Total polar compounds (TPC) and free fatty acids (FFA) are important indicators in evaluating the quality of frying oil. Conventional methods to determine TPC and FFA are often time consuming, involved laboratory analyses which required skilled personnel and used substantial amount of harmful solvent. In this study, dielectric spectroscopy technique was used to investigate the relation between dielectric property of refined, bleached and deodorized palm olein (RBDPO) during deep frying with TPC and FFA. In total, 150 batches of French fries were intermittently fried at 185 ± 5 °C for 7 hr a day over 5 consecutive days. A total of 30 frying oil samples were collected. The dielectric property of frying oil samples were measured using impedance analyzer with frequencies ranging from 100 Hz to 10 MHz. The TPC of frying oil samples were measured with a Testo 270, while the FFA analysis was done using Malaysian Palm Oil Board (MPOB) test method. Results showed that dielectric constant, TPC and FFA of RBDPO increased as the frying time increased. Dielectric constant increased from 3.09 to 3.17, while TPC and FFA increased from 9.96 to 19.52 and from 0.08% to 0.36%, respectively. Partial least square (PLS) analysis produced good prediction of TPC and FFA with the application of genetic algorithm (GA). Model developed for prediction of TPC and FFA yielded highly significant correlation with R2 of 0.91 and 0.95, respectively and both had root mean square error in cross-validation (RMSECV) of 1.06%. This study demonstrates the potential of dielectric spectroscopy in monitoring palm olein degradation during frying. PRACTICAL APPLICATION: The application of dielectric spectroscopy to detect degradation of palm olein during frying was studied. The dielectric property of palm olein during frying has successfully correlated with TPC and FFA. The model developed in this study could be used for the development of a sensing system for palm olein degradation monitoring.
This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes.
Dielectric spectroscopy is employed to study the relaxation phenomena in natural polyhydroxyalkanoates (PHAs) upon temperature and frequency variations. Effects of PHAs molecular structure on the relaxation, arising from the differences in monomeric composition, are investigated under identical conditions in a frequency range of 10-2-106 Hz, and at different temperatures. All PHA samples showed different dielectric response at different temperature. Primary α-relaxation signals are observed at temperature corresponding to the glass transition temperature. On the other hand, secondary β- and γ-relaxations are detected at low temperatures, and attributed to local motions of polar groups and small segments of the polymer chain. The dielectric properties of representative PHA samples are compared and discussed.
For the past decade, much attention was focused on polysaccharide natural resources for various purposes. Throughout the works, several efforts were reported to prepare new function of chitosan by chemical modifications for renewable energy, such as fuel cell application. This paper focuses on synthesis of the chitosan derivative, namely, O-nitrochitosan which was synthesized at various compositions of sodium hydroxide and reacted with nitric acid fume. Its potential as biopolymer electrolytes was studied. The substitution of nitro group was analyzed by using Attenuated Total Reflectance Fourier Transform Infra-Red (ATR-FTIR) analysis, Nuclear Magnetic Resonance (NMR) and Elemental Analysis (CHNS). The structure was characterized by X-ray Diffraction (XRD) and its thermal properties were examined by using differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA). Whereas, the ionic conductivity of the samples was analyzed by electrochemical impedance spectroscopy (EIS). From the IR spectrum results, the nitro group peaks of O-nitrochitosan, positioned at 1646 and 1355 cm-1, were clearly seen for all pH media. At pH 6, O-nitrochitosan exhibited the highest degree of substitution at 0.74 when analyzed by CHNS analysis and NMR further proved that C-6 of glucosamine ring was shifted to the higher field. However, the thermal stability and glass transition temperatures were decreased with acidic condition. The highest ionic conductivity of O-nitrochitosan was obtained at ~10-6 cm-1. Overall, the electrochemical property of new O-nitrochitosan showed a good improvement as compared to chitosan and other chitosan derivatives. Hence, O-nitrochitosan is a promising biopolymer electrolyte and has the potential to be applied in electrochemical devices.