Nutritional and Organoleptic Characterization of Two Quinoa (Chenopodium quinoa) Cultivars Grown in Quebec, Canada
Bibliographic record
Abstract
) cultivation and consumption have been increasing globally for its nutritional value and agricultural adaptability, with over 120 countries involved in its production. In Canada, quinoa is cultivated as a specialty crop to increase crop diversity and support agroresilience. This study is the first to examine quinoa cultivars grown under northern Quebec conditions and to provide a nutritional and sensory characterization of two Quebec (Canada) varieties (Sweet and Bitter) in comparison to the Bolivian reference cultivar, Royal White. Analyses included proximate composition, amino acids, fatty acids, phenolics, and anti-nutrients. Sensory evaluations involved hedonic and bitterness ranking tests. Bolivian cultivar had higher omega-3 content, while the Quebec cultivars showed favorable protein and lipid profiles, with better lipid health indexes. Protein quality was comparable between the Bolivian and Sweet cultivars. The overall flavor appreciation was similar among twice-brushed Bitter cultivar and Bolivian samples. The Bolivian sample received a better score for texture. Descriptive flavor data support the development of a quinoa flavor lexicon. Notably, total saponins content, commonly used as a bitterness indicator, did not consistently correlate with perceived bitterness, emphasizing the need for a standardized quantification method for cultivar selection and further investigation into other flavor-contributing compounds.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".