Total Phenolic Content and Antioxidant Capacity of Selected Canned Fruits
Bibliographic record
Abstract
Fruits are high in polyphenols which are compounds associated with the protection against diseases such as diabetes and cancer. However, food processing including canning can leads to the loss of polyphenol in the fruits. Thus, the aim of this study was to evaluate the total phenolic content (TPC) and antioxidant capacity of canned fruits commercially available in the local supermarkets in Malaysia. The TPC was determined by using Folin-Ciocalteu method while the antioxidant capacity was evaluated by using 2,2-diphenyl-1-picrylhydrazyl radical (DPPH assay) and Ferric Reducing Antioxidant Power (FRAP assay). Five types of different canned fruits with the total of 21 samples including longan, lychee, rambutan, pineapple and orange were selected for the analysis. The samples were analyzed in two forms which were, the homogenized (fruits and syrup) and syrup samples. Canned pineapples have the highest TPC for both homogenized (95.16±30.16 mg GAE/100 g) and syrup sample (108.62±33.88 mg GAE/100 g). For antioxidant capacity, canned pineapple also had the highest value for the homogenized sample (41.79±4.20 umol TE/100 g) while lychee was the highest (46.84±12.81 umol TE/100 g) for syrup sample assessed by DPPH assay. For FRAP assay, lychee was highest in antioxidant capacity for both homogenized sample (40.61±10.55 umol TE/100 g) and syrup sample (33.58±7.56 umol TE/100 g). A positive and significant (P < 0.001) correlation was found between TPC and antioxidant capacity (DPPH and FRAP). In conclusion, canned pineapple and lychee were the highest sources of polyphenol as compared to other types of canned fruits. Further investigation is warranted to determine the specific polyphenol present in the canned fruits.
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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 | 0.000 | 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".