scholarly journals Analysis of Adulterated Pangasius Hypopthalmus Oil by ATR-FTIR Spectroscopy and Chemometric

2019 ◽  
pp. 4
Author(s):  
Lisa Andina ◽  
Revita Saputri ◽  
Aristha Novyra Putri ◽  
Endang Lukitaningsih ◽  
Abdul Rohman
Keyword(s):  
Quantitative Analysis ◽  
Ftir Spectroscopy ◽  
Palm Oil ◽  
Coconut Oil ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
First Derivative ◽  
Derivative Spectra

In this recent study, ATR-FTIR spectroscopy and chemometrics have been successfully used for theclassification and quantitative analysis of adulterated Pangasius Hypopthalmus (P. hypopthalmus) oil. The aimof this research was to evaluate the ability of ATR-FTIR spectroscopy and chemometric to perform theclassification and quantitative analysis of adulterated P. hypopthalmus oil in a binary mixture with palm oil(PO) and coconut oil (CO). In the development of FTIR spectroscopy combined with chemometrics for theclassification and quantitative analysis of P. hypopthalmus oil, P. hypopthalmus oil (MP and LFP) mixed withother oils such as coconut oil (CO) and palm oil (PO) at concentrations of 1-99% v/v. Classification of P.hypopthalmus oil, PO and CO were performed by the principal component analysis (PCA) and thequantification analysis was carried out by partial least square (PLS). Based on the optimization process, thebest classification results were obtained using the first derivative spectra at wave numbers of 1400-1100 cm-1.The prediction of percentage adulterated oil by PLS method also showed very good values of R2 greater than0.9999 and low standard error values in the range of 0.0176-0.703. The prediction was also perform at1400-1100 cm-1 wavenumbers using the first derivative spectra.

scholarly journals AUTHENTICATION OF PATIN (PANGASIUS MICRONEMUS) FISH OIL ADULTERATED WITH PALM OIL USING FTIR SPECTROSCOPY COMBINED WITH CHEMOMETRICS

2019 ◽  
pp. 195-199
Author(s):  
Anggita Rosiana Putri ◽  
Abdul Rohman ◽  
SUGENG RIYANTO
Keyword(s):  
Fish Oil ◽  
Ftir Spectroscopy ◽  
Palm Oil ◽  
Multivariate Calibration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Reliable Technique ◽  
Accuracy Level

Objective: The goal of this research was to perform authentication of patin (Pangasius micronemus) fish oil (PFO) adulterated with palm oil (PO) using FTIR spectroscopy combined with chemometrics method. Methods: Patin fish oil (PFO) and PFO adulterated with palm oil (PO) were measured using FTIR instrument at wavenumbers region of 4000–650 cm-1. The chemometrics methods, namely multivariate calibration of partial least square (PLS) and principal component regression (PCR) were used to make calibration and validation models during quantification. Discriminant analysis (DA) was used to make grouping pure PFO and PFO adulterated with PO. Results: The results showed that PLS and PCR could be used to quantify PO as adulterant in PFO, either in calibration or validation models. FTIR spectroscopy combined with multivariate calibration offered accurate and precise method for quantitative analysis with R2 value of >0.999 and low RMSEC and RMSEP. DA was capable of grouping PFO and PFO adulterated with PO with an accuracy level of 100%. Conclusion: FTIR spectroscopy combined with chemometrics could be reliable technique for quantification and discrimination of PFO and PFO adulterated with PO.

scholarly journals Adulteration of Gabus (Channa striata) fish oil with corn oil and palm oil: the use of FTIR spectra and chemometrics

Food Research ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 184-190
Author(s):  
Irnawati ◽  
S. Riyanto ◽  
A. Rohman
Keyword(s):  
Quantitative Analysis ◽  
Discriminant Analysis ◽  
Fish Oil ◽  
Palm Oil ◽  
Corn Oil ◽  
Ternary Mixtures ◽  
Calibration And Validation ◽  
First Derivative ◽  
Derivative Spectra

The adulteration practice in fats and oils industry can be in the form of addition or substitution high quality oils such as Gabus Fish oil (GFO) with lower price oils. This research highlighted the application of FTIR spectroscopy combined with multivariate calibrations and discriminant analysis (DA) for quantitative analysis and classification of oil adulterants of palm oil (PO) and corn oil (CO) in GFO. The methods involved preparation of training/calibration and validation samples, scanning of samples using FTIR spectrophotometer using attenuated total reflectance, development of calibration and validation models for quantitative analysis of oil adulterants assisted with multivariate calibrations and classification between genuine GFO and GFO adulterated with PO and CO using discriminant analysis. The quantitative analysis of PO in ternary mixtures with CO as an adulterant in GFO was carried out using first derivative spectra at wavenumbers of 3200-600 cm-1 assisted with partial least square (PLS), while quantitative analysis of CO in ternary mixture with PO and GFO was performed using first derivative spectra at wavenumbers region of 3200-2700 cm-1 assisted with principle component regression (PCR). The R2 values for the correlation between actual and predicted values of PO and CO in ternary mixtures either in calibration or prediction samples were of > 0.97 with low errors. In addition, DA using the same wavenumbers region as used in the quantitative analysis could classify or discriminate genuine GFO and GFO mixed/adulterated with PO and CO with an accuracy level of 100%. FTIR spectroscopy using suitable wavenumbers region combined with PLS, PCR and DA could be proposed as analytical tools for quantification and classification of oil adulterants in GFO.

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 APPLICATION OF KERNEL PARTIAL LEAST SQUARE FEATURE EXTRACTION TO QUANTITATIVE ANALYSIS OF FTIR SPECTROSCOPY OF MULTI COMPONENT GAS MIXTURE

2009 ◽  
Vol 28 (2) ◽  
pp. 115-118 ◽  
Author(s):  
Hui-Min HAO ◽  
Cong-Ming Qiao ◽  
Xiao-Jun TANG ◽  
Jun-Hua LIU
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Ftir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Gas Mixture

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 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 PENERAPAN KEMOMETRIK PADA METODE CITRA DIGITAL UNTUK ANALISIS ION MERKURI (II) DENGAN INDIKATOR NANOPARTIKEL PERAK

Alotrop ◽  
2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Angga Aprian Dinata ◽  
M. Lutfi Firdaus ◽  
Rina Elvia
Keyword(s):  
Quantitative Analysis ◽  
Digital Image ◽  
Limit Of Detection ◽  
Principal Component Regression ◽  
Image Data ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Image Method ◽  
Rgb Values

Digital image method in quantitative analysis usually uses one of the RGB primary color components (Red, Green, Blue), so that not all digital image data can be extracted. Then needed a method that can render the whole RGB values as variables in quantitative analysis are known as chemometric. This research aims to know the influence of the application of chemometric against the sensitivity of the digital image. Chemometry method used is the Principal Component Regression (PCR) and Partial Least Square (PLS) using Unscramber X software from Camo software, USA.. This method is applied for the quantitative analysis of Mercury (II) ion with silver nanoparticles (NPP) immobilization on filter paper indicator. The research results showed that chemometric has a good influence against the level of the Limit of Detection (LOD) of the digital image, where the level of LOD with chemometric application of the Principal Component Regression (PCR) is 0.4311 ppb, and Partial Least Square (PLS) is  0.4310 ppb smaller than without the application of chemometric Single Linear Regression (SLR) at 0.837 ppb. 

Sign in / Sign up

Export Citation Format

Share Document