Characterization of Bioactive Compounds in Northern Amazon Fruits
Bibliographic record
Abstract
Fruits and vegetables are highly appreciated because they are constituted by active phytochemicals with functional properties for the organism acting with modulating pharmacological effect. Given the pharmacological properties of this type of food, in this work were studied the concentrations of vitamin C, total carotenoids and reducing and non-reducing sugars of nine fruits developed in the northern Amazon region: Abiu, Acerola, Araçá, Bacuparí, Biribá, Camu-camu, Fruta-do-conde, Graviola and Tapereba. The concentration of vitamin C, the highest concentration in the shell of Camu-camu 2521.51 mg 100 g-1 and for acerola with 1731.4 mg 100 g-1 stand out. The highest concentrations of total carotenoids were also found for the Camu-camu, with concentrations of 0.67 mg 100 g-1 the shell of Camu-camu and 0.57 mg 100 g-1 for the pulp. The concentrations of sugars are higher for the pulps, with the highest concentrations for the pulp of the Fruta-do-conde with 16.31 g 100 g-1 followed by the pulp of the Graviola, both of the Annonaceae family with a concentration of 15.61 g 100 g-1. The different bioactive molecules were correlated for the different parts of the fruit, by means of multivariate analysis techniques (PCA and HCA), where 90.1% of the cases were explained for the pulps, 65.4% for the shell of the fruits and finally the 88.5% of the cases for the seeds. Given the results obtained in this work, these fruits can be used for the preparation of foods with functional interest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".