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).

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 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 Determination of Adulteration Content in Extra Virgin Olive Oil Using FT-NIR Spectroscopy Combined with the BOSS–PLS Algorithm

Molecules ◽  
2019 ◽  
Vol 24 (11) ◽  
pp. 2134 ◽  
Author(s):  
Hui Jiang ◽  
Quansheng Chen
Keyword(s):  
Root Mean Square Error ◽  
Olive Oil ◽  
Mean Square Error ◽  
Virgin Olive Oil ◽  
Nir Spectroscopy ◽  
Extra Virgin Olive Oil ◽  
Mean Square ◽  
Spectroscopy Technique ◽  
Full Spectrum ◽  
Variable Subset

This work applied the FT-NIR spectroscopy technique with the aid of chemometrics algorithms to determine the adulteration content of extra virgin olive oil (EVOO). Informative spectral wavenumbers were obtained by the use of a novel variable selection algorithm of bootstrapping soft shrinkage (BOSS) during partial least-squares (PLS) modeling. Then, a PLS model was finally constructed using the best variable subset obtained by the BOSS algorithm to quantitative determine doping concentrations in EVOO. The results showed that the optimal variable subset including 15 wavenumbers was selected by the BOSS algorithm in the full-spectrum region according to the first local lowest value of the root-mean-square error of cross validation (RMSECV), which was 1.4487 % v/v. Compared with the optimal models of full-spectrum PLS, competitive adaptive reweighted sampling PLS (CARS–PLS), Monte Carlo uninformative variable elimination PLS (MCUVE–PLS), and iteratively retaining informative variables PLS (IRIV–PLS), the BOSS–PLS model achieved better results, with the coefficient of determination (R2) of prediction being 0.9922, and the root-mean-square error of prediction (RMSEP) being 1.4889 % v/v in the prediction process. The results obtained indicated that the FT-NIR spectroscopy technique has the potential to perform a rapid quantitative analysis of the adulteration content of EVOO, and the BOSS algorithm showed its superiority in informative wavenumbers selection.

scholarly journals APPLICATION OF FTIR SPECTRA COMBINED WITH CHEMOMETRICS FOR ANALYSIS OF CANDLENUT OIL ADULTERATION

2018 ◽  
Vol 10 (5) ◽  
pp. 54
Author(s):  
Fitri Yuliani ◽  
Sugeng Riyanto ◽  
Abdul Rohman
Keyword(s):  
Root Mean Square Error ◽  
Ftir Spectroscopy ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Corn Oil ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square

Objective: The aim of this study was to use FTIR spectroscopy in combination with chemometrics techniques for quantification and classification of candlenut oil (CnO) from oil adulterants, namely sunflower oil (SFO), soybean oil (SyO), and corn oil (CO).Methods: The spectra of all samples were scanned using Fourier Transform Infrared (FTIR) Spectrophotometer using attenuated total reflectance (ATR) as sampling technique at mid infrared region (4000-650 cm-1). Multivariate calibrations of principle component regression (PCR) and partial least square regression (PLSR) were used for quantitative models to predict the levels of CnO in the binary mixtures with SFO, SyO, and CO.Results: The results showed that CnO in SFO was best quantified using PCR at wavenumbers region of 3100-2800 cm-1. Quantitative analysis of CnO in SyO was carried out using PLSR with normal spectra mode using combined wavenumbers of 1765-1625 and 839-663 cm-1, while CnO in CO was analyzed quantitatively using normal spectra at wavenumbers of 970-857 cm-1. The coefficient of determination (R2) obtained were>0.99 with low values of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP). The results of discriminant analysis revealed that authentic CnO can be discriminated from CnO adulterated with SFO, SyO and CO using selected wavenumbers.Conclusion: FTIR spectroscopy combined with chemometrics could be used as rapid and reliable method for authentication of candlenut oil (CnO) adulterated with other oils.

scholarly journals Quantification and Classification of Corn and Sunflower Oils as Adulterants in Olive Oil Using Chemometrics and FTIR Spectra

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Abdul Rohman ◽  
Y. B. Che Man
Keyword(s):  
Olive Oil ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Ftir Spectra ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Calibration Model ◽  
Sunflower Oils

Commercially, extra virgin olive oil (EVOO) is subjected to be adulterated with low-price oils having similar color to EVOO. Fourier transform infrared (FTIR) spectroscopy combined with chemometrics has been successfully used for classification and quantification of corn (CO) and sunflower oils (SFOs) in EVOO sets. The combined frequency regions of 3027–3000, 1076–860, and 790–698 cm-1were used for classification and quantification of CO in EVOO; meanwhile, SFO was analyzed using frequency regions of 3025–3000 and 1400–985 cm-1. Discriminant analysis can make classification of pure EVOO and EVOO adulterated with CO and SFO with no misclassification reported. The presence of CO in EVOO was determined with the aid of partial least square calibration using FTIR normal spectra. The calibration and validation errors obtained in CO's quantification are 0.404 and 1.13%, respectively. Meanwhile, the first derivative FTIR spectra and PLS calibration model were preferred for quantification of SFO in EVOO with high coefficient of determination (R2) and low errors, either in calibration or in validation sample sets.

scholarly journals 1H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils

Foods ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1797
Author(s):  
Chiara Roberta Girelli ◽  
Francesca Calò ◽  
Federica Angilè ◽  
Lucia Mazzi ◽  
Daniele Barbini ◽  
...  
Keyword(s):  
Olive Oil ◽  
1H Nmr ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Partial Least Square ◽  
Least Square ◽  
Minor Components ◽  
Multivariate Statistical ◽  
Oil Blends ◽  
Fat Consumption

During the last few years, the global demand for extra virgin olive oil (EVOO) is increased. Olive oil represents a significant percentage of world fat consumption determining an important development of its market. In this context, the problems related to counterfeiting and product fraud is becoming extremely relevant. Thus, the quality and authenticity control of EVOOs is nowadays mandatory. In this study we focused on the use of 1H NMR technique associated with multivariate statistical analysis to characterize Italian EVOOs commercial blends. In particular, a specific database including 126 monocultivar EVOOs reference samples, was used to characterize a total of 241 Italian EVOOs blends over four consecutive harvesting years. Moreover, the effect of the minor components (phenolic compounds) on the qualitative characterization of blended EVOOs was also evaluated. The correlation analysis of classification scores obtained using two pairwise orthogonal partial least square-discriminant analysis models (built with major and combined major–minor components NMR data) revealed that both could be profitably used to generally classify the studied Coratina containing blends.

Determination of hydroxytyrosol and tyrosol in human urine after intake of extra virgin olive oil produced with an ultrasounds-based technology

2021 ◽  
pp. 114204
Author(s):  
Antonella Maria Aresta ◽  
Nicolella De Vietro ◽  
Maria Lisa Clodoveo ◽  
Riccardo Amirante ◽  
Filomena Corbo ◽  
...  
Keyword(s):  
Olive Oil ◽  
Human Urine ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil

Analysis of candlenut oil as oil adulterant in three functional oils of soybean oil, sunflower oil and grapeseed oil in quaternary mixture systems using FTIR spectroscopy and chemometrics

Food Research ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 248-253
Author(s):  
A.B. Riyanta ◽  
S. Riyanto ◽  
E. Lukitaningsih ◽  
A. Rohman
Keyword(s):  
Root Mean Square Error ◽  
Soybean Oil ◽  
Ftir Spectroscopy ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Sunflower Oil ◽  
Ftir Spectra ◽  
Mean Square ◽  
Grapeseed Oil ◽  
Quaternary Mixture

Soybean oil (SBO), sunflower oil (SFO) and grapeseed oil (GPO) contain high levels of unsaturated fats that are good for health and have proximity to candlenut oil. Candlenut oil (CNO) has a lower price and easier to get oil from that seeds than other seed oils, so it is used as adulteration for gains. Therefore, authentication is required to ensure the purity of oils by proper analysis. This research was aimed to highlight the FTIR spectroscopy application with multivariate calibration is a potential analysis for scanning the quaternary mixture of CNO, SBO, SFO and GPO. CNO quantification was performed using multivariate calibrations of principle component (PCR) regression and partial least (PLS) square to predict the model from the optimization FTIR spectra regions. The highest R2 and the lowest values of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were used as the basis for selection of multivariate calibrations created using several wavenumbers region of FTIR spectra. Wavenumbers regions of 4000-650 cm-1 from the second derivative FTIR-ATR spectra using PLS was used for quantitative analysis of CNO in quaternary mixture with SBO, SFO and GPO with R2 calibration = 0.9942 and 0.0239% for RMSEC value and 0.0495%. So, it can be concluded the use of FTIR spectra combination with PLS is accurate to detect quaternary mixtures of CNO, SBO, SFO and GPO with the highest R2 values and the lowest RMSEC and RMSEP values.

scholarly journals Liquid Carbon Dioxide Use in the Extraction of Extra Virgin Olive Oil From Olive Paste

2014 ◽  
Vol 3 (4) ◽  
pp. 119 ◽  
Author(s):  
Raffaele Romano ◽  
Nadia Manzo ◽  
Immacolata Montefusco ◽  
Annalisa Romano ◽  
Antonello Santini
Keyword(s):  
Carbon Dioxide ◽  
Fatty Acids ◽  
Olive Oil ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Liquid Carbon ◽  
Liquid Carbon Dioxide ◽  
A Value ◽  
Olive Mill Waste Water

<p>In this study the use of liquid carbon dioxide, CO<sub>2</sub>, for extraction of oil from olive paste (<em>Peranzana cultivar</em>)<strong> </strong>were examined and extracted oil was compared with oils obtained by centrifugation, pressure and use of chemical solvent.</p> <p>It is well known that the use of CO<sub>2</sub> has many advantages: miscibility with a wide range of molecules, food safety, non-flammability, absence of residues in the extract, possibility of total solvent recovery and no production of olive mill waste water that are highly polluting for the environment and require expansive disposal.</p> <p>Samples were subjected to the following analyses: determination of Free Fatty Acids (FFA), Peroxides Value (PV), Spectrophotometric Indices, Fatty Acids Composition (FA), determination of biophenols content and determination of Volatile Organic Compounds (VOCs). All samples showed FFA, PV and ?K values within the limits established by law for extra-virgin olive oil. The use of CO<sub>2</sub> did not catalyze hydrolysis, oxidation and condensation of double bonds. Centrifuged oils and oils extracted with carbon dioxide presented the lowest PV and FFA values. Extraction with liquid carbon dioxide contributed to an increasing of phenolic content with a value of 270.5 mg/kg, a value twice that of the oils extracted with centrifugation (135.3 mg/kg) or pressure methods (173.2 mg/kg). Oil extracted with liquid carbon dioxide showed the greatest amount of t-2-octenal and t-2-heptenal, giving herbaceous and pungent notes. Moreover the presence of aromatic compounds such as limonene, generally absent in olive oils, was only detected in the sample extracted with liquid carbon dioxide.</p>

Quantification of Lard in the Mixture with Olive Oil in Cream Cosmetics Based on FTIR Spectra and Chemometrics for Halal Authentication

2014 ◽  
Vol 69 (1) ◽  
Author(s):  
Abdul Rohman ◽  
Intan Gupitasari ◽  
Purwanto Purwanto ◽  
Kuwat Triyana ◽  
Arieff Salleh Rosman ◽  
...  
Keyword(s):  
Olive Oil ◽  
Ftir Spectroscopy ◽  
Multivariate Calibration ◽  
Virgin Olive Oil ◽  
Sampling Technique ◽  
Extra Virgin Olive Oil ◽  
Ftir Spectra ◽  
Halal Authentication ◽  
Extracting Solvent

The presence of lard (LD) in cosmetics products is a serious matter for certain religion, like Islam. The Muslim community is not allowed to use cosmetics products containing pig derivatives such as LD. Therefore, analysis of LD in cosmetics products is highly needed. The present study highlighted the employment of Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and principle component analysis (PCA) for quantitative analysis and classification of LD in the binary mixture with extra virgin olive oil (EVOO) as oil base in cream formulations for halal authentication. The lipid component in cream was extracted using liquid-liquid extraction using hexane as extracting solvent, and the lipid obtained was subjected to FTIR spectra measurement, using horizontal attenuated total reflectance as sampling technique. The result showed that FTIR spectroscopy in combination with partial least squares can be used to quantify the levels of LD in the mixture with EVOO in cosmetics creams using the combined frequency regions of 1785-702 cm-1 and 3020-2808 cm-1. PCA using absorbance intensities at 1200 – 1000 cm-1 as variables has been successfully used for the classification of cream with and without LD in the formulation. The developed method is rapid and not involving the excessive sample preparation.

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