Short Communication: Haskap (Lonicera caerulea): A new berry crop with high antioxidant capacity
Bibliographic record
Abstract
Rupasinghe, H. P. V., Yu, L. J., Bhullar, K. S. and Bors, B. 2012. Short Communication: Haskap (Lonicera caerulea): A new berry crop with high antioxidant capacity. Can. J. Plant Sci. 92: 1311-1317. This study evaluated the antioxidant capacity and total phenolic content as well as total flavonoid content of three haskap (Lonicera caerulea) cultivars, Borealis, Indigo Gem and Tundra, grown in Saskatchewan in comparison with six other commercial fruits using ferric reducing antioxidant power (FRAP) assay, oxygen radical absorbance capacity (ORAC) assay, the 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical scavenging assay, the aluminum chloride colorimetric method and the Folin-Ciocalteu method, respectively. The results indicate that haskap berries, especially cv. Borealis possessed the highest antioxidant capacities and total phenolic contents, specifically total flavonoid among tested fruits, and could be used as a promising fruit source of natural antioxidants. The nutritional values of the fruits were also assessed using proximate analysis. Strawberry possessed the highest amount of most minerals and nutrients, whereas the nutritional values for the three haskap cultivars were average.
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 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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".