Effect of acidification on quality and shelf-life of carrot juice
Bibliographic record
Abstract
Yu, L. J. and Rupasinghe, H. P. V. 2012. Effect of acidification on quality and shelf-life of carrot juice. Can. J. Plant Sci. 92: 1113–1120. This study compared the effects of different acidification methods for processing carrot juice: blanching of carrot with 20 and 40 g L −1 of citric acid, 20 and 40 g L −1 of lactic acid and blending carrot juice with cranberry juice in 80:20 and 70:30 ratios. The quality was measured in terms of changes in pH, titratable acidity (TA), total soluble solids (TSS), turbidity, antioxidant capacity, beta-carotene content and total aerobic colony count (TAC) during a 21-d storage at 4°C. Water blanched carrot juice was selected as the control. During storage, the pH, TA, TSS and turbidity values were much more stable for all acidified juices than for water blanched juice. The highest value and stability of antioxidant capacity measured by ferric reducing antioxidant power (FRAP) belonged to a carrot-cranberry juice blend in a 70:30 ratio. The highest beta-carotene value belonged to 40 g L −1 lactic acid blanched juices. Carrot-cranberry juice blend in an 80:20 ratio gave the maximum stability for beta-carotene. All acidification methods prolonged the shelf-life of carrot juice in terms of TAC. Blanching with 40 g L −1 of lactic acid or citric acid provided 3–4 log reduction TAC and was among the most effective methods for extending the shelf-life of carrot juice.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".