Comprehensive Evaluation of Quality Traits of Hovenia acerba Germplasm Resources in Fujian Province
Why this work is in the frame
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Bibliographic record
Abstract
Hovenia acerba is a precious medicinal and edible tree. We assessed the genetic variation of H. acerba quality traits and conducted a comprehensive germplasm resource evaluation to provide a theoretical basis for breeding edible, medicinal, and edible/medicine combination varieties. We evaluated 31 H. acerba germplasm resources, including 12 infructescence and 8 fruit quality traits using correlation, principal component, and cluster analyses. The results showed that there were significant differences in all quality traits, with an average coefficient of variation greater than 0.20, an average genetic diversity greater than 1.80, and an average repeatability greater than 0.90. The average genetic variation and repeatability of quality traits in infructescence were higher than fruit. Infructescence K, Ca, Mn, Mg, and reducing sugar contents are important indicators in evaluating infructescence and fruit quality traits, and infructescence K, Mg, and reducing sugar contents are also quality innovation indices of H. acerba germplasms. Tannin, protein, and soluble sugar were the most suitable quality components for screening, followed by reducing sugar, starch, fat, total saponins, and total flavones. According to principal component factor scores and cluster analysis results, specific genotypes were selected as breeding materials for infructescence protein, tannin, flavone, reductive sugar, fruit tannin, fat, flavonoid, saponin, protein, and starch. The correlation analysis with environmental factors showed that the total amount of applied water could influence H. acerba infructescence and fruit quality. In conclusion, the variability of H. acerba germplasm resources was rich, and selection potential is large, which is beneficial to germplasm quality innovation and breeding.
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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 it