Yield stability analysis of broadly adaptive triticale germplasm in southern and central Alberta, Canada, for industrial end-use suitability
Bibliographic record
Abstract
Goyal A., Beres, B. L., Randhawa, H. S., Navabi, A., Salmon, D. F. and Eudes, F. 2011. Yield stability analysis of broadly adaptive triticale germplasm in southern and central Alberta, Canada for industrial end-use suitability. Can. J. Plant Sci. 91: 125–135. Triticale (×Triticosecale Wittmack) is a cereal crop with high grain yield and biomass potential, which are traits desired in biorefinery processes that currently utilize wheat (Triticum aestivum). This study was conducted to evaluate the performance of introduced germplasm for its adaptability to selected Canadian prairie agroecosystems, and to benchmark both introduced and registered triticale lines against hard red spring wheat. To investigate the genotype×environment interaction effects on the performance of triticale genotypes, 30 genotypes (27 triticale; 3 hard red spring wheat) were grown in three environments for 3 yr (2005–2007) in southern and central Alberta, Canada. Variance due to genotypes, years, locations, and their interactions were studied by employing several stability analysis models. Site Regression Model (SREG) and GGE biplot analysis were conducted to rank the relative yield performance of cultivars and to identify stable genotypes. Triticale consistently produced higher grain and biomass than hard red spring wheat, but some lines were high in pentosan content, produced low test weight, and possessed unacceptable growing degree day requirements. However, several of the introduction lines displayed superior trait performance and high stability. Five advanced to “C” level registration testing with one subsequently recommended for registration. The results provide evidence that some of the global triticale germplasm are well-suited to the production environments of the Canadian prairies, and that triticale has potential to be the ideal cereal platform for future technological and biorefinery end-use applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".