Kuwat Triyana

Analysis of lard in meatball broth using Fourier transform infrared spectroscopy and chemometrics

Meatball is one of the favorite foods in Indonesia. For the economic reason (due to the price difference), the substitution of beef meat with pork can occur. In this study, FTIR spectroscopy in combination with chemometrics of partial least square (PLS) and principal component analysis (PCA) was used for analysis of pork fat (lard) in meatball broth. Lard in meatball broth was quantitatively determined at wavenumber region of 1018-1284 cm(-1). The coefficient of determination (R(2)) and root mean square error of calibration (RMSEC) values obtained were 0.9975 and 1.34% (v/v), respectively. Furthermore, the classification of lard and beef fat in meatball broth as well as in commercial samples was performed at wavenumber region of 1200-1000 cm(-1). The results showed that FTIR spectroscopy coupled with chemometrics can be used for quantitative analysis and classification of lard in meatball broth for Halal verification studies. The developed method is simple in operation, rapid and not involving extensive sample preparation.

Electrospun Nanofibers Based on Polyvinyl Alcohol/Chitosan and its Stability in KOH Solution

Fabrication of nanofibers based on polyvinyl alcohol and chitosan (PVA/chitosan) has been carried out by means of electrospinning with focusing on beads formation and diameter variation due to effects of weight ratio variations of PVA/chitosan. For electrospinning solution, the PVA/chitosan with artios of 10:1, 10:2 and 10:3 w/w were dissolved in 1% acetic acid. In addition, stability testing of PVA/chitosan nanofibers in an electrolyte solution was performed by soaking the nanofiber mat in KOH solution. As results, the addition of chitosan concentration increased the pH, conductivity, and viscosity of the solution. Beads were potentially generated for low chitosan concentration. Furthermore, the effect of viscosity and conductivity on diameter of electrospun nanofibers is very significant and need to be optimized. The average diameter of electrospun nanofibers were found to be 160 ± 18 nm, 120 ± 12 nm, and 148 ± 26 nm, for weight ratios of PVA and chitosan 10:1, 10:2 and 10:3, respectively. In addition, no significant change in morphology after being soaked the electrospun PVA/chitosan nanofibers in KOH 40 wt% solution for 24 hours. It indicates that the electrospun PVA/chitosan nanofibers is stable in electrolyte solution which shows a high potential for electrolyte membrane in fuel cells application.

Differentiation of Bovine and Porcine Gelatins in Soft Candy Based on Amino Acid Profiles and Chemometrics

An UV spectrophotometric area under curve method was developed for the estimation of Levofloxacin Hemihydrate in its mono component tablets. The spectrophotometric method for estimation employed Area under curve method for analysis using 0.1M Sodium Hydroxide as solvent for the drug Levofloxacin Hemihydrate at the wavelength range of 285-295nm. Levofloxacin Hemihydrate obeys Beer’s law in concentration range 10-50µg/ml. The recovery studies ascertained accuracy of the proposed method and the result validated according to ICH guideline. Results of analysis have been valid statistically by recovery studies. The method was successfully for evaluation of Levofloxacin Hemihydrate in tablet dosage form without the interference of common excipients.

Improvement of Heterojunction Donor/Acceptor Organic Photovoltaic Devices by Employing Additional Active Layer

Single-heterojunction (HJ) donor/acceptor photovoltaic devices composed of copper phtalocyanine (CuPc) and 3,4,9,10-perylenetetracarboxylic bis-benzimidazole (PTCBI) sandwiched between indium–tin–oxide (ITO) and Ag top electrode were investigated. An improvement in device performance was obtained by inserting another perylene derivative, 3,4,9,10-perylenetetracarboxylic diimide (PTCDI) between the CuPc and the PTCBI layers. In this case, the PTCDI and the PTCBI act as an active layer and a buffer, respectively. The active layer increased the absorption efficiency of incident photons, while the buffer provided an ohmic contact with the Ag top electrode. The power conversion efficiency (PCE) was improved from 0.81% for the reference device (without a PTCDI layer) to 1.13% for the optimized single-HJ device (with a PTCDI layer). The concept found in the single-HJ device was introduced into the stacked tandem triple-HJ devices. The improvement of power conversion efficiency, however, was achieved by inserting the PTCDI layer between the PTCBI and the top electrode.

Development of Electronic Nose with Low-Cost Dynamic Headspace for Classifying Vegetable Oils and Animal Fats

A portable electronic nose (e-nose) using low-cost dynamic headspace and commercially metal oxide gas sensors has been developed. This paper reports evaluation on the performance of the e-nose to classify vegetable oils (sunflower and grape seed oils) and animal fats (mutton, chicken and pig fats). The e-nose consists of a dynamic headspace sampling, a gas sensor array and a real-time data acquisition system based on ATMega-16 microcontroller. The dynamic headspace can divided into two chambers, i.e. sample and gas sensor array room. It is also equipped with three small fans for adjusting sensing and purging processes. Principal component analysis (PCA) was used for measurement data analysis after all features being extracted. The first two principal components were kept because they accounted for 91.1% of the variance in the data set (first and second principals accounted for 72.9, 18.2% of the variance, respectively). This results show that the e-nose can distinguish vegetable oils and animal fats. This work demonstrates for the future that the e-nose with low-cost dynamic headspace technique may be applied to the identification of oils and fats in halal authentication.

Sensitivity Improvement of Ammonia Gas Sensor Based on Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate) by Employing Doping of Bromocresol Green

The aim of this research is to improve the sensitivity of ammonia gas sensor (hereafter referred to as sensor) based on poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) by employing the doping dye of bromocresol green (BCG). The doping process was carried out by mixing the BCG and the PEDOT:PSS in a solution with an optimum ratio of 1 : 1 in volume. The sensor was fabricated by using spin-coating technique followed by annealing process. For comparison, the BCG thin film and the PEDOT:PSS thin film were also deposited with the same method on glass substrates. For optical characterization, a red-light laser diode with a 650 nm wavelength was used as light source. Under illumination with the laser diode, the bare glass substrate and BCG film showed no absorption. The sensor exhibited linear response to ammonia gas for the range of 200 ppm to 800 ppm. It increased the sensitivity of sensor based on PEDOT:PSS with BCG doping being about twofold higher compared to that of without BCG doping. Furthermore, the response time and the recovery time of the sensor were found very fast. It suggests that the optical sensor based on BCG-doped PEDOT:PSS is promising for application as ammonia gas sensor.

Solvent vapor treatment improves mechanical strength of electrospun polyvinyl alcohol nanofibers

Electrospun nanofibers of polyvinyl alcohol (PVA) have poor mechanical strength. As such their use has often been avoided, particularly in applications that require high mechanical properties. The objective of this study is to increase the mechanical properties of PVA nanofiber mats via physical crosslinking with solvent vapor treatment using organic solvents, dimethyl sulfoxide (DMSO), N, N-dimethyl formamide (DMF), and methanol. The effect of solvent vapor treatment on PVA nanofibers is clearly observed by scanning electron microscope (SEM). The tensile strength increased by over 60%, 90%, and 115% after solvent vapor treatment with DMF at a temperature of 40 °C for 2 h, 4 h, and 8 h, respectively, compared to untreated PVA nanofibers. In addition, Youngs modulus of PVA nanofiber mats also increased after DMF treatment. As a comparison, DMSO and methanol were also used in solvent vapor treatment because of differences in their polymer-solvent affinity. Results showed that the highest improvement (100%) in mechanical strength was obtained using DMF. This study shows that solvent vapor treatment offers a simple and inexpensive method that provides excellent results and is a promising alternative treatment for use in increasing the mechanical properties of electrospun nanofibers.

Study of parallel oriented electrospun polyvinyl alcohol (PVA) nanofibers using modified electrospinning method

Parallel orientedpolyvinyl alcohol (PVA) nanofibershasbeen successfully prepared by using modified electrospinning method. This method uses two pairs of copper (Cu) electrodes which are set apart at a certain distance and applied voltage of 15 kV. The concentrations of PVA were varied from 11%, 13%, 15%, 17%, and 19%. The width of gap collector were varied from 5 mm, 10 mm, 15 mm, and 20 mm. The diameter of nanofibers increase as increasing concentration of PVA. As the width of gap collector increase, first diameter of nanofibers decrease and reach a minimum value at 355 ± 7nm in 15 mm of gap, then the diameters increase again. We also calculated the alignment parameter (S) for given aligned nanofiber. The result showed that alignment parameters (S) were on values around 0,9-1.

Optimized back-propagation combined with radial basic neural network for improving performance of the electronic nose: Case study on the fermentation process of tempeh

Tempeh is a popular traditional food from Indonesia, and its physical and chemical characteristics have been intensively investigated. Study on the fermentation process, however, still requires more attention. Here, the aroma profile during 10-day fermentation process was analyzed using an electronic nose (e-nose). The e-nose used in this study was based on eight kinds of the gas sensor (metal oxide semiconductor). A differential baseline manipulation and a maximum value as feature extraction were applied for the data processing. Meanwhile, the back-propagation neural network (BPNN) was used to classify the tempeh aroma profiles into four classes as described by principal component analysis (PCA). In this work, we optimized the BPNN and combined with the radial basis neural network (RBNN) to improve the performance of the e-nose. As a result, the combination between optimized BPNN and RBNN is able to recognize all data to the appropriate class as 100%.

Synthesis of copper nanorods by aqueous solution method without heating external

So far, synthesizing Cu nanorods (CuNRs) are complicated, expensive, and needs a long time. In this study, We report a simple way to synthesized CuNRs by the aqueous solution method without external heating. Instead of external heating, we used internal heating from the exothermic reaction of NaOH and water. Copper (II) nitrate trihydrate Cu (NO3)2.3H2O, sodium hydroxide (NaOH), ethylenediamine (EDA), and hydrazine (N2H4) were used in our work. The morphology and formation structure of CuNRs have been investigated using Scanning Electron Microscope-Energy Dispersive X-ray Spectroscopy (SEM-EDXS), and X-ray Diffraction (XRD). The SEM analysis confirmed the formation of CuNRs with a diameter of 200-300 nm and length of 3-7 µm.