Pectin from Citrus Canning Wastewater as Potential Fat Replacer in Ice Cream
Bibliographic record
Abstract
Pectin had been recovered from canning wastewater produced by chemical treatment of segment membrane during preparation of canned citrus in our previous research. The purpose of this study was to characterize the extracted pectin from canning wastewater, and to evaluate its application as a fat alternative to replace fat in ice cream. The monosaccharide composition and rheological properties of the pectin were determined. The influences of fat reduction and pectin addition on the physicochemical, rheological and sensory properties of low-fat ice cream were determined. The rheological results showed that pectin solutions were typical pseudoplastic fluids. The addition of pectin in ice cream can cause an increase in viscosity, overrun, and hardness, and a decrease in meltdown of the ice cream. When 0.72% pectin (w/w) is incorporated into ice cream, a prototype product of ice cream with 45% lower fat content compared to the control was made. Results indicated that their qualities such as appearance, flavor, and taste were not significantly different. The low-fat ice cream had higher smoothness scores and lower mouth-coating scores. Hence, pectin extracted from citrus canning wastewater can be potentially used as fat replacer in ice cream, which benefits both the environment and the food industry.
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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 | 0.000 | 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 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".