Improving the determination of moisture in edible oils by FTIR spectroscopy using acetonitrile extraction

D2O assisted FTIR spectroscopic analysis of moisture in edible oil

D₂O-assisted moisture analysis of edible oils was investigated. The acetonitrile extract of the oil samples was split into two parts. The spectrum of one part was taken as is, another was recorded after addition of excess D₂O. Changes in spectral absorption of the H-O-H bending band (1600-1660 cm^-1) was used to calculate moisture in oil samples. To effectively depleting absorption of water in the acetonitrile extract, a 30-fold excess of D₂O is required. The typical OH-containing constituents in oil did not show significant interference on the H/D exchange. Validation experiments by using five oils with five levels of moisture spiked (50-1000 μg/g) suggested that the prediction tracked the spiked amounts well. The results of variance analysis indicate that there is no difference in terms of analytical methods and oil types used (p < 0.001). The D₂O method developed is generally applicable to the accurate analysis of moisture at trace levels (<100 μg/g) in edible oils.

Nondestructive Detection of Moisture Content in Palm Oil by Using Portable Vibrational Spectroscopy and Optimal Prediction Algorithms

Rapid and nondestructive measurement of moisture content in crude palm oil is essential for promoting the shelf-stability and quality. In this research, micro NIR spectrometer coupled with a multivariate calibration model was used to collect and analyse fingerprinted information from palm oil samples at different moisture contents. Several preprocessing methods such as standard normal variant (SNV), multiplicative scatter correction (MSC), Savitzky-Golay first derivative (SGD1), Savitzky-Golay second derivative (SGD2) together with partial least square (PLS) regression techniques, full PLS, interval PLS (iPLS), synergy interval PLS (SiPLS), genetic algorithm PLS (GAPLS), and successive projection algorithm PLS (SPA-PLS) were comparatively employed to construct an optimum quantitative prediction model for moisture content in crude palm oil. The models were evaluated according to the coefficient of determination and root mean square error in calibration (Rc and RMSEC) and prediction (Rp and RMSEC) set, respectively. The model SGD1 + SiPLS was the optimal novel algorithm obtained among the others with the performance of Rc = 0.968 and RMSEC = 0.468 in the calibration set and Rp = 0.956 and RMSEP = 0.361 in the prediction set. The results showed that rapid and nondestructive determination of moisture content in palm oil is feasible and this would go a long way to facilitating quality control of crude palm oil.

Development and Validation of a Simple Method to Quantify Contents of Phospholipids in Krill Oil by Fourier-Transform Infrared Spectroscopy

This study focuses on developing a quantification method for phosphatidylcholine (PC) and total phospholipid (PL) in krill oil using Fourier-transform infrared (FT-IR) spectroscopy. Signals derived from the choline and phosphate groups were selected as indicator variables for determining PC and total PL content; calibration curves with a correlation coefficient of >0.988 were constructed with calibration samples prepared by mixing krill oil raw material and fish oil in different ratios. The limit of detection (LOD, 0.35–3.29%) of the method was suitable for the designed assay with good accuracy (97.90–100.33%). The relative standard deviations for repeatability (0.90–2.31%) were acceptable. Therefore, both the methods using absorbance and that using second-derivative were confirmed to be suitable for quantitative analysis. When applying this method to test samples, including supplements, the PC content and total PL content were in good agreement with an average difference of 2–3% compared to the 31P NMR method. These results confirmed that the FT-IR method can be used as a convenient and rapid alternative to the 31P NMR method for quantifying PLs in krill oil.

A Rapid, Univariate FT-NIR Procedure to Determine Moisture Concentration in Olive Oil

We recently observed that the weak near-infrared (NIR) band near 5260 cm^-1 was relatively more intense for extra virgin olive oil (EVOO) than for refined olive oil (ROO). We also observed that its intensity was diminished upon heating and erroneously presumed that it may be attributed to volatile carbonyl components in EVOO. In the present study we demonstrate for the first time that this band is primarily attributed to a water O-H combination band. To accurately determine the intensity of this weak band, observed on a shifted and sloping baseline, we measured the peak-to-peak (p-p) height of its first derivative. An exponential calibration curve for p-p height versus gravimetrically-determined concentration of spiked water was satisfactorily generated. The calibration curve was first evaluated by using independent sets of gravimetrically prepared test samples. Subsequently, it was used to determine the moisture content, a quality parameter, for a limited set of authenticated reference olive oils whose quality and purity were confirmed by official methods. These concentrations, 0.098-0.12% H₂O (w/w) for EVOO, 0.022-0.030% H₂O (w/w) for ROO, and 0.028-0.054% H₂O (w/w) for pomace olive oil (POO), were consistent with those reported in the literature. For 88 commercial products investigated, the moisture levels fell in the range from 0.026% to 0.13% (w/w). The correlation between moisture content and other olive oil quality parameters has been reported in the literature and has yet to be further investigated.

An approach for in situ qualitative and quantitative analysis of moisture adsorption in nanogram-scaled lignin by using micro-FTIR spectroscopy and partial least squares regression

Moisture sorption has a great impact on the mechanical properties of lignin. To better characterize the moisture sorption of lignin, an approach for in situ qualitative and quantitative analysis of moisture adsorption in nanogram-scaled lignin by using micro-FTIR spectroscopy and partial least squares regression is introduced in this study. Spectra of nanogram-scaled lignin were collected within the relative humidity (RH) of 0%-92%. A qualitative analysis of these measured spectra confirmed the effective water sorption sites and determined spectral ranges related to moisture adsorption. Using these identified spectral ranges, a quantitative forecasting model for the moisture content (MC) of lignin was built and developed according to partial least square regression (R², 0.9996; RMSECV, 0.408; RMSEP, 0.118). Furthermore, the water sorption isotherm of lignin was acquired using the established forecasting model in which a very positive correlation between the estimated and measured MCs was demonstrated using a dynamic vapor sorption (DVS) setup. The results confirmed the practicability and effectiveness of this in situ qualitative and quantitative analysis approach.

Efficient quantification of water content in edible oils by headspace gas chromatography with vapour phase calibration

BACKGROUND

An automated and accurate headspace gas chromatographic (HS-GC) technique was investigated for rapidly quantifying water content in edible oils. In this method, multiple headspace extraction (MHE) procedures were used to analyse the integrated water content from the edible oil sample. A simple vapour phase calibration technique with an external vapour standard was used to calibrate both the water content in the gas phase and the total weight of water in edible oil sample. After that the water in edible oils can be quantified.

RESULTS

The data showed that the relative standard deviation of the present HS-GC method in the precision test was less than 1.13%, the relative differences between the new method and a reference method (i.e. the oven-drying method) were no more than 1.62%.

CONCLUSION

The present HS-GC method is automated, accurate, efficient, and can be a reliable tool for quantifying water content in edible oil related products and research. © 2017 Society of Chemical Industry.

The Application of FT-IR Spectroscopy for Quality Control of Flours Obtained from Polish Producers

Samples of wheat, spelt, rye, and triticale flours produced by different Polish mills were studied by both classic chemical methods and FT-IR MIR spectroscopy. An attempt was made to statistically correlate FT-IR spectral data with reference data with regard to content of various components, for example, proteins, fats, ash, and fatty acids as well as properties such as moisture, falling number, and energetic value. This correlation resulted in calibrated and validated statistical models for versatile evaluation of unknown flour samples. The calibration data set was used to construct calibration models with use of the CSR and the PLS with the leave one-out, cross-validation techniques. The calibrated models were validated with a validation data set. The results obtained confirmed that application of statistical models based on MIR spectral data is a robust, accurate, precise, rapid, inexpensive, and convenient methodology for determination of flour characteristics, as well as for detection of content of selected flour ingredients. The obtained models' characteristics were as follows: R² = 0.97, PRESS = 2.14; R² = 0.96, PRESS = 0.69; R² = 0.95, PRESS = 1.27; R² = 0.94, PRESS = 0.76, for content of proteins, lipids, ash, and moisture level, respectively. Best results of CSR models were obtained for protein, ash, and crude fat (R² = 0.86; 0.82; and 0.78, resp.).

Total Phospholipids in Edible Oils by In-Vial Solvent Extraction Coupled with FTIR Analysis

A simple procedure for the determination of total phospholipids (TPL) in edible oils was developed by combining a single-step, in situ methanol/acetonitrile (MeOH/ACN) extraction of the oil sample followed by Fourier transform infrared (FTIR) spectroscopic analysis of the extract. Spectral analysis of extracts in a 25 μm CaF₂ cell obtained using 1:1 MeOH/ACN added to oil in a 2:1 ratio indicated that measurements made using only the asymmetric phosphate diester PO₂^- stretching band at 1243 cm^-1 in second-derivative spectra were sufficient for the accurate measurement of TPL with minimal coextracted triglyceride interferences being encountered. FTIR calibration spectra were devised using only phosphatidylcholine (PC) as a representative phospholipid standard, covering a range of 0-50000 μg/g TPL and spiked into 1:1 MeOH/ACN, capable of tracking the added PC with an SD of <200 μg/g. The FTIR method was initially validated using model PC-spiked degummed canola oil and subsequently with commercial crude and refined soy and rapeseed oils as well as a lecithin tablet with the FTIR TPL predictions compared to those of the AOCS Ca 12-55 molybdenate method. The FTIR method tracked the AOCS results well, being somewhat more reproducible than the reference method (±3.2 vs ±4.9%), which limited its accuracy relative to the AOCS reference procedure (±2.2%). The simple in-vial solvent extraction procedure, followed by FTIR analysis of the extract, is a simple, efficient, and rapid procedure that is also amenable to automation using an autosampler-equipped FTIR if multiple samples are to be analyzed.

Principles, performance, and applications of spectral reconstitution (SR) in quantitative analysis of oils by Fourier transform infrared spectroscopy (FT-IR)

Spectral reconstitution (SR) is a dilution technique developed to facilitate the rapid, automated, and quantitative analysis of viscous oil samples by Fourier transform infrared spectroscopy (FT-IR). This technique involves determining the dilution factor through measurement of an absorption band of a suitable spectral marker added to the diluent, and then spectrally removing the diluent from the sample and multiplying the resulting spectrum to compensate for the effect of dilution on the band intensities. The facsimile spectrum of the neat oil thus obtained can then be qualitatively or quantitatively analyzed for the parameter(s) of interest. The quantitative performance of the SR technique was examined with two transition-metal carbonyl complexes as spectral markers, chromium hexacarbonyl and methylcyclopentadienyl manganese tricarbonyl. The estimation of the volume fraction (VF) of the diluent in a model system, consisting of canola oil diluted to various extents with odorless mineral spirits, served as the basis for assessment of these markers. The relationship between the VF estimates and the true volume fraction (VF(t)) was found to be strongly dependent on the dilution ratio and also depended, to a lesser extent, on the spectral resolution. These dependences are attributable to the effect of changes in matrix polarity on the bandwidth of the ν(CO) marker bands. Excellent VF(t) estimates were obtained by making a polarity correction devised with a variance-spectrum-delineated correction equation. In the absence of such a correction, SR was shown to introduce only a minor and constant bias, provided that polarity differences among all the diluted samples analyzed were minimal. This bias can be built into the calibration of a quantitative FT-IR analytical method by subjecting appropriate calibration standards to the same SR procedure as the samples to be analyzed. The primary purpose of the SR technique is to simplify preparation of diluted samples such that only approximate proportions need to be adhered to, rather than using exact weights or volumes, the marker accounting for minor variations. Additional applications discussed include the use of the SR technique in extraction-based, quantitative, automated FT-IR methods for the determination of moisture, acid number, and base number in lubricating oils, as well as of moisture content in edible oils.