A comprehensive metabolomic-assisted investigation of bioactive phenolic and lipophilic compounds in underutilized Canadian wild berries
Bibliographic record
Abstract
Prairie berries are cold hardy fruits consumed by Canadians for their perceived health benefits. Phenolic compounds, fatty acids, phytosterols and terpenes are important bioactive molecules in berries. Assessment of the bioactive compounds is essential to identify their potential as a functional food. The objective of this study was to comprehensively examine the contents of phenolic compounds, fatty acids, phytosterols and terpenes content of fourteen different berries grown in prairies. The ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) method was developed and used for the comprehensive and simultaneous analysis of 66 phenolic compounds in fourteen different types of Canadian wild berries. Gas chromatography-mass spectrometry (GC-MS) was used to analyze the fatty acids, phytosterols and terpenes in the aforementioned berries. In vitro, lipid peroxidation was tested in all the selected wild berry types. Principal component analysis and analysis of variance were performed to identify the significance of the results. Wild grapes were rich in phenolic compounds such as resveratrol, while gooseberries were rich in isoquercetin and p-coumaric acid. Saskatoon berries were rich in chlorogenic acid. Rutin and chlorogenic acid were the most abundant phenolic compounds in chokecherry. Essential fatty acids such as linoleic and α-linolenic acids were found in wild grapes, buckthorn and Saskatoon berries. Predominant phytosterols and terpenes identified in Canadian wild berries included β-sitosterol, isofucosterol, phytol, and α-amyrin. The novel UHPLC-HRMS method for phenolic compounds and a GC-MS method for lipophilic compounds proved that the underutilized wild berries consist of unique and beneficial phenolic compounds, essential fatty acids, phytosterols and terpenes. As a source of these important bioactive compounds, these berries have the potential to function as antioxidants and antihypertensive agents. The information from this study will help in finding applications for underutilized prairie berries as potential sources of functional food in the neutraceutical and pharmaceutical industries.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".