Effects of genotype and environment on the breadmaking quality of Canada Western Extra Strong Red Spring wheat cultivars
Bibliographic record
Abstract
In 1995, The Canadian Wheat Board established a collaborative working group of researchers from the Canadian Grain Commission's Grain Research Laboratory, Agriculture and Agri-Food Canada's Cereal Research Centre, and the University of Manitoba's Department of Food Science to investigate the breadmaking quality of the CWES wheat class. The specific issues this group was to investigate the uniformity of cultivars within the class in terms of breadmaking quality, and the consistency of quality for each cultivar grown in different locations. In 1995, the CWES class comprised three registered cultivars, Glenlea (first licensed in 1972 as a Utility class wheat), Bluesky and Wildcat (both registered in l987). Descriptions of these three cultivars were published by Evans et al. (L972) and Clarke et al. (1994a and 1994b, respectively). In addition, the wheat line PT754, which had undergone three years of testing in the Parkland Wheat Co-operative Trial by the prairie Registration Recommending Committee for Grain, was expected to be registered. In 1996, PT754 received a three-year interim registration, and was given the name Laser, thus bringing the total number of cultivars in the cwES class to four. Buyers of CWES wheat expressed concern that the class was no longer performing as well as when Glenlea was the only cultivar within the class for various products, e.g. bread. It was suggested that one or more of the cultivars Bluesky, Wildcat and Laser possessed weaker dough properties compared to those of the established standard CWES wheat cultivar Glenlea. Further, it was not known whether the apparent differences in quality were genetic and/or environmental in nature. This thesis project was undertaken in 1997 to comprehensively examine these questions. CWES wheats are characteristically unique in dough physical properties and protein composition. The flour can be distinguished by very long dough mixing times and relatively high contents of so-called "unextractable" glutenin protein, i.e. glutenin of relatively high average molecular size. This wheat class was founded upon the cultivar Glenlea that was developed at the U of M and was originally licensed into the Canada Western Utility wheat class. In 1993, CWES became the new name of the wheat class to better reflect the functional quality of the cultivars within this class. Commercial interest in CWES wheat increased significantly in the 1990s as its gluten attributes became more widely known and studied. These attributes relate to its use as a blending wheat in a variety of applications where there is a need for increased gluten strength in the dough (Bushuk 1980). For example, to carry weaker and less costly wheats in white pan bread production, as a vital gluten replacer in whole wheat, high-fibre and hearth breads, and in frozen doughs to mitigate the damaging effects of extended freezing and thawing. This study evaluated a sample set of 36 flours derived from six different wheat genotypes- four CWES, and two CWRS- grown in six different locations in Saskatchewan and Alberta. The CWES genotypes were Glenlea, Bluesky, Wildcat, and Laser. The CWRS genotypes were Katepwa and Laura. The three objectives of the study were as follows: * To quantify genotypic differences in dough protein composition, dough mixing properties, and bread baking potential across locations * To similarly quantify the magnitude of location effects * To establish which tests (protein composition, mixing, and/or backing) best characterize the unique properties of CWES wheat.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".