Oat mega-environments and test-locations in Quebec
Bibliographic record
Abstract
Yan, W., Pageau, D., Frégeau-Reid, J., Lajeunesse, J., Goulet, J., Durand, J. and Marois, D. 2011. Oat mega-environments and test-locations in Quebec. Can. J. Plant Sci. 91: 643-649. The Quebec agricultural regions have traditionally been divided into three zones. Zone 1 includes the small, southern most regions in the Montreal plain, zone 3 includes the large, discontinuous northern regions spreading from the west to the east of the province, and zone 2 includes areas between zone 1 and zone 3. Genotypic main effect (G) plus genotype-by-environment interaction (GGE) biplot analysis of the yield data from the Quebec Oat Registration and Recommendation trials during 2006-2009 revealed that the Quebec oat-growing regions can be divided into two distinct mega-environments: the small zone 1 region and the much larger zone 2 plus zone 3 regions. Due to the large genotype by mega-environment interactions, cultivar evaluation and recommendation must be conducted specifically to each mega-environment. However, a zone 3 test location, La Pocatière, consistently behaved like a zone 1 location in terms of cultivar ranking. Therefore, La Pocatière cannot be used to represent the zone 3 region, and cultivar recommendation for the regions represented by this location should be based on data from this location plus the zone 1 locations. In addition, climatic and soil data were examined in an attempt to explain this observation. The methodology adopted in this work may be of value to similar studies for other crops and in other regions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".