Determination of Iron in Vegetable Oil by Fourier Transform Mid-Infrared Spectroscopy

The potential of Fourier transform mid-infrared spectroscopy with attenuated total reflection (FTIR-ATR) for the quantification of iron (Fe) in vegetable oil extracted from the fruit of the moriche palm (buriti) [Mauritia flexuosa] was evaluated. This green method enables direct measurements without previous sample handling. Twenty-five buriti samples were collected in Roraima (Brazil). The statistical models were developed using the technique of partial least squares (PLS) analysis and the data set was divided into two parts: one used for calibration (n = 20) and one used for testing (n = 5). First, the model was calibrated and cross-validated with the calibration data set so that the model was validated with the test data set to verify its prediction ability. To obtain reference data, the samples were analyzed by X-ray fluorescence (EDXRF). The coefficient of determination (R) was 0.9965 and the mean square error of prediction (RMSEP) obtained for iron (Fe) was 0.8067 (in ppm). The results showed that the prediction ability can be considered good for large quantification of iron intervals in vegetable oil, and the mean relative errors were less than ±7%. This indicated that the green method for the determination of iron (Fe) in vegetable oil by Fourier transform mid-infrared spectroscopy with attenuated total reflection can be used as an alternative method to the classic methods of analysis, because it does not use reagents harmful to the environment or operator, does not generate harmful waste, uses a fast technique, and there is minimal manipulation of the sample.


Introduction
The Amazon region stands out for the enormous diversity of exotic fruits and has a great diversity of palm trees that occur in different ecosystems.Moriche palm (Mauritia flexuosa) is one of the most useful palm trees in the Amazon, being found in an extensive area, along the rivers, forests, and savannas, in several Brazilian states and South American countries (Ferreira, Lucien, Amaral, & Silveira, 2008;Gilmore, Endress, & Horn, 2013;Padoch, Ayres, Pinedo-Vasquez, & Henderson, 1999).The fruit of the moriche palm, called buriti, is widely used by the local, riverside, and indigenous population due to the high nutritional value.It can be consumed fresh or as ingredients in juices, cakes, sweets and popsicles, as well as cooking oil for medical purposes by indigenous people (Ribeiro, 2010).Some years ago, the buriti proved to be promising in research on compositions of bioactive compounds, such as sterols, tocopherols and carotenoids and presented application potentiality as a raw material for the extraction of oils for use in the food and cosmetic industries.Recent studies have shown that buriti oils can be considered beneficial for human health, because they present important phytochemical sources of unsaturated fatty acids, phytosterols, β-carotene, among others (Santos, Alves, & Roca, 2015).
Buriti oil is rich in monounsaturated fatty acids and a potential candidate for the prevention of cholesterol called LDL (low-density lipoprotein) (Albuquerque et al., 2005).It also has capacity in antiplatelet activity and inhibition of thrombosis formation and can be used in the prevention of cardiovascular diseases (Fuentes et al., 2013;Webb et al., 2008).Because of its emollient properties, it is used in the cosmetic industry as an adjunct to sun protection formulations (Zanatta, Mitjans, Urgatondo, Rocha-Filho, & Vinardell, 2010).Recent research has shown that buriti oil is a good natural antioxidant, with potential for use in food systems, even at high temperatures (Forero-Doria et al., 2015).Being considered a good source of vitamin E, with a higher concentration than many kinds of cereal and legumes, being able to present high total levels of tocopherols (more than 100%) compared to patauá, mari, tucumã, and inajá oils (Rodrigues, Darnet, & Silva, 2010).
Iron is an essential nutrient for life and primarily acts on the synthesis of red blood cells and transport of oxygen to all cells of the body.However, according to National Iron Supplementation Program (2017), iron deficiency anemia is the largest nutritional deficiency in the world, affecting all social classes, especially children under two years of age and pregnant women.Iron deficiency anemia can have an adverse effect on psychomotor and mental development in children, and the mortality and morbidity of mother and infant during pregnancy (Gibney, Lanham-New, Cassidy, & Vorster, 2009;Oski, 1979;Lozoff, Wolf, & Jimenez, 1996;Almeida et al., 2004).
In view of the harm caused by insufficient iron intake, the labeling of iron content in foods is important, however, food products need to be inspected more quickly and efficiently.
In the literature, many conventional methods for scientific research are not green, because they produce harmful residues during and after analytical processes.The determination of the mineral elements in food is commonly done using atomic spectroscopy, however, the sample needs to be mineralized and then converted into solution.For this, methodologies involving the use of strong acids and other reagents are required, and, unfortunately, this process time-consuming, cost energy, and generating a lot of waste.On the other hand, nowadays scientists are aiming to development of methodologies that can reduce or eliminate reagent consumption and minimize working time through highly efficient analyzes (Namieśnik, 2001).
The mid-infrared spectroscopy (MIR), 4000-400 cm -1 , is based on fundamental molecular vibrations and associated rotational vibration effects and is known to have more intense fundamental bands if compared whit near-infrared spectroscopy (Nunes, 2014).The infrared spectroscopy methods have been employed as an alternative to wet chemistry atomic spectroscopy procedures for food analysis (Mir-Marqués, Martínez-García, Garrigues, Cervera, & de la Guardia, 2016), because they do not harm the environment and the products and, moreover, they strengthen the sustainable development that is useful for the society.
FTIR spectroscopy combined with chemometric techniques is proved to be a successful analytical method for the quantitative modeling of a wide variety of oils, foods, and plants (Sinelli et al., 2010).Also has already proved to be useful in the detection of pig lard in vegetable oils (Rohman, Man, Hashim, & Ismail, 2011) when combined with the least squares regression (PLS) method.But the literature reports only a few papers that show the analysis of mineral elements in food matrices using MIR spectroscopy (Schmitt, Garrigues, & de la Guardia, 2014) and none focusing on the buriti oil.Moros, Iñón, Khanmohammadi, Garrigues and de la Guardia (2006) combined FTIR-ATR and PLS for the determination of calcium in commercial yogurt.Reeves (2001) has indicated that MIR spectroscopy has potential to measure phosphorus (P) in dried poultry manures.The MIR spectroscopy application in dried dairy manure was also developed, and calibrations for fiber were possible, but calibrations for minerals were not successful (Reeves & Kessel, 2002).Soyeurt et al. (2009) developed equations to measure Ca, K, Mg, Na, and P contents directly in bovine milk using MIR spectrometry.The MIR use to estimate iron and zinc contents in powdered milk has also been described (Wu, He, Shi, & Feng, 2009).
Therefore, considering the buriti oil as raw material of economic and social value, in order to demonstrate the possibility of use Fourier transform infrared spectroscopy with attenuated total reflection in direct measurements, without the previous treatment of the sample, as an alternative to the classical methods, the potential of (FTIR-ATR) combined with multivariate calibration (PLS) to the quantification of iron (Fe) in oils extracted from the pulps of buriti fruits was evaluated.

Sampling and Studied Area
The state of Roraima is located in northern Brazil, in the region of the Western Amazon, it borders the states of Amazonas and Pará, as well as the nations of Venezuela (North and West) and Guyana (East and North), with latitude: 1°20′05.1″N and longitude: 61°18′11.6″W. It is a region divided into 15 municipalities that covers a surface area of about 225 000 km 2 .

Sample Preparation
Initially, the pulp of each sample was removed manually, subjected to grinding by a food processor, and was dried in the oven at a controlled temperature of 65 °C for 24 hours.Subsequently, each sample was carefully packaged in filter paper, and was maintained in constant reflux and cycling in the Soxhlet extractor, for 5 hours with 250 mL of ethyl ether (Instituto Adolfo Lutz, 2008).On completion of the extraction, the ethyl ether was recovered and the samples, after being subjected to the rotary vacuum evaporation system, were stored in specific vials with the appropriate numbering.

Acquisition of Spectral Data
Fourier transform mid-infrared spectroscopy coupled with the attenuated total reflection (ATR) technique was used to collect the infrared spectra of Amazon buriti oil samples.The spectra were recorded using the Fourier transform spectrometer "Spectrum Two FT-IR" (PerkinElmer) coupled to the ATR accessory.A new background spectrum was recorded before each sample and the spectra were recorded in a mid-infrared region (4000-450 cm -1 ) using the nominal 4 cm -1 recording resolution.About 100 microliters of sample were used.50 scans were collected for each spectrum.The ATR element was cleaned with ethyl alcohol and dried with soft tissue paper prior to the acquisition of the new spectra.

EDXRF Procedure
Analysis of the iron (Fe) contents present in the buriti oil was performed by Shimadzu EDXRF-720 energy dispersive X-ray fluorescence spectrometry.The following equipment operating conditions were selected: tube voltage of 15 keV (Na to Sc) and 50 keV (Ti to U) with current in the tube of 184 and 25 μA, respectively; 10 mm collimator; real integration time of 300 s; detector dead time of 40 and 39%, under vacuum and Si (Li) detector cooled with liquid nitrogen.One gram of the sample was packed in a polyethylene cup of 20 mm internal diameter and covered with 6 μm thick polypropylene film (Mylar®).

Chemometrics Data Treatment
Partial least squares regression (PLS) is probably the most widely used multivariate calibration method in chemometrics (Kowalski, 1984;Naes, Isaksson, Fearn, & Davies, 2002).It is commonly used in quantitative spectroscopy to correlate spectroscopic data (X) with related physical and chemical data (Y).In PLS, the decomposition of X during regression is guided by the variation in Y: the covariance explained between X and Y is maximized, so that the variation in X directly correlated with Y is extracted.
PLS is based on latent variables and, therefore, can handle highly collinear spectroscopic data in contrast to MLR (Massart, Vandeginste, Deming, Michotte, & Kaufman, 1988).The linear model between the vector Y c , containing the centered reference data, and the matrix X c , containing the centered spectral data, can be described by: where, b is a vector that contains the regression coefficients to be determined during the calibration, and e is the residue.In order to obtain a good estimation of b, the PLS model needs to be calibrated on samples that span the variation in Y well and in general are representative of the future samples.
Models for the estimation of iron contents in the Amazon buriti oil using its spectral measurements were performed with PLS regression.A definite PLS calibration model was constructed, using full cross-validation, employing the data of the selected samples and selected variables.Constructed model was used to predict the iron values for five samples (validation samples), using their spectral data (external validation).All data manipulation cited was done using The Unscrambler 9.2 software.

MIR Spectra
Figure 1 shows the raw FTIR-ATR spectrum (4000-450 cm -1 ) of buriti oil.Can be observed that all spectrum is dominated by some peaks, the vibration at 3005 cm -1 is assigned as CH stretching, related to =C-H bonding.In the with mean relative errors less than ±7%.The methodology used showed in agreement to the concepts of the green method because it did not use reagents that are harmful to the environment or operator and it enabled fast and efficient analysis with minimal manipulation of the sample.