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- MakaleAçık Erişim2026Scopus SJRQ1Microwave-Assisted Extraction of Pectin from Pickled Cabbage Waste: Process Optimisation, Characterisation and Application in Low-Sugar Jam
Cebeci Aydın, Fatma; Erten, Tayyibe
This study optimised pectin extraction from pickled cabbage waste using microwave-assisted extraction (MAE), characterised the extracted pectin, and explored its potential for low-sugar jam production. The Box–Behnken design concluded that the optimal conditions are 539 W (microwave power), 116 s (time), and pH 1.5, yielding a pectin yield of 22.53 ± 2.63%. The physicochemical analysis revealed that the microwave-extracted pectin (MEP) was low methoxyl and had a high molecular weight (1.20 ± 0.004 MDa). It was composed of galacturonic acid, arabinose, rhamnose, xylose and glucose. FTIR, 1H NMR and SEM results also confirmed structural characteristics of MEP. MEP was confirmed to have remarkable technological properties, including an emulsion activity of 53.43 ± 2.19% and good stability over 30 days at 4 °C and 24 °C. Moreover, it has an oil-holding capacity of 1.18 ± 0.51 g oil/g pectin and an elevated water-holding capacity (9.36 ± 3.25 g water/g pectin). The application of MEP as a stabiliser in low-sugar jam enhanced viscoelastic characteristics of jam, like apple pectin, and G′ > G″ confirmed the improved shelf-life stability at 25 °C. This study emphasised that microwave-assisted extraction can be a sustainable, time- and energy-saving method for the valorisation of pickled cabbage waste, and highlighted the effect of MEP on the characteristics of low-sugar jam.
- MakaleAçık Erişim2020Scopus SJRQ1An integrated neural-fuzzy methodology for characterisation and modelling of exopolysaccharide (EPS) production levels of Leuconostoc mesenteroides DL1
Kabli, Mohammad; Yilmaz, Mustafa Tahsin; Taylan, Osman; Kaya, Yasemin; İspirli, Hümeyra; Basahel, Abdulrahman; Sagdic, Osman; Dertli, Enes
Optimisation of exopolysaccharides (EPS) production in Lactic Acid Bacteria (LAB) is an important task as EPS production can be affected by different parameters. In this respect, this study aimed to characterise the structure of an EPS from Leuconstoc mesenteroides DL1 strain and to optimise the EPS production by determination of the effects of incubation time, sucrose concentration, incubation temperature and initial levan concentration (input parameters) using integrated ANNs (Artificial neural networks) and fuzzy modelling approaches. The characterisation of the EPS monomeric composition by HPLC analysis revealed that EPS DL1 was composed of glucose and fructose. The 1H and 13C NMR spectra of EPS DL1 also confirmed the glucan and fructan production. The effects of the input parameters on glucan and fructan production levels as output parameters by DL1 were optimised using neural network and fuzzy modelling tools. The fuzzy model was developed based on the recognition of basic elements of input-output parameters, and the power of ANNs used for system identification. A structural analysis was carried out to improve the flexibility of fuzzy model, and to design the unknown mappings of the input and output parameters more robustly. The parameters then were fine-tuned by qualitative reasoning to establish the relations of input output parameters using membership functions (MFs) and their intervals determination. A hybrid training algorithm was employed for parameter identification, MFs and their interval determination to obtain the fuzzy model. The model can predict the outcome parameters; glucan and fructan with high accuracy for the predetermined input parameters.
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