Infrared Radiation Favorably Influences the Quality Characteristics of Key Lime Juice
Bibliographic record
Abstract
The effect of infrared radiation (IR) on the physicochemical characteristics, pectin methylesterase activity (PME), hydroxymethylfurfural (HMF) content, microbiological activity, color, and sensory aspects on black lime juice was studied. IR was compared to conventional thermal heating (CTH) in batch infrared extraction pasteurizer, designed to allow both infrared and conventional heating. IR resulted in a reduction in pH and Brix values and a mild increase in titratable acidity, as compared to CTH and control. After 60 days at 5 °C, the ascorbic acid percentage was decreased by 24.90%, 29.75%, and 58.31% in the control, IR and CTH, respectively. The total amount of phenols in juice treated with IR was higher as compared to CTH and control, while there was a significant decrease in the antioxidant activity. The statistical analysis reflected significantly low (p < 0.05) activity of PME for IR samples as compared to CTH and control. The amount of Hydroxymethylfurfural (HMF) in all juice samples steadily increased during the storage at 5 °C in 60 days. The microbial content of control was 3.85 log cfu/mL after 60 days at 5 °C, while it was 2.1 log cfu/mL for IR which reflected a significant difference between the IR, CTH, and control samples. Additionally, color and sensory analysis of IR treated sample when compared to control, reflected similar attributes. Overall, IR was found to be an excellent substitute for the preservation of black lime juice as a rapid pasteurization technique with less heat exposure; wherein the nutrition and health benefits of the juice could be maintained for a minimum period of 60 days.
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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 | 0.001 |
| 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 | 0.001 | 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".