scholarly journals FTIR Spectroscopy Combined with Partial Least Square for Analysis of Red Fruit Oil in Ternary Mixture System

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
A. Rohman ◽  
Dwi Larasati Setyaningrum ◽  
Sugeng Riyanto
Keyword(s):  
Ftir Spectroscopy ◽  
Ternary Mixture ◽  
Edible Oils ◽  
Ftir Spectra ◽  
Partial Least Square ◽  
Least Square ◽  
Reliable Technique ◽  
Fruit Oil ◽  
Mixture System

FTIR spectroscopy is a promising method for quantification of edible oils. Three edible oils, namely, red fruit oil (RFO), corn oil (CO), and soybean oil (SO), in ternary mixture system were quantitatively analyzed using FTIR spectroscopy in combination with partial least square (PLS). FTIR spectra of edible oils in ternary mixture were subjected to several treatments including normal spectra and their derivative. Using PLS calibration, the first derivative FTIR spectra can be exploited for determination of RFO; meanwhile, the second derivative spectra were preferred for determination of CO and SO. The R2 values obtained for the relationship between actual and FTIR predicted values of RFO, CO, and SO were 0.9863, 0.9276, and 0.9693, respectively. The root mean square error of calibration (RMSEC) values obtained were 1.59, 1.72, and 1.60% (v/v) for RFO, CO, and SO, respectively. The result showed that FTIR spectroscopy offers accurate and reliable technique for quantitative analysis of RFO, CO, and SO simultaneously in ternary mixture systems. Besides, the developed method can be extended for analysis of CO and SO as adulterants in RFO.

scholarly journals ANALYSIS OF PALM OIL AS OIL ADULTERANT IN OLIVE AND PUMPKIN SEED OILS IN TERNARY MIXTURE SYSTEMS USING FTIR SPECTROSCOPY AND CHEMOMETRICS

2019 ◽  
pp. 210-215 ◽  
Author(s):  
IRNAWATI ◽  
RIYANTO S. ◽  
MARTONO S. ◽  
ROHMAN A.
Keyword(s):  
Ftir Spectroscopy ◽  
Palm Oil ◽  
Ternary Mixture ◽  
Prediction Models ◽  
Virgin Olive Oil ◽  
Ftir Spectra ◽  
Partial Least Square ◽  
Least Square ◽  
Ternary Mixtures ◽  
Pumpkin Seed

Objective: The study was designed to develop Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics techniques of multivariate calibration and discriminant analysis (DA) for analysis of palm oil in a ternary mixture with EVOO and PSO. Methods: FTIR spectra of pure palm oil (PO), extra virgin olive oil (EVOO), pumpkin seed oil (PSO) and its ternary mixtures randomly prepared were scanned using FTIR spectrophotometer at wavenumbers of 4000-650 cm-1 corresponding to mid-infrared region, with resolution of 8 cm-1 and 32 scanning using sampling technique of attenuated total reflectance (ATR). Two calibrations in multivariate models, namely principle component (PCR) and partial least square (PLS) regressions were used to facilitate quantification of PO. Results: The PLS using first derivative FTIR–ATR spectra at 3100-2750 combined with 1500-663 cm-1 showed the best prediction models for quantification of PO in ternary mixtures with EVOO and PSO. Using this condition, correlation coefficient (R) values for the relationship between actual values and FTIR predicted values of 0.9967 and 0.9906 were achieved in calibration and validation models, respectively. The errors in calibration and prediction models, expressed by RMSEC and RMSEP, were low, i.e. 0.0080% and 0.0152%, respectively. DA using absorbance values at the same wavenumbers also offered the optimum discrimination model for discrimination between PO and PO mixed with EVOO and PSO in ternary mixtures. Conclusion: This result concluded that FTIR spectra in conjunction with DA (for classification) and PLS (for quantification) is fast and accurate tools during the analysis of PO as oil adulterant in EVOO and PSO.

scholarly journals The employment of Fourier Transform Infrared Spectroscopy (FTIR) and chemometrics for analysis of candlenut oil in binary mixture with grape seed oil

Food Research ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 184-190
Author(s):  
A.B. Riyanta ◽  
S. Riyanto ◽  
E. Lukitaningsih ◽  
Abdul Rohman
Keyword(s):  
Ftir Spectroscopy ◽  
Seed Oil ◽  
Prediction Models ◽  
Principal Component ◽  
Analytical Techniques ◽  
Grape Seed ◽  
Ftir Spectra ◽  
Partial Least Square ◽  
Least Square ◽  
Grape Seed Oil

Candlenut oil (CDO) is the target of adulteration with other plant oils to get economical profits, therefore, reliable analytical techniques should be developed. Based on the principal component analysis (PCA), grape seed oil (GSO) has the close similarity with CDO. Therefore, this study was intended to make modelling in the authentication analysis of CDO from GSO using Fourier transformed infrared (FTIR) spectroscopy in combination with chemometrics of partial least square calibration (PLSR) and discriminant analysis (DA). FTIR spectra of CDO, GSO and its binary mixtures were subjected to FTIR spectral measurement at wavenumbers of 4000-650 cm-1 , and its absorbances were used for modelling of PLSR and DA. FTIR spectra were also subjected to pre-processing including Savitzy-Golay derivatization. The optimization results showed that FTIR spectra using second derivative at the combined wavenumbers of 3000-2800 and 1600-650 cm-1 offered the optimum models. The coefficient determination (R2 ) for the relationship between actual values and FTIR predicted values was 0.9996 and 0.9975 in calibration and internal validation (prediction) models, respectively. The errors in calibration and validation were relatively low, i.e. 0.84% and 2.19 %vol/vol, respectively. Using the same FTIR spectra, DA could discriminate pure CDO and that mixed with GSO at concentration range of 1-50%vol/vol. The combination of FTIR spectroscopy and chemometrics offered effective tools for the quantification and discrimination of CDO mixed with GSO with the main advantage of its simplicity and rapidity.

scholarly journals Attenuated Total Reflectance-FTIR Spectra Combined with Multivariate Calibration and Discrimination Analysis for Analysis of Patchouli Oil Adulteration

2019 ◽  
Vol 20 (1) ◽  
pp. 1
Author(s):  
Zaki Fahmi ◽  
Mudasir Mudasir ◽  
Abdul Rohman
Keyword(s):  
Root Mean Square Error ◽  
Ftir Spectroscopy ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Multivariate Calibration ◽  
Ftir Spectra ◽  
Partial Least Square ◽  
Least Square ◽  
Calibration Model ◽  
Mean Square

The adulteration of high priced oils such as patchouli oil with lower price ones is motivated to gain the economical profits. The aim of this study was to use FTIR spectroscopy combined with chemometrics for the authentication of patchouli oil (PaO) in the mixtures with Castor Oil (CO) and Palm Oil (PO). The FTIR spectra of PaO and various vegetable oils were scanned at mid infrared region (4000–650 cm–1), and were subjected to principal component analysis (PCA). Quantitative analysis of PaO adulterated with CO and PO were carried out with multivariate calibration of Partial Least Square (PLS) regression. Based on PCA, PaO has the close similarity to CO and PO. From the optimization results, FTIR normal spectra in the combined wavenumbers of 1200–1000 and 3100–2900 cm–1 were chosen to quantify PaO in PO with coefficient of determination (R2) value of 0.9856 and root mean square error of calibration (RMSEC) of 4.57% in calibration model. In addition, R2 and root mean square error of prediction (RMSEP) values of 0.9984 and 1.79% were obtained during validation, respectively. The normal spectra in the wavenumbers region of 1200–1000 cm–1 were preferred to quantify PaO in CO with R2 value of 0.9816 and RMSEC of 6.89% in calibration, while in validation model, the R2 value of 0.9974 and RMSEP of 2.57% were obtained. Discriminant analysis was also successfully used for classification of PaO and PaO adulterated with PO and CO without misclassification observed. The combination of FTIR spectroscopy and chemometrics provided an appropriate model for authentication study of PaO adulterated with PO and CO.

scholarly journals A NEW METHOD FOR THE DETERMINATION OF TOXIC DYE USING FTIR SPECTROSCOPY

2010 ◽  
Vol 9 (2) ◽  
pp. 27-38 ◽  
Author(s):  
Mohammad Elwathig Saeed Mirghani ◽  
Nassereldeen A. Kabbashi ◽  
Isam Y. Qudsieh ◽  
Faiz A. Elfaki
Keyword(s):  
Ftir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
New Method ◽  
Calibration Model ◽  
Chemical Methods ◽  
Toxic Dyes ◽  
Wet Chemical ◽  
The Difference

A new method was developed to determine toxic dyes content in textileand other products using Fourier Transform Infrared (FTIR) spectroscopy withAttenuated Total Reflectance (ATR) element and KBr transmission cell. Thewavelengths used were selected using pure dyes and dye mixtures. Transmittance valuesfrom the wavelengths regions 3500 – 2650 and 1675 – 1500 cm-1 and partial least square(PLS) regression method were used to derive FTIR spectroscopic calibration model fordyes containing –N=N– in their structure. The coefficient of determinations (R2) for themodels were computed by comparing the results obtained from FTIR spectroscopyagainst the actual values of the dyes concentrations. R2 were 0.9321 and 0.9819 for twosamples of toxic dyes respectively. The standard errors (SE) of calibrations were 1.84and 1.36 respectively. The calibration model was cross validated within the same set ofsamples and the standard deviation (SD) of the difference for repeatability and accuracyof the FTIR method were determined. With its speed and ease of data manipulation,FTIR spectroscopy is a useful alternative method to wet chemical methods for rapid androutine detection of azo dyes as toxic dyes in such products for quality control.

scholarly journals Determination of acid, peroxide, and saponification value in patin fish oil by FTIR spectroscopy combined with chemometrics

Food Research ◽  
2020 ◽  
Vol 4 (5) ◽  
pp. 1758-1766
Author(s):  
A.R. Putri ◽  
A. Rohman ◽  
W. Setyaningsih ◽  
S. Riyanto
Keyword(s):  
Fish Oil ◽  
Ftir Spectroscopy ◽  
Principal Component Regression ◽  
Principal Component ◽  
Acid Value ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Saponification Value

Simple, rapid, and reproducible methods for determining the acid value (AV), peroxide value (PV), and saponification value (SV) of patin fish oil (PFO) were developed using Fourier Transform Infrared (FTIR) spectroscopy combined with chemometrics of Principal Component Regression (PCR) and Partial Least Square (PLS). The relationship between actual values was determined using AOCS method and predicted value was determined with FTIR spectroscopy and chemometrics. From the validation work, the high coefficient of determination (R2 ) reached up to > 0.99. This study concluded that by means of FTIR spectra that combined with PCR and PLS technique can be used to determine AV, PV, and SV of PFO.

scholarly journals Identification and quantification of additives in bituminous binders based on FTIR spectroscopy and multivariate analysis methods

2021 ◽  
Vol 54 (4) ◽  
Author(s):  
Sandra Weigel ◽  
Michael Gehrke ◽  
Christoph Recknagel ◽  
Dietmar A. Stephan
Keyword(s):  
Ftir Spectroscopy ◽  
Climatic Conditions ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Linear Discriminant ◽  
Bituminous Binders ◽  
Identification And Quantification

AbstractBitumen is a crucial building material in road construction, which is exposed to continuously higher stresses due to higher traffic loads and changing climatic conditions. Therefore, various additives are increasingly being added to the bitumen complicating the characterisation of the bituminous binder, especially concerning the reuse of reclaimed asphalt. Therefore, this work aimed to demonstrate that the combination of Fourier transform infrared (FTIR) spectroscopy with attenuated total reflexion (ATR) technique and multivariate evaluation is a very well-suited method to reliable identify and quantify additives in bituminous binders. For this purpose, various unmodified and modified binders, directly and extracted from laboratory and reclaimed asphalts, were investigated with FTIR-ATR spectroscopy. The determined spectra, pre-processed by standard normal variate (SNV) transformation and the determination of the 1st derivation, were evaluated using factor analysis (FA), linear discriminant analysis (LDA) and partial least square regression (PLSR). With this multivariate evaluation, first, a significant model with a very high hit rate of over 90% was developed allowing for the identification of styrene-butadiene copolymers (SBC), ethylene-copolymer bitumen (ECB) and different waxes (e.g. amide and Fischer-Tropsch wax) even if the additives do not show any additional peaks or the samples are multi-modified. Second, a quantification of the content is possible for SBC, ECB, and amide wax with a mean error of RMSE ≤ 0.4 wt% and a coefficient of determination of R2 > 90%. Based on these results, FTIR identification and quantification of additives in bituminous binders is a very promising method with a great potential.

scholarly journals Determination of extra virgin olive oil in quaternary mixture using FTIR spectroscopy and multivariate calibration

2011 ◽  
Vol 26 (3) ◽  
pp. 203-211 ◽  
Author(s):  
Abdul Rohman ◽  
Y. B. Che Man
Keyword(s):  
Root Mean Square Error ◽  
Olive Oil ◽  
Ftir Spectroscopy ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Partial Least Square ◽  
Least Square ◽  
Mean Square ◽  
Quaternary Mixture

The purpose of this study was to optimize Fourier transform infrared (FTIR) spectroscopy in combination with multivariate calibrations (partial least square and principle component regression) for determination of extra virgin olive oil (EVOO) in quaternary mixture systems with grape seed oil (GSO), rice bran oil (RBO) and walnut oil (WO). FTIR spectra of EVOO in quaternary mixtures were subjected to several treatments including mean centering (MC), standard normal variate, and spectra derivatives. The combined frequency regions of 1200–900 and 2949–2885 cm–1were used for determination of EVOO. Using partial least square calibration, FTIR normal spectra treated with MC model give the highest values of coefficient of determination (R2) and the lowest values of root mean square error of calibration (RMSEC). TheR2value obtained for the relationship between actual and FTIR predicted value of EVOO was >0.99 with RMSEC value of 1.55% (v/v). The developed PLS model was further used to calculate EVOO in prediction samples, and the root mean square error of prediction obtained was 3.65% (v/v).

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