Genetic Diversity of Blueberry Genotypes Estimated by Antioxidant Properties and Molecular Markers
Bibliographic record
Abstract
spp.) have gained much attention worldwide because of their potential health benefits and economic importance. Genetic diversity was estimated in blueberry hybrids, wild clones and cultivars by their antioxidant efficacy, total phenolic and flavonoid contents, and express sequence tag-simple sequence repeat (SSR) (EST-SSR), genomic (G)-SSR and express sequence tag-polymerase chain reaction (EST-PCR) markers. Wide diversity existed among the genotypes for antioxidant properties, with the highest variation for DPPH radical scavenging activity (20-fold), followed by the contents of total flavonoids (16-fold) and phenolics (3.8-fold). Although a group of 11 hybrids generated the maximum diversity for antioxidant activity (15-fold), wild clones collected from Quebec, Canada, had the maximum variation for total phenolic (2.8-fold) and flavonoid contents (6.9-fold). Extensive genetic diversity was evident from Shannon's index (0.34 for EST-SSRs, 0.29 for G-SSR, 0.26 for EST-PCR) and expected heterozygosity (0.23 for EST-SSR, 0.19 for G-SSR, 0.16 for EST-PCR). STRUCTURE analysis separated the genotypes into three groups, which were in agreement with principal coordinate and neighbour-joining analyses. Molecular variance suggested 19% variation among groups and 81% among genotypes within the groups. Clustering based on biochemical data and molecular analysis did not coincide, indicating a random distribution of loci in the blueberry genome, conferring antioxidant properties. However, the stepwise multiple regression analysis (SMRA) revealed that 17 EST-SSR, G-SSR and EST-PCR markers were associated with antioxidant properties. The study is valuable to breeding and germplasm conservation programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".