Characterisation of chokeberry and saskatoon berry fruits
Bibliographic record
Abstract
Diploma thesis deals with the characterization of chokeberry (Aronia melanocarpa) and saskatoon berry (Amelanchier alnifolia) fruits. The theoretical part focuses on the botanical classification, chemical composition, curative effects and the use of chokeberry and saskatoon berry in the food industry. Further, the attention is also devoted to a review of methods for the determination of important antioxidants, specialized on the determination of polyphenols, anthocyanins, ascorbic acid and total antioxidant activity. The experimental part of the work deals with the determination of selected parameters in different varieties of chokeberry and serviceberry, harvested in 2012 and 2013 using spectroscopic and chromatographic techniques with an emphasis on effect of solvent (50% ethanol, destilled water, DMSO). Specifically total content of polyphenols and anthocyanins, color characteristics using the CIE L*a*b* system and the ability of the sample to reduce the iron are determined using the UV-VIS-NIR spectroscopy. Further ascorbic acid concentration in individual extracts is quantified by High performance liquid chromatography coupled with a diode array detector and the total antioxidant activity is characterized by electron paramagnetic resonance involving •DPPH and ABTS•+ assays.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".