Pemanfaatan Fly Ash Sawit sebagai Katalis Asam dalam Proses Esterifikasi Gliserol sebagai Produk Samping Biodiesel Menjadi Triacetin

Glycerol is a by-product of biodiesel that produced about 10% of the amount of biodiesel. Glycerol can be processed into economic products such as triacetin. Triacetin is a triesther of glycerol and acetic acid that can be applied as additive in the field of food or non food. Triacetin can be produced through estherification of glycerol and acetic acid by using palm fly ash as the solid acid catalyst. The aim of this research was to determined the characteristic of the palm fly ash as solid acid catalyst and determined the influence of the catalyst concentration, mol ratio of reactan and time of estherification toward the conversion of glycerol. Variation that used were concentration of catalyst 1, 2, 3% of acetic acid mass, mol ratio of reactan 1:5, 1:7, 1:9, and time of estherification 1, 2, and 3 hours. The estherification temperature was 100oC. The characteristic of palm fly ash catalyst of acidity, crystallinity, and surface area increasing after activation process. The conversion of glycerol increased by the increasing of catalyst concentration, mol ratio of reactan and time of estherification. The highest conversion gain at concentration of catalyst 1%, mol ratio of reactan 1:9, and time of estherification 3 hours is 47.41%

Effect of Substrate Temperature and Target-Substrate Distance on Growth of TiO2 Thin Films by Using DC- Reactive Sputtering Technique

Titanium oxide (TiO2) thin films have been deposited by a DC sputtering technique onto microscope glass slides. The effect of substrate temperature (Ts) and target-substrate distance (Dts) on some optical and electrical properties have been studied each individually. The structure of TiO2 thin films has been improved and became more crystalline when Ts has been increased (from 150 ºC to 250 ºC). The conductivity (ϭ), deposition rate (DR) and average values of grain size (G.S) have been increased with increasing Ts while the values of band gap (Eg) and weight percentage of the anatase phase (WA) have been decreased. The thickness of TiO2 film has been increased from 920 nm to 960 nm with increase Ts while it has been decreased from 960 nm to 680 nm with increase Dts (from 25mm to 35mm). As Dts has been increased, the conductivity ϭ, thickness (d) and average values of grain size have been decreased. The decreasing of conductivity at Dts=35 maybe attributes to increase the weight percentage of the rutile phase (WR). The XRD results show that the TiO2 structure phase has been varied. The results show that the optical and electrical properties of TiO2 film affected by changes the condition parameters especially Ts and Dts as well as the density and energy of the impinging atoms. The surface morphology and component of TiO2 thin films, resistance, optical transmittance and structure of film were characterized by SEM (EDX), I-V meter, UV-VIS spectrophotometer and XRD respectively

Prototype of Electronic Nose Based on Gas Sensors Array and Back Propagation Neural Network for Tea Classification

We have developed an electronic nose based on metal oxide gas sensor array and back-propagation neural network for tea classification. The sensor array consists of six Tagushi Gas Sensor (TGS) type devices. To recognize the pattern formed by the six sensors we used six neurons in the input layer. Since we only want to classify four tea samples, we used two neurons in the output layer. The four tea samples (different tea flavors) were purchased from local super store in Yogyakarta, namely, black tea, green tea, vanilla tea and jasmine tea. Under the relatively similar conditions, we measured each sample of tea as a function of time. Prior to the exposure of tea samples, the sensor array was tested with air ambient. Then the electronic nose was trained by using one set of four tea samples without pre-processing step. By using all data sets, the electronic nose is able to recognize the pattern for almost 80%. This result prove that our electronic nose is capable of discriminating between the flavors of tea samples. For further investigation, the performance of this system should be compared with the data sets with pre-processing. Keywords : Odor, Tea flavor, Metal oxide gas sensor, Sensor array, Back Propagation Neural networ

Electronic nose coupled with linear and nonlinear supervised learning methods for rapid discriminating quality grades of superior java cocoa beans

An electronic nose (E-nose), comprising eight metal oxide semiconductor (MOS) gas sensors and a moisture-temperature sensor, was used for classifying three quality grades of superior java cocoa beans, namely fine cocoa dark bean 60%, and bulk cocoa bean that is a harder task compared to the discrimination of high versus low-quality cocoa beans. The E-nose signals were pre-processed using the maximum value method. The capability for discriminating the quality grade of the cocoa beans was checked by applying multivariate statistical tools, namely, linear discriminant analysis (LDA), support vector machine (SVM) and artificial neural networks (ANN). For this, the experimental dataset was split into two subsets, one for training (i.e., establishing the classification models) and the other for external-validation purposes. Furthermore, hyperparameter optimization and K-fold cross-validation variant were implemented during the model training procedure to select the best classification models and to avoid over-fitting issues. The best predictive classification performance was obtained with the E-nose-MLP-ANN procedure, which allowed 99% of correct classifications (overall accuracy) for the training dataset and 95% of correct classifications (overall accuracy) for the external-validation dataset. The satisfactory results clearly demonstrated that the E-nose could be applied as a quality control tool in the cocoa industry, requiring minimum and simple sample preparation. © Intelligent Network and Systems Society.The authors thank the Directorate of Research and Community Service, Ministry of Research, Technology and Higher Education, the Republic of Indonesia for providing research grants of PTUPT 2019 (Contract No. 2688/UN1.DITLIT/DITLIT/LT/2019). The authors also like to acknowledge the financial support given by Associate Laboratory LSRE-LCM-UID/EQU/50020/2019, strategic funding UID/BIO/04469/2019-CEB, BioTecNorte operation (NORTE-01-0145-FEDER-000004) and strategic project PEst-OE/AGR/UI0690/2014 – CIMO, all funded by national funds through FCT/MCTES (PIDDAC).info:eu-repo/semantics/publishedVersio

Effects of Molar Ratios and Sintering Times on Crystal Structures and Surface Morphology of Nd1+xFeO3 Oxide Alloy Prepared by using Solid Reaction Method

The effects of molar ratios and sintering times on crystal structures and surface morphology on NdFeO3 oxide alloy have been studied. NdFeO3 oxide alloy formed by chemical preparation with solid reaction method using raw oxide Fe2O3 (99.9 %) and Nd2O3 (99.9 %) powders. In this article we reported the effects of molar ratios x = (–0.1, –0.2 and – 0.3) and sintering times for 15 h and 20 h on crystal structures and surface morphology of Nd1+xFeO3 synthesized by solid-state reaction method. The results indicate that variation of molar ratio and sintering time has influenced the FWHM, crystalline size and grain size. The Nd1+xFeO3 have a major phase is NdFeO3, and other minor phases are Fe2O3, Nd2O3 and Nd(OH)3. The dominant intensity of hkl (121) with a value in FWHM, crystallite size, and grain size an indication the results will be applied as a gas sensor material as the focus of the further study

EFFECT OF ALKALI TREATMENT AND MAPP ADDITION ON TENSILE STRENGTH OF SISAL/POLYPROPYLENE COMPOSITES

Mechanical properties of composite are strongly influenced by surface treatment of fibers and fiber content. The study aimed to verify the influence of a modified fiber surface using an alkali solution and, the addition of maleic anhydride grafted polypropylene (MAPP) and both (alkali solution + MAPP) on increasing the tensile strength of sisal/polypropylene (PP) composites. The composites were fabricated using hot compression molding with a fiber content of 30 and 50 wt%. Untreated and alkali-treated sisal fibers with a fiber length of ~ 2 mm were used. Various amounts (5, 10 and 15 wt%) of MAPP were added to the untreated sisal/PP and alkali-treated sisal/PP composites. The results indicated that the tensile strength of the untreated sisal/PP composite containing 50 wt% of fiber was higher than that of 30 wt% fiber content. The addition of 5 wt% MAPP into both untreated and alkali-treated sisal/PP composites significantly increased tensile strength compared to that of 10 and 15 wt% MAPP addition. Good interfacial bonding between sisal fiber and the PP matrix was observed at 5 wt% MAPP loading. Excessive MAPP content could form a barrier that tends to inhibit the stress transferred across the matrix-fiber interfaces

Aplikasi Jaringan Syaraf Tiruan Propagasi Balik Pada System Olfaktori Elektronik Larik Sensor Gas Untuk Deteksi Jenis Bahan Herbal

Penggunaan sistem jaringan syaraf tiruan propagasi Balik untuk mengenali pola keluaran larik sensor gas dalam sistem olfaktori elektronik atau electronic nose (yang selanjutnya disebut enose) telah terapkan terhadap empat macam sampel bahan herbal. Keempat bahan herbal tersebut meliputi: jahe (zingiber officinale), kencur (Kaempferia galanga) , kunyit (curcuma domestica val) dan lengkuas (languas galanga). Enose yang digunakan terdiri atas empat sensor gas berbahan logam oksida seri TGS 822, TGS 825, TGS 826, dan TGS 880. Sepertidalam sistem olfaktori pada manusia (hidung) maka untuk dapat mengidentifikasi pola berdasarkan aroma khas yang ada pada setiap sampel bahan herbal, enose harus melalui serangkaian proses pelatihan dan pengujian dengan model tertentu, salah satunya dengan menggunakan jaringan syaraf tiruan (JST). Sebelum diproses lebih lanjut, sinyal keluaran (berupa tegangan) dari masing-masing sensor yang membentuk suatu pola perlu diekstraksi untuk memperoleh karakteristik ciri masing-masing sampel sekaligus mereduksi himpunan datanya.Penelitian ini menerapkan dekomposisi wavelet daubechies 4 tingkat 8, sehingga sinyal asli keluaran yang membentuk sinyal kontinyu tak periodik dengan himpunan data sangat besar berbentuk matriks 400×4 tereduksi menjadi himpunan data yang tersusun atas matriks berukuran 16×4. Dalam hal ini, setiap sensor diwakili dengan himpunan data berdimensi 16 yang merupakan nilai koefisien aproksimasi cA8, dan himpunan data koefisien detail cD8. Matriks berukuran 16×4 inilah yang merupakan hasil ekstraksi ciri masing-masing sinyal keluaran sistem larik empat sensor sekaligus menjadi input data pada sistem jaringan syaraf tiruan. Selanjutnya dengan melakukan serangkaian pelatihan dan pengujian empat jenis bahan herbal, sistem jaringan syaraf tiruan propagasi Balik mampu untuk mengenali jenis bahan herbal dengan ketelitian mencapai 93 %

Optimisation of the Maillard reaction of bovine gelatine-xylose model using response surface methodology

The Maillard reaction is known as an amino-carbonyl reaction or non-enzymatic browning reaction which has an essential role in food processing to improve the appearance, taste and functional properties of food. In halal authentication, results could be used to differentiate the sources of gelatine based on the colour and flavour. Since many factors can influence the reaction, it is important to study and optimize the Maillard reaction in a gelatine model system using response surface method, applied to optimize the processing of bovine gelatine-xylose to improve the Maillard reaction products. In this study, the effects of initial pH, temperature, and heating time to browning intensity of melanoidin were evaluated. The increasing of initial pH, temperature and heating time were associated with an enhanced browning intensity of Maillard reaction products. This study demonstrated that the coefficient of determination 0.8429 reveals the response surface reduced linear model is an adequate model for browning intensity of Maillard reaction of the bovine gelatine-xylose system. For a system with 5% of gelatine solution and 0.75 g of xylose, the optimum condition for the browning process obtained was initial of pH 10.92, temperature of 140°C and heating time of 37.28 mins. The predicted results at optimum conditions coincided well with the experimental value with the relative error of less than 5%

Fourier transform infrared spectrum pre-processing technique selection for detecting PYLCV-infected chilli plants

Pre-processing is a crucial step in analyzing spectra from Fourier transform infrared (FTIR) spectroscopy because it can reduce unwanted noise and enhance system performance. Here, we present the results of pre-processing technique optimization to facilitate the detection of pepper yellow leaf curl virus (PYLCV)-infected chilli plants using FTIR spectroscopy. Optimization of a range of pre-processing techniques was undertaken, namely baseline correction, normalization (standard normal variate, vector, and min–max), and de-noising (Savitzky-Golay (SG) smoothing, 1st and 2 derivatives). The pre-processing was applied to the mid-infrared spectral range (4000 – 400 cm−1) and the biofingerprint region (1800 – 900 cm−1) then the discrete wavelet transform (DWT) was used for dimension reduction. The pre-processed data were then used as an input for classification using a multilayer perceptron neural network, a support vector machine, and linear discriminant analysis. The pre-processing method with the highest classification model accuracy was selected for the further use in the processing. It was seen that only the SG 1st derivative method applied to both wavenumber ranges could produce 100% accuracy. This result was supported by principal component analysis clustering. Thus, we have demonstrated that by using the right pre-processing technique, classification success can be increased, and the process simplified by optimization and minimization of the technique used