scholarly journals SB-ATR FTIR Spectroscopic Monitoring of Free Fatty Acids in Commercially AvailableNigella sativa(Kalonji) Oil

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
S. A. Mahesar ◽  
Aftab A. Kandhro ◽  
Abdul Rauf Khaskheli ◽  
M. Y. Talpur ◽  
S. T. H. Sherazi
Keyword(s):  
Fatty Acids ◽  
Free Fatty Acids ◽  
Ftir Spectroscopy ◽  
Nigella Sativa ◽  
Partial Least Square ◽  
Least Square ◽  
Attenuated Total Reflectance ◽  
Calibration Model ◽  
Absorption Region ◽  
Spectroscopic Monitoring

Free fatty acids (FFA) inNigella sativa(N. sativa) commercial and seed oil were determined using single-bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy. Gravimetrical mixing was done by adding 0.1–40% oleic acids in neutralizedN. sativaoil containing 0.1% FFA. FTIR spectroscopy technique and partial least square (PLS) calibration were used to detect the absorption region of carbonyl (C=O) which is in the range of 1690–1727 cm−1. The results of PLS calibration model and root mean square error of calibration (RMSEC) are 0.999 and 0.449, respectively. Comparing the FFA obtained inN. sativaoil by using FTIR with the FFA obtained using AOCS titrimetric method shows a positive correlation and confirms that the described method is a useful procedure.

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.

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.

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 The optimization of FTIR spectroscopy combined with partial least square for analysis of animal fats in quartenary mixtures

2011 ◽  
Vol 25 (3-4) ◽  
pp. 169-176 ◽  
Author(s):  
Abdul Rohman ◽  
Yaakob B. Che Man
Keyword(s):  
Ftir Spectroscopy ◽  
Multivariate Calibration ◽  
Infrared Region ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Attenuated Total Reflectance ◽  
Analytical Technique ◽  
Animal Fats ◽  
Handling Technique

Four types of animal fats, namely lard (LD) and body fats of lamb (LBF), cow (Cow-BF) and chicken (Ch-BF), in quaternary mixtures were quantitatively analyzed using FTIR spectroscopy in combination with multivariate calibration of partial least square (PLS). The animal fats, either individual or in quaternary mixtures, were subjected to horizontal total attenuated total reflectance (HATR) as sample handling technique and scanned at mid-infrared region (4000–650 cm–1) with resolution of 4 cm–1and with 32 interferograms. PLS calibration revealed that the first derivative FTIR spectrum was well suited for the correlation between actual value of LD and FTIR calculated value. The other animal fats (LBF, Cow-BF and Ch-BF) were better determined using normal FTIR spectra. The coefficient of determination (R2) obtained using the optimized spectral treatments was higher than 0.99. The root mean standard error of calibration (RMSEC) values obtained were in the range of 0.773–1.55. Analysis of animal fats using FTIR spectroscopy allows rapid, no excessive sample preparation, and can be regarded as “green analytical technique” due to the absence of solvent and chemical reagent used during the analysis.

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.

Field Nitrogen Dioxide and Ozone Monitoring Using Electrochemical Sensors with Partial Least Squares Regression

2021 ◽  
Vol 5 (1) ◽  
pp. 61
Author(s):  
Rachid Laref ◽  
Etienne Losson ◽  
Alexandre Sava ◽  
Maryam Siadat
Keyword(s):  
Nitrogen Dioxide ◽  
Electrochemical Sensors ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Calibration Model ◽  
Least Squares Regression ◽  
Monitoring Networks ◽  
Concentration Estimation ◽  
The Impact

Low-cost gas sensors detect pollutants gas at the parts-per-billion level and may be installed in small devices to densify air quality monitoring networks for the spread analysis of pollutants around an emissive source. However, these sensors suffer from several issues such as the impact of environmental factors and cross-interfering gases. For instance, the ozone (O3) electrochemical sensor senses nitrogen dioxide (NO2) and O3 simultaneously without discrimination. Alphasense proposes the use of a pair of sensors; the first one, NO2-B43F, is equipped with a filter dedicated to measure NO2. The second one, OX-B431, is sensitive to both NO2 and O3. Thus, O3 concentration can be obtained by subtracting the concentration of NO2 from the sum of the two concentrations. This technique is not practical and requires calibrating each sensor individually, leading to biased concentration estimation. In this paper, we propose Partial Least Square regression (PLS) to build a calibration model including both sensors’ responses and also temperature and humidity variations. The results obtained from data collected in the field for two months show that PLS regression provides better gas concentration estimation in terms of accuracy than calibrating each sensor individually.

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.

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