The effect of the environment on the grain colour and quality of commercially grown Canada hard white spring wheat,<i>Triticum aestivum</i>L. ‘Snowbird’
Bibliographic record
Abstract
Lukow, O. M., Adams, K., Suchy, J., DePauw, R. M. and Humphreys, G. 2013. The effect of the environment on the grain colour and quality of commercially grown Canada hard white spring wheat, Triticum aestivum L. ‘Snowbird’. Can. J. Plant Sci. 93: 1–11. One of the main advantages of hard white wheat is its lighter grain colour, which can produce visually appealing lighter-coloured end-products. However, grain colour variation can be a concern due to a lack of consistency. This study was carried out to determine the effect of the environment on commercially grown hard white wheat grain colour and wheat grading. More than 1100 samples of the cultivar Snowbird were collected from elevators across western Canada during the 2003 to 2007 crop years. Grain and wholemeal colours were recorded using the CIE L* a* b* scale. Samples were analyzed for grain properties including dimensions, hardness and protein content. Variation in grain colour was mostly attributed to annual fluctuations in climatic conditions (71–79%) and agro-climates (13–18%). Grain ranged in colour from white and bright to dark grey-red. Grain brightness was very highly correlated with grain yellowness. Grain a* and b* were inversely related to grade indicating that higher quality grain was redder and more yellow than lower grades. Warmer and drier environments showed reduced grain yields but produced on average better quality grain with higher protein content.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".