Enhancing color and bioactive retention during purple eggplant drying via sonicated pretreatments and optimized blanching
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Bibliographic record
Abstract
The retention of color, bioactive compounds, and texture during drying remains a challenge for the food processing industry. This study investigates the effects of sonication-assisted calcium chloride and ascorbic acid (1–2% solution) pretreatments combined with optimized blanching on the quality retention of dried purple eggplant. Different pretreatment methods, including sonication and blanching, were applied to eggplant slices followed by hot-air drying. Results showed that sonication significantly improved color retention, with sonicated samples maintaining higher lightness (L∗-value of 7.8 ± 0.4 for SSnB2) compared to non-sonicated controls (L∗-value of 6.6 ± 0.4 for SB2). The ΔE∗ (total color difference) for sonicated treatments was lower (7.5 ± 1.5 for SSnB2) compared to non-sonicated treatments (10.5 ± 1.2 for SB1), indicating superior color stability. Bioactive compound retention was enhanced, with sonicated samples exhibiting higher levels of polyphenols (12.8 ± 0.6 mg GAE/g DW), flavonoids (4.4 ± 0.5 mg QE/g DW), and anthocyanins (8.9 ± 0.6 mg C3G/g DW) compared to non-sonicated samples. DPPH scavenging activity was also higher in sonicated samples (75% ± 1.5 for SSnB2), compared to non-sonicated samples (75% ± 1.6 for SB2). Sensory evaluations showed that sonicated samples scored higher in color (7.8 ± 0.4), texture (7.5 ± 0.4), and overall acceptability (8.0 ± 0.3) compared to non-sonicated samples. These findings confirm that sonication, combined with blanching, significantly enhances the quality, bioactive retention, and consumer acceptability of dried purple eggplant, offering a promising, scalable technique for the food industry.
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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 | 0.000 | 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 it