Environmental effects on fruit composition of cloudberry/bakeapple (Rubus chamaemorus L.) grown in southern Labrador, Canada
Bibliographic record
Abstract
Li, J., Percival, D., Hoyle, J., Yue, J., White, J., Head, K. and Pruski, K. 2015. Environmental effects on fruit composition of cloudberry/bakeapple (Rubus chamaemorus L.) grown in southern Labrador, Canada. Can. J. Plant Sci. 95: 1167-1175. The composition of fruit collected from three fields located near Lanse'au Clair, Red Bay and Cartwright in southern Labrador, Canada, was analyzed over the 2011 and 2012 growing seasons. Soluble solids, titratable acidity, total phenolics, total anthocyanins, chlorogenic acid, caffeic acid, quercetin-3-glucoside, cyanidin-3-glucoside and ellagic acid were determined after each harvest using standard laboratory procedures. Temperature, precipitation, wind and other environmental factors affected growth and deposition of nutrients in harvested fruit. Soluble solids content (TSS), titratable acidity (TA), total anthocyanin, chlorogenic acid, cyanidin, total phenolic compounds and total anthocyanins of cloudberry fruit were significantly (P<0.05) affected by the combination of the growing season and the location. The TSS, TA and total phenolics were higher in fruits from Cartwright (most northern location) in both seasons compared with the other two locations. The HPLC analysis of compounds showed the ellagic acid and quercetin 3-o-β-D-glucoside contents of fruits were significantly affected by the location and the growing season (higher in 2012 compared with 2011), while contents of chlorogenic acid, caffeic acids, and cyanidin-3-o-β-glucoside were not. To our knowledge this is the most comprehensive study of fruit composition of bakeapple conducted in southern Labrador, Canada.
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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 | 0.001 | 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".