) and ear yield (2.053). 115 waxy corn varieties were further clustered into eight groups at distance of 55 by Euclidean distance and the furthest neighbor method. Among them, overall characteristics of group Ⅱ was fine, such as high yield, short growth period, low plant height and ear height and moderate corncob. The group Ⅵ has the highest yield, the largest ear type, the longest growth period and the highest plant. The growth period of group Ⅶ is the shortest, the yield is the lowest, and other characters are also in the lowest position.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".