| Literature DB >> 30236728 |
Rami H Al-Amoudi1, Osman Taylan2, Gozde Kutlu3, Asli Muslu Can4, Osman Sagdic5, Enes Dertli6, Mustafa Tahsin Yilmaz7.
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 (89 °C, 4.83 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 (123 °C) and exothermic peaks (192 °C). Thermogravimetric analysis revealed three decomposition regions, 50-225 °C, 225-400 °C and 400-600 °C. Steady and dynamic shear analyses revealed that pectin had a pseudo-plastic behavior with storage (G') and loss (G″) modulus increasing with increment in frequency, indicating viscoelastic structure more predominantly elastic than viscous.Entities:
Keywords: Medlar fruit; Molecular, thermal and rheological characterization; Pectin extraction yield; RSM and ANFIS modeling
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Year: 2018 PMID: 30236728 DOI: 10.1016/j.foodchem.2018.07.211
Source DB: PubMed Journal: Food Chem ISSN: 0308-8146 Impact factor: 7.514