Bibliographic record
Abstract
Although potato ( Solanum tuberosum L.) tuber yellow flesh per se is known to be controlled by a single gene, the intensity of yellow flesh varies widely in Solanum L. species. Many diploid species have very intense yellow flesh, as compared to the commercial tetraploid yellow-flesh cultivar `Yukon Gold'. Inheritance of yellow-flesh intensity at the diploid level was investigated in a hybrid population of S. phureja ssp. phureja (Juz. & Buk.) -S. stenotomum ssp. stenotomum (Juz. & Buk.) (PHU-STN). Six randomly chosen male parents were crossed to five randomly chosen female parents in a Design II mating scheme. In 1993, ≈12 progeny (clones) from each of the 30 families were planted in a randomized complete block design with two replications in Presque Isle, Maine, and evaluated for tuber yellow-flesh intensity as measured by a reflectance colorimeter. Twenty-five tubers from each plot were scored using the YI E-313 yellow intensity scale. An average YI E-313 score was obtained for each plot. Narrow-sense heritability on a plot mean basis was estimated as 0.99 with a SE of 0.65 to 0.72. There were significant differences among clones within a family. Results suggest that rapid progress can be made in breeding for intense yellow flesh in this diploid population. Clones from this population that produce 2n gametes represent an important source of germplasm for enhancing the intensity of the yellow-flesh trait in tetraploid potatoes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".