Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7584023 | Food Chemistry | 2019 | 33 Pages |
Abstract
In this work, response surface methodology and adaptive neuro-fuzzy inference system approaches were used to predict and model effect of extraction conditions of pectin from medlar fruit (Mespilus germanica L.). The pectin extracted at optimized conditions (89â¯Â°C, 4.83â¯h and 4.2 pH) could be classified as high methoxyl pectin. Sugar composition analysis showed that pectin was mainly composed of D-galacturonic acid, L-arabinose, L-rhamnose, D-galactose and D-glucose. Fourier Transform Infrared Spectroscopy, RAMAN and nuclear magnetic resonance spectra confirmed molecular structure, revealing presence of D-galacturonic acid backbone. X-ray diffraction patterns revealed an amorphous structure. Differential scanning calorimetry showed endothermic (123â¯Â°C) and exothermic peaks (192â¯Â°C). Thermogravimetric analysis revealed three decomposition regions, 50-225â¯Â°C, 225-400â¯Â°C and 400-600â¯Â°C. Steady and dynamic shear analyses revealed that pectin had a pseudo-plastic behavior with storage (Gâ²) and loss (Gâ³) modulus increasing with increment in frequency, indicating viscoelastic structure more predominantly elastic than viscous.
Related Topics
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Authors
Rami H. Al-Amoudi, Osman Taylan, Gozde Kutlu, Asli Muslu Can, Osman Sagdic, Enes Dertli, Mustafa Tahsin Yilmaz,