Comparative analysis of quality and nutritional traits from <i>Lonicera caerulea</i> (Honeyberry) cultivars and other berries grown in Scotland
Bibliographic record
Abstract
Abstract Lonicera caeruleabrix is a perennial shrub native to North America, Europe and Asia. It produces dark blue berries known as honeyberries or haskap berries which are produced commercially in several territories including Canada, Japan, Russia and Poland. Plants are suited to UK environments, but it is yet to be widely commercially developed in the UK. In the present work, quality and nutritional traits of six honeyberry cultivars grown in Scotland were compared with other commonly grown berry fruits (strawberry, raspberry, blueberry, blackberry, blackcurrant) to aid the identification of environmentally stable, high‐quality honeyberry cultivars suitable for UK cultivation. Differences were observed in fruit quality variables (soluble solids, titratable acidity and Brix/acid ratios) between honeyberry cultivars. Three of six cultivars examined exhibited notable variation in soluble solids dependent on harvest year with ‘Aurora’ and ‘Strawberry Sensation’ having consistently high oBrix values. Titratable acidity exhibited cultivar differences and there was limited variation over harvest years. ‘Aurora’ exhibited consistently high oBrix/titratable acidity ratio reflected by high glucose and fructose content. Honeyberry fruit had good nutritional profile relative to other soft fruits with higher polyphenol and anthocyanin content than strawberry, blueberry, blackberry and raspberry, manifested in greater antioxidant capacity. The major anthocyanins in aqueous honeyberry fruit extracts were cyanidin, pelargonidin and peonidin glycosides. These findings indicate that L. caerulea represents a crop suitable for UK cultivation capable of producing high quality fruit with a valuable nutritional profile relative to other soft fruits. Cultivars exhibit significant differences in fruit quality and nutritional profile as well as harvest consistency and growers should consider this when establishing new plantations.
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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 | 0.000 | 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".