Two-dimensional correlation spectroscopy and multivariate curve resolution for the study of lipid oxidation in edible oils monitored by FTIR and FT-Raman spectroscopy.

Accelerate oxidative degradation of six vegetable oils was monitored using FTIR and FT-Raman spectroscopy. Two-dimensional correlation spectroscopy and multivariate curve resolution alternating least squares (MCR-ALS) were applied to the analysis of the data. The use of hetero-spectral two-dimensional correlation of FTIR and FT-Raman data allowed the use of well established band assignments to interpret less clearly assigned spectral features. With a moving window approach it was possible to obtain simplified two-dimensional correlation maps and to detect compounds evolving with different kinetic. Simultaneous analysis of the oxidation experiments of the six different oils monitored by both spectroscopic techniques was performed using MCR-ALS. Although a complete resolution of the data was not possible, the spectral changes occurring during the oxidative degradation of the oils were described with a five-component model. The two fundamentally different chemometric approaches lead to coincident results.

Direct monitoring of lipid oxidation in edible oils by Fourier transform Raman spectroscopy.

Fourier transform Raman spectroscopy has been used to investigate the chemical changes taking place during lipid oxidation in several edible oils. Oxidative degradation of six vegetable oils was accelerated by heating at 160 degrees C. Formation of aldehydes was detected, and saturated as well as alpha,beta-unsaturated aldehydes could be identified with the help of pure component spectra. The formation of conjugated double bond systems and the isomerisation of cis to trans double bonds was observed in the C=C stretching region and found to follow a distinct pattern for the different oils. It was possible to associate these differences to the fatty acid composition. The time-dependent intensity changes in certain Raman bands were compared to conventional parameters used to determine the extent of oxidation in oils, such as anisidine value and K(270), and showed good correlation.

Discrimination of olives according to fruit quality using Fourier transform Raman spectroscopy and pattern recognition techniques.

Fourier transform Raman spectroscopy combined with pattern recognition has been used to discriminate olives of different qualities. They included samples of sound olives, olives with frostbite, olives that have been collected from the ground, fermented olives, and olive samples with diseases. Milled olives were measured in a dedicated sample cup, which was rotated during spectrum acquisition. A preliminary study of the data set structure was performed using hierarchical cluster analysis and principal component analysis. Two supervised pattern recognition techniques, K-nearest neighbors and soft independent modeling of class analogy (SIMCA), were tested using a "leave-a-fourth-out" cross-validation procedure. SIMCA provided the best results, with prediction abilities of 95% for sound, 93% for frostbite, 96% for ground, and 92% for fermented olives. The olive samples with diseases (too few to define a class) were included in the validation and recognized as not belonging to any class. None of the damaged olive samples was wrongly predicted to the class of sound olives. With this approach a selection of sound olives for the production of high-quality virgin olive oil can be achieved.

Determination of oil and water content in olive pomace using near infrared and Raman spectrometry. A comparative study.

Near infrared (NIR) reflectance and Raman spectrometry were compared for determination of the oil and water content of olive pomace, a by-product in olive oil production. To enable comparison of the spectral techniques the same sample sets were used for calibration (1.74-3.93% oil, 48.3-67.0% water) and for validation (1.77-3.74% oil, 50.0-64.5% water). Several partial least squares (PLS) regression models were optimized by cross-validation with cancellation groups, including different spectral pretreatments for each technique. Best models were achieved with first-derivative spectra for both oil and water content. Prediction results for an independent validation set were similar for both techniques. The values of root mean square error of prediction (RMSEP) were 0.19 and 0.20-0.21 for oil content and 2.0 and 1.8 for water content, using Raman and NIR, respectively. The possibility of improving these results by combining the information of both techniques was also tested. The best models constructed using the appended spectra resulted in slightly better performance for oil content (RMSEP 0.17) but no improvement for water content.

Fourier transform Raman spectrometry for the quantitative analysis of oil content and humidity in olives.

A method for the direct and fast determination of oil content and humidity in olives using Fourier transform Raman spectrometry is reported. The only sample preparation step required was crushing of the olives using a hammer mill. The crushed olives were placed in a dedicated sample cup, which was rotated excentrically to the horizontal laser beam during spectrum acquisition. This allowed us to sample an increased volume and thus compensate for sample inhomogeneities. In this way the reproducibility of Raman spectra taken from crushed olives was significantly improved. Partial least-squares (PLS) regression was used for the chemometric evaluation of the Raman spectra. Standard errors of prediction for the validation set of 0.81% for oil content (in the range 19.68-35.71%) and 1.54% for humidity (in the range 29.23-51.49%), both expressed as weight percentage referred to fresh matter, were obtained.

Determination of yeast assimilable nitrogen content in wine fermentations by sequential injection analysis with spectrophotometric detetection.

An automated method for measuring the primary amino acid concentration in wine fermentations by sequential injection analysis with spectrophotometric detection was developed. Isoindole-derivatives from the primary amino acid were formed by reaction with o-phthaldialdehyde and N-acetyl- L-cysteine and measured at 334 nm with respect to a baseline point at 700 nm to compensate the observed Schlieren effect. As the reaction kinetic was strongly matrix dependent the analytical readout at the final reaction equilibrium has been evaluated. Therefore four parallel reaction coils were included in the flow system to be capable of processing four samples simultaneously. Using isoleucine as the representative primary amino acid in wine fermentations a linear calibration curve from 2 to 10 mM isoleucine, corresponding to 28 to 140 mg nitrogen/L (N/L) was obtained. The coefficient of variation of the method was 1.5% at a throughput of 12 samples per hour. The developed method was successfully used to monitor two wine fermentations during alcoholic fermentation. The results were in agreement with an external reference method based on high performance liquid chromatography. A mean-t-test showed no significant differences between the two methods at a confidence level of 95%.