Effects of genotype and environment on seed and forage yield in fenugreek (Trigonella foenum-graecum L.) grown in western Canada.
Bibliographic record
Abstract
Fenugreek is being developed as a forage legume crop in western Canada, as it has desirable agronomic and forage quality traits. The objective of the present study was to determine if genotype x environment interactions have an impact on seed and forage yield when plants are grown under the short growing season of western Canada. Two studies were conducted: one with up to 83 accessions grown under rain-fed and irrigated conditions at Lethbridge, Alberta for two years and the other had five selected genotypes grown under seven environments scattered over Alberta and British Columbia over five years. In the first study significant (P < 0.01) location and year effects were observed for forage yield and 1000 seed weight respectively, while for seed yield effect of year, genotype, year X location and year X genotype were significant (P < 0.01). In the second study significant (P < 0.01) genotype, environment and their interaction effects were observed for forage and seed yield. These studies indicate that improvement through phenotypic selection for forage and seed yield is possible but, will require use of multiple locations and years. Improvement in seed yield can be achieved through selection for less variable seed size and/or early maturity.
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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 | 0.000 | 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) | 0.000 | 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".