This paper outlines the application of chemometrics and pattern recognition tools to classify palm oil using Fourier Transform Mid Infrared spectroscopy (FT-MIR). FT-MIR spectroscopy is used as an effective analytical tool in order to categorise the oil into the category of unused palm oil and used palm oil for frying. The samples used in this study consist of 28 types of pure palm oil, and 28 types of frying palm oils. FT-MIR spectral was obtained in absorbance mode at the spectral range from 650 cm -1 to 4000 cm -1 using FT-MIR-ATR sample handling. The aim of this work is to develop fast method in discriminating the palm oils by implementing Partial Least Square Discriminant Analysis (PLS-DA), Learning Vector Quantisation (LVQ) and Support Vector Machine (SVM). Raw FT-MIR spectra were subjected to Savitzky-Golay smoothing and standardized before developing the classification models. The classification model was validated through finding the value of percentage correctly classified by test set for every model in order to show which classifier provided the best classification. In order to improve the performance of the classification model, variable selection method known as t-statistic method was applied. The significant variable in developing classification model was selected through this method. The result revealed that PLSDA classifier of the standardized data with application of t-statistic showed the best performance with highest percentage correctly classified among the classifiers.
Two functional food oils, namely extra virgin olive oil (EVOO) and virgin coconut oil (VCO) have been analyzed simultaneously using Fourier transform infrared (FTIR) spectroscopy. The performance of multivariate calibration of principle component regression (PCR) and partial least square regression (PLSR) was evaluated in order to give the best prediction model for such determination. FTIR spectra were treated with several treatments including mean centering (MC), derivatization, and standard normal variate (SNV) at the combined frequency regions of 3050 – 3000, 1660 – 1650, and 1200 – 900 cm-1. Based on its capability to give the highest values of coefficient of correlation (R) for the relationship between actual value of EVOO/VCO and FTIR predicted value together with the lowest values of root mean square error of calibration (RMSEC), PLSR with mean centered-first derivative spectra was chosen for simultaneous determination of EVOO and VCO. It can be concluded that FTIR spectroscopy combined with multivariate calibration of PLSR was successfully applied to simultaneously quantify EVOO and VCO with acceptable parameters.
This aim of this research is to investigate thermal stability of virgin coconut oil, (VCO) which was heated at 190°C upon 40 days storage as compared to extra virgin olive oil (EVOO). The changes in fatty acids composition through (GC), Fourier Transform Infrared (FTIR) spectra, iodine value (IV) and total phenolic content were determined throughout the period of study. Results from GC showed that there was significant changes (P
This study was conducted to prepare a mixed matrix membrane (MMM) and to test the performance of the prepared MMM for CO2 and CH4 gas separation. MMM containing polyethersulfone (PES) and multi-walled carbon nanotubes (MWCNTs) was prepared by a dry-wet phase inversion technique using a pneumatically-controlled membrane casting machine. The surface modification was performed on MWCNTs in order to enhance the selectivity of CO2/CH4. The surface modification of MWCNTs using chemical and physical approaches has been adopted. Mixed acid (HNO3/H2SO4) and β-CD were used for chemical and physical approaches, respectively. Effects of surface modification on MWCNTs/PES MMM were investigated. MWCNTs/PES MMMs were characterised using scanning electron microscopy (SEM), the Fourier Transform Infrared (FT-IR) spectroscopy and pure gas permeation test. The permeability and selectivity, which are the parameters describing membrane performance were calculated via the data obtained from pure gas permeation test with the feed pressure difference from 3 to 7 bars. In this study, surface modified MWCNTs/PES MMM using mixed acid and β-CD has successfully enhanced the CO2/CH4 selectivity by 40.6% compared to that of neat PES.
Neat cellulose acetate (CA) and CA/polysulfone (PSf) blend ultrafiltration membranes in the presence of polyvinylpyrrolidone as a pore former were prepared via a phase inversion technique. The prepared membranes were characterized by Fourier transform infrared, scanning electron microscopy, mechanical strength, water content, porosity, permeate flux and heavy metals (Pb2+, Cd2+, Zn2+ and Ni2+) rejection to comprehend the impact of polymer blend composition and additive on the properties of the modified membranes. The water flux expanded by increasing of PSf content in the polymer composition. CA/PSf (60/40) had the highest flux among prepared membranes. Prepared blend membranes were able to remove heavy metals from water in the following order: Pb2+ > Cd2+ > Zn2+ > Ni2+. The CA/PSf (80/20) blend membrane had great performance among prepared membranes due to the high heavy metals removal and permeate flux.
Due to the outbreak of the COVID-19 pandemic, practicing personal hygiene such as frequent hand sanitising has become a norm. The making of effective hand sanitiser products should follow the recommended formulations, but the high demand worldwide for such affordable products could have made them a candidate for counterfeiting, thus deserving forensic determination and profiling for source determination or supply chain tracing. In this study, determination and discrimination of hand sanitisers was carried out by employing attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics. Fifty commercially available hand sanitisers were obtained from the market and analysed. ATR-FTIR profiles of each sanitiser were compared and decomposed by principal component analysis (PCA) followed by linear discriminant analysis (LDA). Physical observation enabled the discrimination of seven samples based on their respective colours, the presence of beads and their colours, and the physical forms of formulations. Subsequently, eight distinct patterns were observed through visual comparison of ATR-FTIR profiles of the remaining 43 samples. An initial unsupervised exploratory PCA model indicated the separation of two main groups with ATR-FTIR profiles similar to those of ethanol and isopropanol, respectively. The PCA score-LDA model provided good predictions, with a 100% correct classification into eight different groups. In conclusion, this study demonstrated a quick determination and discrimination of hand sanitiser samples, allowing screening for any restricted components and sample-to-sample comparison.
Hypothyroidism in infants is caused by the insufficient production of hormones by the thyroid gland. Due to stress in the chest cavity as a result of the enlarged liver, their cry signals are unique and can be distinguished from the healthy infant cries. This study investigates the effect of feature selection with Binary Particle Swarm Optimization on the performance of MultiLayer Perceptron classifier in discriminating between the healthy infants and infants with hypothyroidism from their cry signals. The feature extraction process was performed on the Mel Frequency Cepstral coefficients. Performance of the MLP classifier was examined by varying the number of coefficients. It was found that the BPSO enhances the classification accuracy while reducing the computation load of the MLP classifier. The highest classification accuracy of 99.65% was achieved for the MLP classifier, with 36 filter banks, 5 hidden nodes and 11 BPS optimised MFC coefficients.
In this study, dye-sensitized solar cells (DSSCs) has been assembled with poly(1-vinylpyrrolidone-co-vinyl acetate) (P(VP-co-VAc)) gel polymer electrolytes (GPEs) which have been incorporated with binary salt and an ionic liquid. The potential of this combination was studied and reported. The binary salt system GPEs was having ionic conductivity and power conversion efficiency (PCE) that could reach up to 1.90 × 10(-3) S cm(-1) and 5.53%, respectively. Interestingly, upon the addition of the ionic liquid, MPII into the binary salt system the ionic conductivity and PCE had risen steadily up to 4.09 × 10(-3) S cm(-1) and 5.94%, respectively. In order to know more about this phenomenon, the electrochemical impedance studies (EIS) of the GPE samples have been done and reported. Fourier transform infrared studies (FTIR) and thermogravimetric analysis (TGA) have also been studied to understand more on the structural and thermal properties of the GPEs. The Nyquist plot and Bodes plot studies have been done in order to understand the electrochemical properties of the GPE based DSSCs and Tafel polarization studies were done to determine the electrocatalytic activity of the GPE samples.
Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.
The present study investigated the biosorption capacity of live and dead cells of a novel Bacillus strain for chromium. The optimum biosorption condition was evaluated in various analytical parameters, including initial concentration of chromium, pH, and contact time. The Langmuir isotherm model showed an enhanced fit to the equilibrium data. Live and dead biomasses followed the monolayer biosorption of the active surface sites. The maximum biosorption capacity was 20.35 mg/g at 25 °C, with pH 3 and contact time of 50 min. Strain 139SI was an excellent host to the hexavalent chromium. The biosorption kinetics of chromium in the dead and live cells of Bacillus salmalaya (B. salmalaya) 139SI followed the pseudo second-order mechanism. Scanning electron microscopy and fourier transform infrared indicated significant influence of the dead cells on the biosorption of chromium based on cell morphological changes. Approximately 92% and 70% desorption efficiencies were achieved using dead and live cells, respectively. These findings demonstrated the high sorption capacity of dead biomasses of B. salmalaya 139SI in the biosorption process. Thermodynamic evaluation (ΔG⁰, ΔH⁰, and ΔS⁰) indicated that the mechanism of Cr(VI) adsorption is endothermic; that is, chemisorption. Results indicated that chromium accumulation occurred in the cell wall of B. salmalaya 139SI rather than intracellular accumulation.
Drugs-facilitated crimes (DFCs) involve the incapacitation of victims under the influence of drugs. Conventionally, a drug administration act is often determined through the examination of biological samples; however, dry residues from any surface, such as drinking glass if related to a DFC could be a potential source of evidence. This study was aimed to establish an attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy coupled with chemometrics for the determination of spiked sedative-hypnotics from dry residues of a drug-spiked beverage. In this study, four sedative-hypnotics, namely diazepam, ketamine, nimetazepam, and xylazine were examined using ATR-FTIR spectroscopy. Subsequently, the ATR-FTIR profiles were compared and decomposed by principal component analysis (PCA) followed by linear discriminant analysis (LDA) for their detection and discrimination. Visual comparison of ATR-FTIR profiles revealed distinct spectra among the tested drugs. An initial unsupervised exploratory PCA model indicated the separation of four main sedative-hypnotics clusters, and the proposed PCA score-LDA model had allowed for a 100% accurate classification. Discrimination of sedative-hypnotics from a dry beverage previously spiked with these drugs was also possible upon an additional extraction procedure. In conclusion, ATR-FTIR coupled with PCA score-LDA model was useful in detecting and discriminating sedative-hypnotics, including those that had been previously spiked into a beverage.
A computer-aided detection auto-probing (CADAP) system is presented for detecting breast lesions using dynamic contrast enhanced magnetic resonance imaging, through a spatial-based discrete Fourier transform. The stand-alone CADAP system reduces noise, refines region of interest (ROI) automatically, and detects the breast lesion with minimal false positive detection. The lesions are then classified and colourised according to their characteristics, whether benign, suspicious or malignant. To enhance the visualisation, the entire analysed ROI is constructed into a 3-D image, so that the user can diagnose based on multiple views on the ROI. The proposed method has been applied to 101 sets of digital images, and the results compared with the biopsy results done by radiologists. The proposed scheme is able to identify breast cancer regions accurately and efficiently.
Microencapsulated paraffin wax/polyaniline was prepared using a simple in situ polymerization technique, and its performance characteristics were investigated. Weight losses of samples were determined by Thermal Gravimetry Analysis (TGA). The microencapsulated samples with 23% and 49% paraffin showed less decomposition after 330 °C than with higher percentage of paraffin. These samples were then subjected to a thermal cycling test. Thermal properties of microencapsulated paraffin wax were evaluated by Differential Scanning Calorimeter (DSC). Structure stability and compatibility of core and coating materials were also tested by Fourier transform infrared spectrophotometer (FTIR), and the surface morphology of the samples are shown by Field Emission Scanning Electron Microscopy (FESEM). It has been found that the microencapsulated paraffin waxes show little change in the latent heat of fusion and melting temperature after one thousand thermal recycles. Besides, the chemical characteristics and structural profile remained constant after one thousand thermal cycling tests. Therefore, microencapsulated paraffin wax/polyaniline is a stable material that can be used for thermal energy storage systems.
The chitosan/polyvinyl alcohol/TiO2 composite was synthesized. Two different degrees of deacetylation of chitosan were prepared by hydrolysis to compare the effectiveness of them. The composite was analyzed via field emission scanning electron microscopy, Fourier transform infrared, X-ray diffraction, thermal gravimetric analysis, weight loss test and adsorption study. The FTIR and XRD results proved the interaction among chitosan, PVA and TiO2 without any chemical reaction. It was found that, chitosan with higher degree of deacetylation has better stability. Furthermore, it also showed that higher DD of chitosan required less time to reach equilibrium for methyl orange. The adsorption followed the pseudo-second-order kinetic model. The Langmuir and Freundlich isotherm models were fitted well for isotherm study. Adsorption capacity was higher for the composite containing chitosan with higher DD. The dye removal rate was independent of the dye's initial concentration. The adsorption capacity was increased with temperature and it was found from reusability test that the composite containing chitosan with higher DD is more reusable. It was notable that adsorption capacity was even after 15 runs. Therefore, chitosan/PVA/TiO2 composite can be a very useful material for dye removal.
Nanostructured hydrogenated carbon nitride (CNx:H) thin films were synthesized on a crystal silicon substrate at low deposition temperature by radio-frequency plasma-enhanced chemical vapor deposition (PECVD). Methane and nitrogen were the precursor gases used in this deposition process. The effects of N₂ to the total gas flow rate ratio on the formation of CNx:H nanostructures were investigated. Field-emission scanning electron microscopy (FESEM), Auger electron spectroscopy (AES), Raman scattering, and Fourier transform of infrared spectroscopies (FTIR) were used to characterize the films. The atomic nitrogen to carbon ratio and sp² bonds in the film structure showed a strong influence on its growth rate, and its overall structure is strongly influenced by even small changes in the N₂:(N₂ + CH₄) ratio. The formation of fibrous CNx:H nanorod structures occurs at ratios of 0.7 and 0.75, which also shows improved surface hydrophobic characteristic. Analysis showed that significant presence of isonitrile bonds in a more ordered film structure were important criteria contributing to the formation of vertically-aligned nanorods. The hydrophobicity of the CNx:H surface improved with the enhancement in the vertical alignment and uniformity in the distribution of the fibrous nanorod structures.
In this study, the physical, morphological, mechanical and thermal properties of furfuryl alcohol/2-ethylhexyl methacrylate/halloysite nanoclay wood polymer nanocomposites (FA-co-EHMA-HNC WPNCs) were investigated. FA-co-EHMA-HNC WPNCs were prepared via an impregnation method and the properties of the nanocomposites were characterized through the weight percent gain, Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), three-point flexural test, dynamic mechanical thermal analysis (DMTA), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) analysis and moisture absorption test. The weight percent gain in the 50:50 FA-co-EHMA-HNC WPNC was the highest compared with the raw wood (RW) and other WPNCs. The FT-IR results confirmed that polymerization took place in the nanocomposites, especially 50:50 FA-co-EHMA-HNC WPNC, which had a reduced amount of hydroxyl groups. The SEM results revealed that the 50:50 FA-co-EHMA-HNC WPNC had the smoothest and most uniform surface among all of the nanocomposites. The 50:50 FA-co-EHMA-HNC WPNC showed the highest flexural strength and modulus of elasticity. The results revealed that the storage modulus and loss modulus of the FA-co-EHMA-HNC WPNCs were higher and the tan δ of FA-co-EHMA-HNC WNPCs was lower compared with the RW. The FA-co-EHMA-HNC WPNCs exhibited the higher thermal stability in the TGA and DSC analysis. The 50:50 FA-co-EHMA-HNC WPNC exhibited remarkably lower moisture absorption compared with the RW. Overall, this study proved that the ratio 50:50 FA-co-EHMA ratio was the most suitable for introduction in the in the RW.
Solid polymer electrolytes electrolytes based Poly
(ethylene oxide) (PEO) complexed with sodium
trifluoromethanesulfonate (NaCF3SO3
) salt were prepared by
using solution cast technique. Ion-polymer ionic conductivity
and interaction studies have been reported by Electrical
Impedance spectroscopy (EIS) and Fourier transform infrared
spectroscopy (FTIR). FTIR studies suggested that there are
stronger interaction between Na+
ions and the polymer than
interaction of anions cations of the salt. The temperature
dependance electrical conductivity of polymer electrolytes films
follow Arrhenius relation and the low activation energy 0.2993
eV was observed for PEO-18 wt. % NaCF3SO3 below 323 K.
In this study, adsorption behavior of anthill-eggshell composite (AEC) for the removal of hexavalent chromium (Cr6+) from aqueous solution was investigated. The raw AEC sample was thermally treated at 864 °C for 4 h and characterized using Brunauer-Emmett-Teller (BET), scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), and X-ray fluorescence (XRF) techniques. The effects of adsorption process variables including initial Cr6+ concentration, contact time, and adsorbent dosage on the Cr6+ removal efficiency were investigated using central composite design (CCD) of response surface methodology (RSM). Equilibrium adsorption isotherm and kinetic were also studied. From the analysis of variance (ANOVA), the three variables proved to be significant and the optimum conditions for Cr6+ adsorption were obtained to be 150 mg/L initial Cr6+ concentration, 45.04-min contact time, and 0.5 g adsorbent dosage, which resulted in 86.21% of Cr6+ adsorbed. Equilibrium isotherm study showed that Freundlich model fitted well to the experimental data. The pseudo-second-order kinetic model appeared to better describe the experimental data. The study showed that mixed anthill-eggshell is a promising adsorbent for removing Cr6+ from aqueous solution.
Bioactive compounds are one of the natural products used especially for medicinal, pharmaceutical and food application. Increasing research performed on the extraction, isolation and identification of bioactive compounds, however non to date has explored on the identification of flavonoids classes. Therefore, this study was focused on the development of algorithm for rapid identification of flavonoids classes which are flavanone, flavone and flavonol and also their derivatives. Fourier Transform Infrared (FTIR) spectroscopy coupled with multivariate statistical data analysis, which is Principal Component Analysis (PCA) was utilized. The results exhibited that few significant wavenumber range provides the identification and characterization of the flavonoids classes based on PCA algorithm. The study concluded that FTIR coupled with PCA analysis can be used as a molecular fingerprint for rapid identification of flavonoids.
A combination of phosphoric acid (H3PO4) 20% v/v impregnation and carbonization method was employed to convert honeydew rind into activated carbons (ACPHDR) for Zn(II) and Cr(III) removal aqueous solution. The characterization of ACPDHR by N2 sorption, iodine number and Boehm analysis result 1272 m2/g surface area, 1174 mg/g and 1.13 mmol/g total acidic functional groups respectively. Fourier transform infrared (FTIR) and Field emission scanning electron microscopy-electron dispersed microscopy (FESEM-EDX) analysis of unloaded and metal-loaded carbon showed shifted of significance peaks and the changes of surface morphology of the sorbent. The adsorption was optimized at pH, shaking duration, initial metal concentration and mass of adsorbent of 5.5, 40 min and 500 mg/L, 0.4 g for Zn(II) and 4, 40 min, 1000 mg/L, 0.1 g for Cr(III) removal. It is concluded that the metal removal was influenced by pH solution, contact time, initial metal concentration and mass of adsorbent. The highest removal of Zn(II) and Cr(III) was observed at 84.24% and 90.10% respectively. Waste from honeydew will be benefited from this research which offer a cheaper alternative precursor to coal based activated carbons.