Synergistic effect of microwave heating and thermosonication on the physicochemical and nutritional quality of muskmelon and sugarcane juice blend
Bibliographic record
Abstract
Melons (Cucumis melo L.) are highly popular due to its delicate and delightful flavor in the worldwide. However, the flavor of the melon juice was easily affected by thermal treatments and unpleasant cooking smell during production process. Sugarcane (Saccharum officinarum) juice is a proven nutritious beverage with high levels of antioxidants, polyphenols, and other beneficial nutrients. Due to its low sugar content, combined with sugarcane, muskmelon-sugarcane blend juice gives an appealing and exotic drink. The research was planned to evaluate the effect of thermo-sonication (20 kHz, 70% amplitude, 5, 10 and 15 min) and microwave (90 °C, 400 W, 120 sec) on physicochemical parameters including pH, titratable acidity, total soluble solids (TSS), total phenolic contents (TPC), total flavonoid contents (TFC) and antioxidant capacity of muskmelon and sugarcane juice blend, during storage of 90 days at refrigeration (4±1 °C). The statistical results showed that synergism of sonication and microwave treatments had a significant (p ≤ 0.05) influence on pH, TSS, titratable acidity, TPC, TFC and antioxidant capacity. T3 (15 min of sonication and 120 s of microwave) showed the maximum TSS (12.00±0.40 °B), pH (5.07±0.02), TPC (484.33±10.41 mg GAE/100 mL), TFC (261.73±11.32 mg CE/100 mL), and antioxidant activity (381.62±17.72 µg AAE/100 mL), as compared to untreated samples. Thermosonication for 15 min caused maximum retention of TPC, TFC and antioxidant capacity of blend juice during 90 days of storage, whereas in untreated samples these parameters were found highly decreased during storage. Thus, sonication and microwave can be recommended as an alternative to both conventional pasteurization processes and chemical preservatives.
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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) | 0.001 | 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".