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 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 INFRARED SPECTROSCOPY AND MULTIVARIATE CALIBRATION FOR THE RAPID QUANTIFICATION OF FREE FATTY ACID CONTENT IN PANGASIUS HYPOPTHALMUS OIL

2018 ◽  
Vol 10 (6) ◽  
pp. 199
Author(s):  
Lisa Andina ◽  
Revita Saputri ◽  
Aristha Novyra Putri ◽  
Abdul Rohman
Keyword(s):  
Fatty Acid ◽  
Ftir Spectroscopy ◽  
Multivariate Calibration ◽  
Fatty Acid Content ◽  
Principal Component Regression ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Stretching Vibration

Objective: The objective of this study was to evaluate the capability of fourier transform infrared (FTIR) spectroscopy in combination with multivariate calibration for prediction of free fatty acids (FFA) in Pangasius hypopthalmus (P. hypopthalmus) oil.Methods: FFA content in P. hypopthalmus oil was determined by attenuated total reflectance-FTIR spectroscopy. P. hypopthalmus oil derived from Pangasius’s meat (MP), and Pangasius’s liver and fat (LFP) were subjected to heat treatments. Determination of FFA content in P. hypopthalmus oil’s was performed by gas chromatography-flame ionization detector.Results: Oleic acid was found to be the main fatty acid component in P. hypopthalmus oil. FTIR spectra of P. hypopthalmus oil has 3 main peaks, C-H bonds of cis-form of fatty acid showed the stretching vibration, symmetric and asymmetric vibrations of the C-H2 and C-H3 aliphatic group and vibrations of the carbonyl (C=O) ester derived from the oil triacylglycerols. Principal component regression (PCR) model showed a better performance than the partial least square (PLS) model. PCR at wavenumbers of 1200-1000 cm-1 with first derivative treatment was chosen for FFA prediction, which resulted in a coefficient of determination (R2) value of 0.9417, root means square error of calibration (RMSEC) of 0.725%, and root mean square error of prediction (RMSEP) value of 2.40%, respectively.Conclusion: FTIR spectroscopy combined with PCR can be used as an alternative method for analysis of fatty acid contents.

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 Authentication of Patin Fish Oil (Pangasius micronemus) using FTIR Spectroscopy Combined with Chemometrics

2020 ◽  
pp. 23
Author(s):  
Anggita Rosiana Putri ◽  
Abdul Rohman ◽  
Sugeng Riyanto ◽  
Widiastuti Setyaningsih
Keyword(s):  
Root Mean Square Error ◽  
Fish Oil ◽  
Ftir Spectroscopy ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square

Authentication of Patin fish oil (MIP) is essential to prevent adulteration practice, to ensure quality, nutritional value, and product safety. The purpose of this study is to apply the FTIR spectroscopy combined with chemometrics for MIP authentication. The chemometrics method consists of principal component regression (PCR) and partial least square regression (PLSR). PCR and PLSR were used for multivariate calibration, while for grouping the samples using discriminant analysis (DA) method. In this study, corn oil (MJ) was used as an adulterate. Twenty-one mixed samples of MIP and MJ were prepared with the adulterate concentration range of 0-50%. The best authentication model was obtained using the PLSR technique using the first derivative of FTIR spectra at a wavelength of 650-3432 cm-1. The coefficient of determination (R2) for calibration and validation was obtained 0.9995 and 1.0000, respectively. The value of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were 0.397 and 0.189. This study found that the DA method can group the samples with an accuracy of 99.92%.

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.

Nondestructive NIR Reflectance Spectroscopic Method for Rapid Fatty Acid Analysis of Peanut Seeds

2011 ◽  
Vol 38 (2) ◽  
pp. 85-92 ◽  
Author(s):  
Jaya Sundaram ◽  
Chari V. Kandala ◽  
Christopher L. Butts ◽  
Charles Y. Chen ◽  
Victor Sobolev
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Near Infrared ◽  
Methyl Esters ◽  
Spectroscopic Method ◽  
Nondestructive Method ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance

ABSTRACT Near Infrared Reflectance Spectroscopy (NIRS) was used to rapidly and nondestructively analyze the fatty acid concentration present in peanut seeds samples. Absorbance spectra were collected in the wavelength range from 400 nm to 2500 nm using NIRS. The oleic, linoleic and palmitic fatty acids were converted to their corresponding methyl esters and their concentrations were measured using a gas chromatograph (GC). Partial least square (PLS) analysis was performed on a calibration set, and models were developed for prediction of fatty acid concentrations. The best model was selected based on the coefficient of determination (R2), Root Mean Square Error of Prediction, residual percent deviation (RPD) and correlation coefficient percentage between the gas chromatography measured values and the NIR predicted values. The NIR reflectance model developed yielded RPD values of three and above for prediction of the three fatty acids, indicating that this nondestructive method would be suitable for fatty acid predictions in peanut seeds.

Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Khairunnisa Khairunnisa ◽  
Rizka Pitri ◽  
Victor P Butar-Butar ◽  
Agus M Soleh
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Principal Component Regression ◽  
Circulation Model ◽  
Principal Component ◽  
Meteorological Station ◽  
Grid Size ◽  
Partial Least Square ◽  
Least Square ◽  
Output Data

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.

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 Monitoring of Biochemical Compounds and Fatty Acid in Marine Microalgae from the East Coast of Thailand

2018 ◽  
Vol 17 (4) ◽  
pp. 334-347
Author(s):  
Kwanchayanawish MACHANA ◽  
Amonrat KANOKRUNG ◽  
Sirinart SRICHAN ◽  
Boonyadist VONGSAK ◽  
Maliwan KUTAKO ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
East Coast ◽  
Predictive Accuracy ◽  
Partial Least Square ◽  
Least Square ◽  
Biodiesel Production ◽  
Fatty Acid Profiles ◽  
Omega 3 ◽  
Ft Ir

Determinations of fatty acid profiles of five microalgae; Amphora sp., Chaetoceros sp., Melosira sp., Bellerochae sp., and Lithodesmium sp., from the east coast of Thailand were evaluated by conventional Gas Chromatography-Flame Ionization Detector (GC-FID). The results exhibited that the fatty acids suitable for biodiesel production were the most frequent entities encountered in all microalgae profiles. The GC chromatogram of fatty acid profiles in microalgae showed that both Amphora sp. and Chaetoceros sp. comprised essential omega-3 fatty acids, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). Additionally, this study assessed whether Fourier Transform infrared (FT-IR) microspectroscopy could be used to evaluate and monitor the biochemical compositions of microalgae, including lipid, carbohydrate, and protein profiles, by using colorimetric methods. Results showed that FT-IR spectra combined with biochemical values of lipid, carbohydrate, and protein contents were used as predictive models generated by partial least square (PLS) regression. Cross-validation of the lipid, protein, and carbohydrate models showed high degrees of statistical accuracy with RMSECV values of approximately 0.5 - 3.22 %, and a coefficient of regression between the actual and predicted values of lipids, carbohydrates, and proteins were 92.66, 95.73, and 96.43 %, respectively. The RPD values were all high (> 3), indicating good predictive accuracy. This study suggested that FT-IR could be a tool for the simultaneous measurement of microalgae composition of biochemical contents in microalgae cells.

scholarly journals Application of FTIR Spectroscopy and Chemometrics for Halal Authentication of Beef Meatball Adulterated with Dog Meat

2018 ◽  
Vol 18 (2) ◽  
pp. 376 ◽  
Author(s):  
Wiranti Sri Rahayu ◽  
Abdul Rohman ◽  
Sudibyo Martono ◽  
Sudjadi Sudjadi
Keyword(s):  
Ftir Spectroscopy ◽  
Reliable Method ◽  
Cross Validation ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Calibration Model ◽  
Mean Square ◽  
Folch Method ◽  
Halal Authentication

Beef meatball is one of the favorite meat-based food products among Indonesian community. Currently, beef is very expensive in Indonesian market compared to other common meat types such as chicken and lamb. This situation has intrigued some unethical meatball producers to replace or adulterate beef with lower priced-meat like dog meat. The objective of this study was to evaluate the capability of FTIR spectroscopy combined with chemometrics for identification and quantification of dog meat (DM) in beef meatball (BM). Meatball samples were prepared by adding DM into BM ingredients in the range of 0–100% wt/wt and were subjected to extraction using Folch method. Lipid extracts obtained from the samples were scanned using FTIR spectrophotometer at 4000–650 cm-1. Partial least square (PLS) calibration was used to quantify DM in the meatball. The results showed that combined frequency regions of 1782–1623 cm-1 and 1485-659 cm-1 using detrending treatment gave optimum prediction of DM in BM. Coefficient of determination (R2) for correlation between the actual value of DM and FTIR predicted value was 0.993 in calibration model and 0.995 in validation model. The root mean square error of calibration (RMSEC) and standard error of cross validation (SECV) were 1.63% and 2.68%, respectively. FTIR spectroscopy combined with multivariate analysis can serve as an accurate and reliable method for analysis of DM in meatball.

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