Phenotypic characterization of a strawberry (<i>Fragaria</i> ×<i>ananassa</i> Duchesne ex Rosier) diversity collection
Bibliographic record
Abstract
Societal Impact statement To secure a stable, safe food supply, the future of humanity depends on the conservation and application of cultivated and wild plant diversity. Strawberries are globally important. They are widely produced and provide significant human health benefits. In 2019, annual world production was 14.5 MT (FAOSTAT, 2022). This report characterizes agricultural traits of diverse heritage strawberries. The gene pool of breeding programs has traditionally included a reliable but limited set of cultivars. The traits of lesser known heritage strawberry cultivars and selections examined by our study could be of value in expanding gene pools by tapping into existing cultivated genetic diversity. Summary Strawberries are a berry crop of global significance. We present a comprehensive evaluation of strawberry diversity through phenotyping 284 strawberry cultivars from the U.S. Department of Agriculture, National Clonal Germplasm Repository Corvallis, Oregon, USA. We assessed 284 cultivars in 2019 and 2020 for quantified variation across 16 traits, including phenology, plant morphology, and fruit quality traits at full ripeness. Through cluster analysis, we determined groups of accessions that had desirable traits, including quality fruits, earliest fruit ripening, or high numbers of daughter plant production. We observed that this strawberry diversity panel displayed a wide range of phenotypic variation that could prove useful for future strawberry improvement. ORUS 2427‐1, NW 90054‐37, and “Independence,” each developed by the Oregon USDA breeding program, displayed a combination of the highest fruit quality traits. “Independence” also had the longest runner length and the highest number of daughter plants. Two California cultivars, Oso Grande and Cuesta, and the Oregon cultivar Pinnacle had a short ripening time, on average 32 days between flowering and harvest, with the range for the study group of 25–41 days. Our data provide insight for breeders to expand gene pools, producers who choose cultivars for green‐wall production, or geneticists who need data to prepare genome‐wide association studies.
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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 | 0.000 | 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 | 0.001 | 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) | 0.003 | 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".