Development of a Scalable Extraction Process for Anthocyanins of Haskap Berry (Lonicera caerulea)
Bibliographic record
Abstract
Haskap (Lonicera caerulea) berry is rich in anthocyanins, particularly cyanidin-3-O-glucoside (C3G). In this investigation, a response surface methodology was applied to optimize the anhydrous ethanol-based extraction parameters to obtain the maximum yield of anthocyanins from haskap berry and to compare the recovery of anthocyanins from different extraction methods. The central composite design was employed to study the effect of three independent variables (XA = ultrasonic bath power, XB = extraction temperature, and XC = extraction time) which were found to significantly affect the response variable total anthocyanin content (TAC) and fit to the second-order polynomial model. The optimum process parameters of XA = 536 W, XB = 62.3 °C, and XC = 63.5 min provided a predicted TAC of 16.5 mg C3G equivalence (C3GE)/g dry weight (DW), which was experimentally validated with 16.1 mg of C3GE/g DW. The optimized ultrasonication-assisted extraction process using anhydrous ethanol was also effective in recovering quercetin glycosides, catechin, procyanidin B2, and iridoids, as determined by ultra-pressure liquid chromatography–mass spectrometry. Though the anthocyanin recovery was the highest (17.6 mg of C3GE/g DW) when a deep eutectic solvent consisting of citric acid and D-(+)-maltose was used, this solvent system has limitations when preparing dehydrated extracts for industrial applications. This study concludes that the effective extraction of anthocyanins and other phytochemicals from haskap berries can be performed using food-grade anhydrous ethanol.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 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".