Phenotypic Diversity and Ornamental Evaluation Between Introduced and Domestically Bred Crabapple Germplasm
Bibliographic record
Abstract
Crabapples (Malus spp.) are important ornamental trees in northern temperate regions. However, their phenotypic diversity and ornamental values remain poorly characterized, due to a lack of systematic comparison between introduced and domestically bred cultivars/lines. This knowledge gap limits the effective utilization of their germplasm. In this study, 111 floral, foliar, fruit, and tree architectural traits were measured across 93 introduced (North American) and 118 domestically bred (Chinese) cultivars/lines. Comparative analyses using Shannon–Wiener (H′) and Pielou’s evenness (J) indices revealed that floral traits exhibited the highest phenotypic diversity, followed by fruits, leaves, and tree architecture. Among these, 51 key traits (e.g., budlet color, leaf area, and fruit shape) showed above-average diversity, while others (e.g., flower type, leaf cracking, and exocarp color) were less uniform, indicating rare phenotypes. Domestically bred cultivars showed significant improvements in flower color and type, mature leaf shape and size, and fruit characteristics, including novel budlet, bud and petal colors, increased stamen numbers, semi-double or double flowers, and diverse fruit colors. A multi-dimensional ornamental evaluation (Analytic Hierarchy Process) identified 26 superior genotypes and several organ-specific selections for flower- (26), fruit- (25), foliage- (21), and tree architecture-viewing (14) purposes. These findings provide a theoretical basis for updating Malus distinctness, uniformity, and stability (DUS) guidelines, targeted breeding, and strategic landscape applications, highlighting the potential of both introduced and domestic germplasm for ornamental improvement.
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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 | 0.001 | 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 | 0.001 | 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".