Evaluation and differentiation of garlic cultivars growing in Québec using phenotypic and genotypic traits
Bibliographic record
Abstract
Garlic (Allium sativum L.) production in Québec represents only 10% of the local market. Local production is restrained in part by a lack of knowledge on the phenotypic and genotypic stability of different cultivars grown locally. The goals of this project were to study the phenotypic variation in a set of garlic cultivars grown in different environments in Québec, differentiate them using DNA polymorphic patterns, and compare the morphological classification to the genetic one. A two-year field trial was conducted in Lac Saint-Jean and Montréal areas with 36 garlic cultivars of different types. In the first part of this study, cultivars were characterized morphologically by measuring the size, shape and arrangement of leaves, pseudostems, scapes, bulbils, bulbs and cloves. Although differences between cultivar types were identified, it was not possible to obtain a unique set of morphological characteristics specific to each cultivar. Also, yield and yield related characteristics varied widely between environments and within environments. In the second part of this study, 35 microsatellite regions were screened and 21 markers have finally been used to differentiate our cultivars. Overall, garlic types were different genetically, but the cultivars within a type were generally identical resulting in redundancy for 61% of our set of cultivars. Since garlic is propagated by clones, it is likely duplicates, but some cultivars like ‘Rose de Lautrec’ showed major morphological differences with other cultivars found to be genetically identical. We also found that the cultivars, previously reported to show more than one phenotype had also more than one genotype. A more thorough investigation using advanced genotyping technique is needed to get better insight in the genetic identity of cultivars studied herein
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".