Population genomics of Vaccinium vitis-idaea L. and links to environmental conditions, total phenolics, and antioxidant capacity in Newfoundland and Southern Labrador
Bibliographic record
Abstract
Lingonberry, also called Partridgeberry in Newfoundland (Vaccinium vitis-idaea L.) is \nnative to Eurasia, Greenland, Iceland and North America. Partridgeberry is well known for \nits nutritional benefits, making it increasingly important for cultivation. While cultivation in \nEurope is widespread, it is only in developmental stages in North America. Knowledge of \nthe genetic structure of wild populations, and its relationship with environmental \nconditions, phenolic content (TPC), and antioxidant capacity (AC) is necessary for the \nselection of desirable genotypes, but this knowledge is incomplete globally. Therefore, the \ngenetic structure of 56 wild partridgeberry populations distributed across nine ecoregions \nof Newfoundland and Southern Labrador in Canada were investigated in the present \nexperimental study. This thesis also evaluated the effects of environmental factors on the \nTPC and AC of partridgeberry leaves. By testing different variable levels, significantly \nhigher TPC on leaves was found in individuals growing under elevated levels of surface \nwater pH (>7). Significantly higher AC was found in individuals from the Central \nNewfoundland, North Shore Forest, and Maritime Barrens ecoregions and in individuals \nwith low surface water pH (<6.6). AC was significantly lower for individuals with low \nsensitivity to acid rain (alkalinity of >200 μeq/L). Temperature and precipitation had no \neffect on TPC or AC. Contrary to expectations, no correlation between TPC and AC was \nfound. Individuals formed three genetic groups, which showed some geographic structure \naccording to ecoregion and temperature. Individuals collected in areas with the coldest \nmean annual and summer temperatures were clustered within one genetic group. As \nexpected, geographically closer individuals were also genetically closer and contained \nsimilar quantities of TPC. However, I did not find any correlation between genetic distance \nand TPC or AC, suggesting that these desired biochemical traits for plant breeding \nprograms are very much influenced by the environment. Future research should focus on \nthe environmental effects I found over a longer period of time, under controlled field or \ngreenhouse conditions, and the expression of genes in the phenyl-propanoid metabolism.
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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".