A rapid and simple method for the determination of iodine values using derivative Fourier transform infrared measurements

Use of FTIR Spectroscopy and Chemometrics with Respect to Storage Conditions of Moldavian Dragonhead Oil

Oils often have similar properties and can be difficult to identify based on color, smell or taste alone. The present paper suggests the use of Fourier-transform infrared spectroscopy (FTIR) in combination with chemometric methods to explore similarities and differentiate between samples of Moldavian dragonhead oil subjected to different storage conditions. Dragonhead is a plant characterized by very good honey output and ease of cultivation. Principal component analysis (PCA) was applied to a standard, full range of FTIR spectra. Additionally, hierarchical cluster analysis (HCA) was employed to explore the organization of the samples in groups relative to their “proximity” (similarity), by way of Euclidean distance measurement. PC1 and PC2 accounted respectively for 85.4% and 10.1% of the total data variance. PC1 and PC2 were strongly, negatively correlated within the entire spectral range; the only exception was the region corresponding to νs(-C-Hvst, -CH2) vibrations (aliphatic groups in triglycerides), where PC2 was positively correlated. The use of FTIR spectral analysis revealed noticeable differences in the intensity of bands characteristic of the ageing processes (markers of oxidative processes, etc.) taking place in oleaginous samples and related to the processes of fatty acids oxidation.

Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy

Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent.

NIR spectroscopy and partial least-squares regression for determination of natural alpha-tocopherol in vegetable oils

Near-infrared (NIR) spectroscopy and partial least-square regression were used for determination of alpha-tocopherol in edible oils after extraction with ethanol. The standard error of calibration and the standard error of prediction were calculated for evaluation of the calibration models. The chemometric calibration model was prepared in spectral region 6500-4500 cm(-1) for standard alpha-tocopherol solutions (0.54-53.54 mg/mL). Obtained mean concentrations of natural alpha-tocopherol in different types of oils varied from 17.53 to 57.10 mg/100 g. Net analyte signal calculation was used to estimate detection limit (DL = 0.12 mg/mL), quantification limit (QL = 0.40 mg/mL), sensitivity (SEN = 0.045 mg/mL), and selectivity (SEL ranged between 0.24 and 0.54% of the measured reflectance signal) of the proposed NIR method. The comparable precision (RSD = 0.68-2.80% and 0.79-3.06%) and accuracy (recovery, 97.2-102.4% and 96.8-103.2%) for the proposed NIR and standard HPLC methods, demonstrate the benefit of the NIR method in the routine analysis of alpha-tocopherol in vegetable oils.

Fourier-transform infrared derivative spectroscopy with an improved signal-to-noise ratio

Infrared derivative spectroscopy is a useful technique for finding peaks hidden in broad spectral features. A data acquisition technique is shown that will improve the signal-to-noise ratio (SNR) of Fourier-transform infrared (FTIR) derivative spectroscopy. Typically, in a FTIR measurement one samples each point for the same time interval. The effect of using a graded time interval is studied. The simulations presented show that the SNR of first-derivative FTIR spectroscopy will improve by 15% and that the SNR of second-derivative FTIR will improve by 34%.

Determination of C22:5 and C22:6 marine fatty acids in pork fat with Fourier transform mid-infrared spectroscopy

Fatty acids in samples (n=74) of pork adipose tissue were measured with a Fourier transform mid-infrared (FT-MIR) spectrometer and by gas chromatography. The measured absorption spectra provided information to estimate partial least squares regression models for fatty acid groups, the iodine value and several fatty acids. The iodine values were predicted with correlation coefficient R=0.996 and root mean square error of cross-validation RMSECV=0.658. The sum of the two marine fatty acids of main interest, C22:5n3+C22:6n3, were predicted with R=0.982 and RMSECV=0.062. The K nearest neighbours procedure successfully classified the samples in three classes, depending on their proportions of marine fatty acids. Application of fat and absorption measurements were rapid, requiring less than 5 min of labour per sample. The results reported in this paper demonstrate that FT-MIR measurements can serve as a rapid method to determine marine fatty acids in pork fat.