Physicochemical properties, structural characteristics, and rheological behavior of mango peel pectin with different degrees of esterification
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Bibliographic record
Abstract
• Purification reduced protein, ash, and impurities in mango peel pectin (MP). • De-esterified mango peel pectins (DEMPs) was prepared by alkaline method. • De-esterification enhanced solubility, water-holding capacity, dispersibility and surface texture of DEMPs. • Ca2+ improved elasticity and gelation properties of DEMPs. Raw mango peel pectin (RMP) was extracted from mango peel with a yield of 12%. The RMP was subsequently purified to obtain mango peel pectin (MP) and de-esterified to obtain de-esterified mango peel pectins (DEMPs) with degrees of esterification (66.26% - 33.67%). The moisture content (4.48% - 5.36%), ash content (3.31% - 4.57%), protein content (4.14% - 9.51%), total sugar content (35.74% - 36.84%), solubility, water-holding capacity (WHC) and colour of RMP, MP, and DEMPs were systematically analyzed. The content of galacturonic acid in all DEMPs samples was higher than 65% and above the commercial grade. Notably, the highly de-esterified sample (DEMP 4 ) demonstrated the lowest molecular weight (342.37 KDa), the smallest particle size (1278.67 nm ± 27.65 nm) and the highest zeta potential (-36.09 mV), indicating its strongest dispersibility and stability in solutions. Scanning electron microscopy showed that the DEMP 4 was highly porous, which exhibited superior solubility and WHC. Rheological analysis showed that although DEMP 4 had the lowest consistency coefficient (0.133 Pa·s n ), the addition of Ca 2+ enhanced its elasticity and gelation properties. These results demonstrated that de-esterification significantly improved the physicochemical properties, structural morphology, and rheological behavior of MP, and provided a theoretical basis for the development and utilization of mango peel pectin.
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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