scholarly journals Determination of sesame oil, rice bran oil and pumpkin seed oil in ternary mixtures using FTIR spectroscopy and multivariate calibrations

Food Research ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 135-142 ◽  
Author(s):  
Irnawati ◽  
S. Riyanto ◽  
S. Martono ◽  
Abdul Rohman
Keyword(s):  
Root Mean Square Error ◽  
Rice Bran ◽  
Seed Oil ◽  
Rice Bran Oil ◽  
Sesame Oil ◽  
Ftir Spectra ◽  
Ternary Mixtures ◽  
Mean Square ◽  
Pumpkin Seed ◽  
Pumpkin Seed Oil

Pumpkin seed oil (PSO), rice bran oil (RBO), sesame oil (SEO) are considered as functional oils due to its biological activities which are beneficial to human health, as a consequence, these oils had the higher price. This attracted unethical players to blend these oils with lower price oils, therefore, its authentication by analysis of purity levels of oils is very important. This study highlighted the potential application of FTIR spectroscopy and multivariate calibrations for analysis of PSO, RBO, and SEO in ternary mixtures. Individual FTIR spectra of studied oils as well as in ternary mixtures with certain compositions were scanned and pre-processed. Two multivariate calibrations of principle component regression (PCR) and partial least square regression (PLSR) were compared and used to build the prediction models at optimized FTIR spectra regions. The selection of multivariate calibrations, wavenumbers region, and FTIR spectra modes was based on the statistical parameters of highest R2 and lowest values of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP). The results showed that PLSR using second derivative FTIR spectra at wavenumbers region of 3100-2750 and 1500-663 cm-1 was used to predict the levels of PSO in ternary mixtures with RBO and SEO with R2 > 0.99 in calibration and validation models along with RMSEC value of 0.0054% and RMSEP of 0.0179%. FTIR spectra using the second and first derivatives at wavenumbers of 3100-650 cm-1 were used for prediction of RBO and SEO in ternary mixture with PSO, respectively. It can be concluded that FTIR spectra combined with PLSR at certain wavenumbers region are accurate as indicated by high R2 values and precise as indicated by low values of RMSEC and RMSEP for analysis of PSO, RBO and SEO in ternary mixtures.

scholarly journals The employment of FTIR spectroscopy and chemometrics for authentication of pumpkin seed oil from sesame oil

Food Research ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 42-48 ◽  
Author(s):  
Irnawati ◽  
S. Riyanto ◽  
S. Martono ◽  
A. Rohman
Keyword(s):  
Discriminant Analysis ◽  
Root Mean Square Error ◽  
Ftir Spectroscopy ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Sesame Oil ◽  
Ftir Spectra ◽  
Mean Square ◽  
Pumpkin Seed ◽  
Principle Component

The adulteration practice of high price oils such as pumpkin seed oils (PSO) with lower ones could be motivated by economic gains. The objective of this study was to apply FTIR spectroscopy in combination with chemometrics of multivariate calibrations and discriminant analysis for the authentication of PSO. A total of fifteen oils were scanned using FTIR spectrophotometer at mid-infrared regions (4000-650 cm-1 ) and subjected to principal component analysis (PCA) using absorbance values at whole mid-IR regions to know oil having a close similarity to PSO in terms of FTIR spectra. Two multivariate calibrations namely principle component regression (PCR) and partial least square regression (PLSR) along with FTIR spectra modes (normal, derivative-1, and derivative2) were optimized to get the best prediction models. In addition, discriminant analysis (DA) was used for classification of PSO and PSO adulterated with oil adulterant. The results showed that among 15 oils, sesame oil (SeO) had the closer score plot in terms of the first principle component and second principle components with that of PSO. Based on the statistical parameters selected (higher R2 and lowest errors), FTIR spectra in derivative -1 mode at wavenumbers of 1800-663 cm-1 were selected for quantification of PSO in SeO with coefficient of determination (R) values of 0.9998 and 0.9994 in calibration and validation models, respectively. The values of root mean square error of calibration (RMSEC) and root mean square error of prediction obtained were 0.003% and 0.006%, respectively. DA using 10 principle components could clearly discriminate PSO and PSO adulterated with SeO with accuracy levels of 100%. FTIR spectroscopy in combination with chemometrics could be an effective means to detect the adulteration of PSO with SeO.

The antioxidant effects of pumpkin seed oil on subacute aflatoxin poisoning in mice

2011 ◽  
Vol 28 (12) ◽  
pp. 681-688 ◽  
Author(s):  
Gökhan Eraslan ◽  
Murat Kanbur ◽  
Öznur Aslan ◽  
Mürsel Karabacak
Keyword(s):  
Seed Oil ◽  
Pumpkin Seed ◽  
Pumpkin Seed Oil ◽  
Antioxidant Effects

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.

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