Evaluation of genetic variability of wild hops (<i>Humulus lupulus</i> L.) in Canada and the Caucasus region by chemical and molecular methods
Bibliographic record
Abstract
Wild hops (Humulus lupulus L.) are potential new germplasms to expand the variability of genetic resources for hop breeding. We evaluated Canadian (62 plants) and Caucasian (58 plants) wild hops by their chemical characteristics and with molecular genetic analyses using sequence-tagged site and simple sequence repeat markers, in comparison with European (104 plants) and North American (27 plants) wild hops. The contents of alpha and beta acids varied from 0.36% to 5.11% and from 0.43% to 6.66% in Canadian wild hops, and from 0.85% to 3.65% and from 1.22% to 4.81% in Caucasian wild hops, respectively. The contents of cohumulone and colupulone distinctly differed between European and North American wild hops: the cohumulone level in alpha acids was in the range 46.1%-68.4% among North American wild hops and in the range 13.6%-30.6% among European wild hops. The high content of myrcene and the low contents of humulene, farnesene, and selinenes were typical for wild hops from Canada, in contrast to wild hops from the Caucasus region. We compared the chemical characteristics with molecular genetic data. Chemical characteristics differentiated wild hops into North American and Eurasian groups. Molecular genetic analysis was able to separate Caucasian wild hops from European wild hops. We proved a hop phylogeny by means of wide molecular analysis.
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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 | 0.002 | 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) | 0.000 | 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 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".