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 Application of FTIR spectroscopy coupled with chemometrics for authentication ofNigella sativaseed oil

2011 ◽  
Vol 25 (5) ◽  
pp. 243-250 ◽  
Author(s):  
A. F. Nurrulhidayah ◽  
Y. B. Che Man ◽  
H. A. Al-Kahtani ◽  
A. Rohman
Keyword(s):  
Ftir Spectroscopy ◽  
Seed Oil ◽  
Cross Validation ◽  
Multivariate Calibration ◽  
Nigella Sativa ◽  
Grape Seed ◽  
Partial Least Square ◽  
Least Square ◽  
Grape Seed Oil ◽  
The Relationship

The present study is intended to analyze the presence of grape seed oil (GSO) inNigella sativaL. seed oil (NSO) using Fourier transform infrared (FTIR) spectroscopy and gas chromatography (GC). FTIR spectroscopy coupled with multivariate calibration of partial least square can quantify the levels of GSO in NSO at wavelength number of 1114–1074, 1734–1382 and 3005–3030 cm–1. The coefficient of correlation (R2) obtained for the relationship between actual (x-axis) and FTIR predicted (y-axis) values are 0.981. The errors in cross validation and in prediction are 2.34% (v/v) and 2.37% (v/v), respectively.

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 FTIR spectroscopy and chemometrics for authentication of essential oil of Curcuma mangga from candle nut oil

Food Research ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 515-521 ◽  
Author(s):  
M. Khudzaifi ◽  
S.S. Retno ◽  
Abdul Rohman
Keyword(s):  
Discriminant Analysis ◽  
Essential Oil ◽  
Ftir Spectroscopy ◽  
Prediction Models ◽  
Multivariate Calibration ◽  
Ftir Spectra ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
High Price

The adulteration of high price oil such as essential oil of Curcuma mangga Val. (EOCM) with lower price oil is common to get economical profit. This study was to investigate the authentication of EOCM toward candlenut oil (CNO) using FTIR spectroscopy combined with multivariate calibration and discriminant analysis. The selection of CNO as adulterant oil model was due to its close similarity to EOCM in terms of FTIR spectra. Besides, EOCM has similar color with CNO, therefore, CNO is potential adulterant toward EOCM. Two multivariate calibrations of partial least square regression (PLSR) and principle component regression (PCR) along with FTIR spectra (normal versus derivatization) were optimized to get prediction models for quantification. The results showed that the combination of PLSR and normal FTIR spectra at optimized wavenumbers of 1614-1068 cm-1 was capable of predicting the levels of EOCM adulterated with CNO. Discriminant analysis was also success to differentiate the classification of EOCM and EOCM adulterated with CNO with accuracy levels of 100%. Using FTIR spectroscopy for oil authentication is rapid, simple without any chemicals, solvents, and sample preparation so that this technique is considered as a green analytical method.

Identification and Quantification of Metamizole in Traditional Herbal Medicines using Spectroscopy FTIR-ATR combined with Chemometrics

2021 ◽  
pp. 4413-4419
Author(s):  
Dharmastuti Cahya Fatmarahmi ◽  
Ratna Asmah Susidarti ◽  
Respati Tri Swasono ◽  
Abdul Rohman
Keyword(s):  
Discriminant Analysis ◽  
Herbal Medicine ◽  
Ftir Spectroscopy ◽  
Herbal Medicines ◽  
Principal Component ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Precision Data

The study aims to develop an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu. Jamu powders, Metamizole, and the binary mixture of Jamu and Metamizole were measured using FTIR-ATR at the mid-infrared region (4000-650 cm-1). The obtained spectra profiles were further analyzed by Principal Component Analysis, Partial Least Square Regression, Principal Component Regression, and Discriminant Analysis. Jamu Pegel Linu (JPL), Jamu Encok (JE), Jamu Sakit Pinggang (JSP), Metamizole (M), and adulterated Jamu by Metamizole were discriminated well on PCA score plot. PLSR and PCR showed the accuracy and precision data to quantify JPL, JE, and JSP, and each adulterated by M with R2 value > 0,995 and low value of RMSEC and RMSEP. Discriminant Analysis (DA) was successfully grouping Jamu and Metamizole without any misclassification. A combination of FTIR spectroscopy and chemometrics offered useful tools for detecting Metamizole in traditional herbal medicine.

scholarly journals THE AUTHENTICATION OF VIRGIN COCONUT OIL FROM GRAPE SEED OIL AND SOYBEAN OIL USING FTIR SPECTROSCOPY AND CHEMOMETRICS

2019 ◽  
pp. 259-263 ◽  
Author(s):  
ABDUL ROHMAN ◽  
YAAKOB BIN CHE MAN ◽  
MD. EAKUB ALI
Keyword(s):  
Soybean Oil ◽  
Ftir Spectroscopy ◽  
Seed Oil ◽  
Multivariate Calibration ◽  
Coconut Oil ◽  
Grape Seed ◽  
Mean Square ◽  
Virgin Coconut Oil ◽  
Grape Seed Oil

Objective: The objective of this study was to develop Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and discriminant analysis (DA) for the authentication of virgin coconut oil (VCO) from grape seed oil (GSO) and soybean oil (SO). Methods: FTIR spectra of VCO, GSO, SO and its binary mixture of VCO-SO, and VCO-GSO were scanned at mid-infrared region (4000-650 cm-1) using attenuated total reflectance technique. The wavenumbers were selected based on its capability to provide the best prediction models for quantification and classification of adulterants in VCO assisted by multivariate calibrations and DA, respectively. Results: The results showed that partial least square (PLS) calibration using absorbance values at combined wavenumbers of 1200-900 and 3027-2985 cm-1 revealed reliable method for quantification of GSO in VCO, as indicated by high value of coefficient of determination (R2) and low value of root mean square of calibration (RMSEC) and root mean square error of prediction (RMSEP). PLS using FTIR spectra at the combined wavenumbers of 1200-1000 and 3025-2995 cm-1 was suitable for quantitative analysis of SO in VCO. DAwas also successfully used for classification of VCO and VCO added with adulterants of GSO and SO. Conclusion: FTIR spectroscopy in combination with chemometrics of multivariate calibration and DA offered effective tools for the authentication of VCO

scholarly journals Application of FTIR Spectroscopy and HPLC Combined with Multivariate Calibration for Analysis of Xanthones in Mangosteen Extracts

2020 ◽  
Vol 88 (3) ◽  
pp. 35
Author(s):  
Endjang Prebawa Tejamukti ◽  
Widiastuti Setyaningsih ◽  
Irnawati ◽  
Budiman Yasir ◽  
Gemini Alam ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Ethanolic Extract ◽  
Ftir Spectra ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Garcinia Mangostana

Mangosteen, or Garcinia mangostana L., has merged as an emerging fruit to be investigated due to its active compounds, especially xanthone derivatives such as α -mangostin (AM), γ-mangostin (GM), and gartanin (GT). These compounds had been reported to exert some pharmacological activities, such as antioxidant and anti-inflammatory, therefore, the development of an analytical method capable of quantifying these compounds should be investigated. The aim of this study was to determine the correlation between FTIR spectra and HPLC chromatogram, combined with chemometrics for quantitative analysis of ethanolic extract of mangosteen. The ethanolic extract of mangosteen pericarp was prepared using the maceration technique, and the obtained extract was subjected to measurement using instruments of FTIR spectrophotometer at wavenumbers of 4000–650 cm−1 and HPLC, using a PDA detector at 281 nm. The data acquired were subjected to chemometrics analysis of partial least square (PLS) and principal component regression (PCR). The result showed that the wavenumber regions of 3700–2700 cm−1 offered a reliable method for quantitative analysis of GM with coefficient of determination (R2) 0.9573 in calibration and 0.8134 in validation models, along with RMSEC value of 0.0487% and RMSEP value 0.120%. FTIR spectra using the second derivatives at wavenumber 3700–663 cm−1 with coefficient of determination (R2) >0.99 in calibration and validation models, along with the lowest RMSEC value and RMSEP value, were used for quantitative analysis of GT and AM, respectively. It can be concluded that FTIR spectra combined with multivariate are accurate and precise for the analysis of xanthones.

scholarly journals COMPARATIVE STUDY OF FATTY ACID PROFILES IN PATIN (PANGASIUS MICRONEMUS) AND GABUS (CHANNA STRIATA) FISH OIL AND ITS AUTHENTICATION USING FTIR SPECTROSCOPY COMBINED WITH CHEMOMETRICS

2019 ◽  
pp. 55-60
Author(s):  
ANGGITA ROSIANA PUTRI ◽  
ABDUL ROHMAN ◽  
SUGENG RIYANTO
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Fish Oil ◽  
Ftir Spectroscopy ◽  
Principal Component Regression ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Channa Striata

Objective: The aims of this research were to analyse the fatty acids contained in Patin (Pangasius micronemus) and Gabus (Channa striata) fish oils also its authentication using FTIR spectroscopy combined with chemometrics. Methods: Patin fish oil (PFO) was extracted from patin flesh using the maceration method with petroleum benzene as the solvent, while gabus fish oil (GFO) was purchased from the market in Yogyakarta. The analysis of fatty acid was done using gas chromatography–flame ionization detector (GC-FID). The authentication was performed using FTIR spectrophotometer and chemometrics methods. Principal component analysis (PCA) was used to determine the proximity of oils based on the characteristic similarity. The quantification of adulterated PFO was performed using multivariate calibrations, partial least square (PLS) and principal component regression (PCR). The classification between authentic oils and those adulterated used discriminant analysis (DA). Results: The level of saturated and polyunsaturated fatty acids in PFO is higher than in GFO. The PLS and PCR methods using the second derivative spectra at wavenumbers of 666–3050 cm-1 offered the highest values of coefficient of determination (R2) and lowest root means the square error of calibration (RMSEC) and root mean square error of prediction (RMSEP). Conclusion: The PCA method was successfully used to determine the proximity of oils. Among oils studied, PFO has a similarity fatty acid composition with GFO. The DA method was able to screen pure PFO from adulterated PFO without any misclassification reported. FTIR spectroscopy in combined with chemometrics can be used for authentication and quantification.

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.

Quality Detection of Soybean Oil with Voltammetric Electronic Tongue

2013 ◽  
Vol 680 ◽  
pp. 333-338
Author(s):  
Hong Men ◽  
Cai Wa Zhang ◽  
Yan Ping Zhang ◽  
Hong Hui Gao
Keyword(s):  
Soybean Oil ◽  
Prediction Models ◽  
Electronic Tongue ◽  
Principal Component ◽  
Sample Pretreatment ◽  
Electrode System ◽  
Partial Least Square ◽  
Least Square ◽  
Kernel Principal Component Analysis ◽  
Voltammetric Electronic Tongue

This paper proposes a reasonable methodology applied in classification and quantification techniques based on the voltammetric electronic tongue. We designed voltammetric electronic tongue oil sample pretreatment system with petroleum ether organic solvent. Through three-electrode system and cyclic voltammetry method processing blending soybean oil sample to get waveform output. Extracting crest methods as its feature extraction Pattern recognition use kernel principal component analysis and factor analysis blending on a different level of soybean oil, Partial Least Square (PLS) techniques was applied for data management and prediction models building, the prediction models are the blending ratio, the results show that voltammetric electron tongue can distinguish the quality of soybean oil.

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