Characterization of chemical, molecular, thermal and rheological properties of medlar pectin extracted at optimum conditions as determined by Box-Behnken and ANFIS models
Küçük Resim Yok
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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. © 2018 Elsevier Ltd
Açıklama
Anahtar Kelimeler
Medlar fruit, Molecular, thermal and rheological characterization, Pectin extraction yield, RSM and ANFIS modeling, Differential scanning calorimetry, Extraction, Fourier transform infrared spectroscopy, Fruits, Fuzzy neural networks, Fuzzy systems, Nuclear magnetic resonance spectroscopy, Thermogravimetric analysis, Adaptive neuro-fuzzy inference system, ANFIS model, Extraction yield, High methoxyl pectins, Medlar fruits, Response surface methodology, Rheological characterization, Thermal and rheological properties, Fuzzy inference, arabinose, galactose, galacturonic acid, glucose, pectin, rhamnose, Article, chemical structure, controlled study, decomposition, differential scanning calorimetry, flow kinetics, Fourier transform infrared spectroscopy, fruit, fuzzy system, measurement repeatability, Mespilus germanica, nuclear magnetic resonance, physical chemistry, process control, Raman spectrometry, response surface method, thermogravimetry, Medlar fruit, Molecular, thermal and rheological characterization, Pectin extraction yield, RSM and ANFIS modeling, Differential scanning calorimetry, Extraction, Fourier transform infrared spectroscopy, Fruits, Fuzzy neural networks, Fuzzy systems, Nuclear magnetic resonance spectroscopy, Thermogravimetric analysis, Adaptive neuro-fuzzy inference system, ANFIS model, Extraction yield, High methoxyl pectins, Medlar fruits, Response surface methodology, Rheological characterization, Thermal and rheological properties, Fuzzy inference, arabinose, galactose, galacturonic acid, glucose, pectin, rhamnose, Article, chemical structure, controlled study, decomposition, differential scanning calorimetry, flow kinetics, Fourier transform infrared spectroscopy, fruit, fuzzy system, measurement repeatability, Mespilus germanica, nuclear magnetic resonance, physical chemistry, process control, Raman spectrometry, response surface method, thermogravimetry
Kaynak
Food Chemistry
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
271
