Al-Amoudi, Rami H.Taylan, OsmanKutlu, GözdeMuslu Can, AslıSağdıç, OsmanDertli, EnesYılmaz, Mustafa Tahsin2023-11-302023-11-3020190308-81461873-7072https://hdl.handle.net/11363/6583https://doi.org/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.eninfo:eu-repo/semantics/openAccessMedlar fruitPectin extraction yieldRSM and ANFIS modelingMolecular, thermal and rheological characterizationArticle27165066210.1016/j.foodchem.2018.07.211302367282-s2.0-85051051781Q1WOS:000444967800082Q1