Corn Oil Samples Research Articles

A sensitive intelligent point-of-care test method for tert-butylhydroquinone in edible oil via a test strip with a smartphone

Tert-butylhydroquinone (TBHQ) is easily overused or illegally added to edible oil and attracts a growing concern because of its cytotoxic, liver-damaging, and carcinogenic effects. Thus, a sensitive and intelligent point-of-care testing (iPOCT) method is developed to fulfill the on-site monitoring. This iPOCT method depended on a fluorescent immunochromatographic assay within 15 min. Under optimization, the limit of quantification (LOQ) was calculated as 0.03 μg mL-1. The iPOCT method provided a low limit of detection (LOD) of 0.02 μg mL−1, a wide linear range of 0.03–100 μg mL−1, and great selectivity. Recoveries by the spiking experiments ranged from 97.4% to 103.5% with relative standard deviations (RSDs) of 2.4%–4.9% in soybean, peanut, rapeseed, and corn oil samples. The results showed that the iPOCT method is highly consistent with the high-performance liquid chromatography (HPLC) method.

Chemical transesterification of coconut and corn oils using different metal hydroxides as catalysts to determine the chemical and physiochemical changes to the oils.

The transesterification of butteroil has been shown to alter its lipid chemistry and thus alter the crystallization of the fat. The reaction kinetics and resulting crystallization of the butteroil differ depending on the nature of the catalyst used. Modeling the reaction with vegetable oils is a simpler method for the analysis of resulting products to understand the chemical and physiochemical changes that occur based on catalyst selection. The objective of this work is to perform a chemical transesterification of coconut and corn oil using monovalent and divalent catalysts to investigate the chemical and crystal changes that occur. Coconut and corn oil were subjected to chemical transesterification using both Ca(OH)2 and KOH as catalysts. In both the coconut and corn oil samples, transesterification caused monoglycerides (MAGs) and diacylglycerides (DAGs) to form from the most abundant fatty acid found in each sample. Coconut oil's melting temperature, solid fat content (SFC), and storage modulus decreased as a result of the transesterification, and crystals began to form in the corn oil causing melting thermograms to be evident, higher SFC, and a more viscous oil as a result. Using Ca(OH)2 as a catalyst resulted in more MAG formation, and a higher SFC and melting temperature than when KOH was used as a catalyst. The results demonstrate that the chemical changes that result from transesterification of plant-based oils change the crystallization behavior of the oils and can therefore be used for different applications in the food industry. © 2024 The Author(s). Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Monitoring of Chlorpyrifos Residues in Corn Oil Based on Raman Spectral Deep-Learning Model.

This study presents a novel method for the quantitative detection of residual chlorpyrifos in corn oil through Raman spectroscopy using a combined long short-term memory network (LSTM) and convolutional neural network (CNN) architecture. The QE Pro Raman+ spectrometer was employed to collect Raman spectra of corn oil samples with varying concentrations of chlorpyrifos residues. A deep-learning model based on LSTM combined with a CNN structure was designed to realize feature self-learning and model training of Raman spectra of corn oil samples. In the study, it was discovered that the LSTM-CNN model has superior generalization performance compared to both the LSTM and CNN models. The root-mean-square error of prediction (RMSEP) of the LSTM-CNN model is 12.3 mg·kg-1, the coefficient of determination (RP2) is 0.90, and the calculation of the relative prediction deviation (RPD) results in a value of 3.2. The study demonstrates that the deep-learning network based on an LSTM-CNN structure can achieve feature self-learning and multivariate model calibration for Raman spectra without preprocessing. The results of this study present an innovative approach for chemometric analysis using Raman spectroscopy.

Comparison of the performance of different one-dimensional convolutional neural network models-based near-infrared spectra for determination of chlorpyrifos residues in corn oil

This study introduces a fast analytical approach for detecting chlorpyrifos residues in corn oil, based on a one-dimensional convolutional neural network (1D-CNN) structure for near-infrared (NIR) spectral deep learning models. Data augmentation algorithms were introduced to effectively expand the database of corn oil samples obtained in the experiment, ensuring sufficient training of the deep learning network. A well-designed 1D-CNN structure was implemented to create a multivariate calibration model. This model can be used to quantify chlorpyrifos residues in corn oil. The study found that using data augmentation with a 1D-CNN model led to improved performance compared to using the original spectra calibration in the model. Particularly, the 1D-CNN model’s best overall performance was achieved using data augmented with varying degrees of signal-to-noise ratio (SNR) algorithms, with a prediction coefficient of determination (RP2) of 0.9492 and a relative percent deviation (RPD) of 4.4569. The study demonstrates the feasibility of using NIR spectral deep learning models for quantitative analysis of pesticide residues in edible oils. Furthermore, data augmentation methods can effectively improve the accuracy of deep learning algorithms in NIR spectral chemometrics model calibration.

Authentication of vegetable oils using isotope mass spectrometry

Vegetable oils play an important role in the human diet. Both the physiological value of the product and its cost largely depend on the type of processed raw materials. In this regard, the establishment of the type of vegetable raw materials used for the production of vegetable oils is an important area of research in the identification of this product type. To date, one of the most informative methods for assessing the authenticity of plant raw materials is the method of isotope mass spectrometry. Thirty samples of vegetable oils produced from various raw materials and places of origin (Italy, Greece, Spain, Turkey, Armenia, Russia, Slovenia) were studied. The isotopic ratios of carbon, oxygen and hydrogen were measured in the samples. It is shown that the samples of corn oil (C4 type of photosynthesis) are characterized by the highest values of the indicator δ13C, from –17.00‰ to –17.73‰. The rest of the studied samples of vegetable oils were produced from C3 plants (grape seed oil, olive, linseed, sesame, pumpkin, mustard, sunflower, etc.). For them, the values of δ13C lie in the range from –26.60‰ to –31.14‰. Thus, the method of isotope mass spectrometry makes it possible to detect the introduction of corn oil into a product produced from plants with C3 type of photosynthesis, even in small quantities. In addition, this method enables establishing the introduction of cheap oils into corn oil. The values of the indicators δ18O and δ2H largely depend on the year of harvest and the climatic characteristics of the region where the raw materials grow. Thus, the values of the isotopic characteristics of the δ18O structural components of the oil samples from grape seeds produced in Turkey, Armenia and Italy have significant differences (19.40± 0.77‰, 16.55± 0.66‰ and 23.29± 0.93‰, respectively). The values of the isotopic characteristics of hydrogen δ2H of the sample from Armenia differed from the values of the samples from Turkey and Italy in the direction of a higher content of “light” isotopes (–189.86± 1.13‰, —163.17 ± 0.97‰ and –160.72± 0.97‰, respectively). The annual monitoring of these values, the creation of a database, as well as the use of statistical analysis methods will allow in the future identifying vegetable oils by their geographical origin with a high degree of reliability.

Optimisation and validation of a modified QuEChERS method for the determination of 222 pesticides in edible oils using GC-MS/MS: a case study on corn oil

ABSTRACT Recently, various pesticides have been employed at different stages of cultivation to protect the oil crop from insect, disease, and weed. Those pesticides, especially lipophilic ones, bio-accumulate in the oilseeds and get co-extracted into edible oils during the refining process. Hence, this study aimed to optimise an extraction method for routine pesticide multi-residue analysis in edible vegetable oil samples using gas chromatography coupled to tandem mass spectrometry (GC – MS/MS). Two parameters were optimised using a factorial design of experiment (solvent type and solvent/sample ratio). In general, the number of pesticides that conformed to our criteria (mean recovery 70–120%) increased as the solvent/sample ratio increased. Each of the three tested solvents had an advantage over the other, ethyl acetate showed the highest capability for non-polar pesticides extraction, acetonitrile had the highest sensitivity, and the ethyl acetate/acetonitrile mixture showed the highest number of pesticides with acceptable criteria. The three solvents were tested using two different cleanup sorbents (EMR, and Z-Sep), the best solvent/cleanup combination was found to be ethyl acetate/acetonitrile mixture in addition to Z-Sep. The final method was validated in accordance with the European guidelines for Analytical Quality Control and Method Validation Procedures for Pesticide Residues Analysis in Food and Feed (SANTE/11312/2021). The precision and trueness of the method were determined from recovery experiments on six replicates of spiked blank corn oil samples at 0.01, 0.025, and 0.05 mg/kg. The number of pesticides that showed accepted criteria were 130, 166, and 182 out of 222 for each spiking level respectively.

Chronic Treatment With WY-14643 Induces Tumorigenesis and Triglyceride Accumulation in Mouse Livers.

Peroxisome proliferator-activated receptor α (PPARα) is closely related to lipid metabolism and various liver diseases. Previous study has shown that chronic treatment with PPARα agonist WY-14643 can induce liver tumors in rodents, but the implications of this process on lipid metabolism in the liver remain unclear. Thus, this study aimed to explore the influences of chronic treatment with WY-14643 on the liver and hepatic lipid metabolism. Wild-type C57BL/6 mice were treated with WY-14643 (100 mg/kg/week, i.p.) or corn oil, and liver and serum samples were collected for testing after 42 weeks of WY-14643 treatment. The results showed that hepatomegaly, liver tumors with mild liver injury, and hepatocyte proliferation were induced in mice treated with WY-14643. The mRNA and protein expression levels of PPARα downstream targets acyl-CoA oxidase 1 and cytochrome P450 4A were significantly upregulated in the WY-14643-treated group. Lipidomic analysis revealed that chronic treatment with WY-14643 disturbed lipid homeostasis, especially triglycerides (TGs), which were significantly elevated after WY-14643 treatment. Moreover, TG homeostasis-related genes were significantly increased in the WY-14643-treated group. In conclusion, these findings demonstrated that hepatomegaly and liver tumors induced by chronic treatment with WY-14643 in mice are accompanied by hepatocyte proliferation and TG accumulation. SIGNIFICANCE STATEMENT: The present study clearly demonstrated that sustained peroxisome proliferator-activated receptor α (PPARα) activation by chronic treatment with WY-14643 induces hepatomegaly and liver tumors with triglyceride accumulation by regulating lipid homeostasis-related genes in mice. These findings may help to clarify the influences of sustained PPARα activation on liver lipid homeostasis and provide data for the clinically rational use of drugs that can activate PPARα.

Exposure assessment of aflatoxins and zearalenone in edible vegetable oils in Shandong, China: health risks posed by mycotoxin immunotoxicity and reproductive toxicity in children.

Human exposure to aflatoxins (AFs) and zearalenone (ZEA) has not been sufficiently investigated. Here, we analyzed the exposure level and health risks posed by AFs (B1, B2, G1, G2) and ZEA through cooking oil consumption in Shandong, China. The individual daily consumption of cooking oil was calculated through 2745 questionnaires during 2017-2019. The average contamination levels of mycotoxins were estimated by examining 60 cooking oil samples. For the peanut oil, AFs ranged from <0.2 to 274 μg/kg, with a positive rate of 66.6% (20/30). Average levels of 36.62 μg/kg AFB1 and 44.43 μg/kg total AFs were found. Over-the-limit level (20 μg/kg) of AFB1 was detected in 8/30 samples. Estimated daily intake (EDI) and margin of exposure (MOE) for age-stratified population groups showed that children are facing highest adverse health risk with AFB1 (MOE 5.88-6.39). The liver cancer incidences attributable to AFB1 exposure are non-negligible as 0.896, 0.825, and 0.767 cases per 100,000 for 6-14 age group, 15-17 age group, and adult labor-intensive workers. Over-the-limit level (60 μg/kg) ZEA contamination was detected in 25/30 corn oil samples with a 50th percentile value of 97.95 μg/kg. Our health risk assessment suggested significant health risks of enterohepatic (inflammation and cancer), reproductive, and endocrine systems posed by AFs and ZEA. However, the health risk of immunotoxicity is unclear because currently animal study data are not available for the immunotoxicity induced after long-term exposure. In general, the health risks posed by mycotoxins are non-negligible and long-term mycotoxin surveillance is necessary.

Characterization of Corn Oil Using Fluorescence Spectroscopy.

In these studies, Fluorescence spectroscopy has been utilized for the characterization of pure and commercially available corn oil. The best excitation wavelength of 380nm has been investigated, where maximum spectral information can be assessed. The emission spectra from pure and commercial corn oil samples disclosed that pure corn oil contained oleic acid, beta-carotenes, chlorophylls, isomers of vitamin E and traces of oxidized products which exhibit fluorescence at 406, 525, 675, 440 and 435/475nm respectively. Whereas, commercial corn oils lack these valuable ingredients and only contain fats along with their primary and secondary oxidized products that emit a broad emission band centred at 440nm. The study has also depicted that Fluorescence spectroscopy can even be used to select best quality corn oil among pure corn oil samples with different varieties and seed origins. In addition, the effect of temperature on the composition of pure and commercial corn oil samples have also been investigated by heating them at 100, 120,140, 160, 180 and 200°C each sample for 30min. This was done because corn oil is being used for cooking where it is generally heated up to 120°C and for deep frying up to 180°C. On heating, in pure corn oil, deterioration of Vitamin-E and beta-carotenes occurred with an increase in the oxidation products, whereas, in commercial oil samples, only the concentration of oxidation products increased. However, it was found that up to 140°C, pure corn oil can be used safely for cooking purpose where it does not lose much of its valuable ingredients while in commercial corn oils, fat composition does not alter much up to 180°C and after that oxidized products start to increase rapidly.

Rapid and sensitive noncompetitive immunoassay for detection of aflatoxin B1 based on anti-immune complex peptide

Noncompetitive immunoassays for small molecules are generally considered to be more sensitive than competitive ones. In this study, a phage-peptide against immune complex of aflatoxin B1 (AFB1) and nanobody Nb28 was obtained by phage-display technology. The phage-peptide was labeled with peroxidase and used to develop a direct noncompetitive magnetic-chemiluminescent enzyme-linked immunoassay (Nc-MCLEIA) for AFB1. The 50% signal saturation concentration (SC50) and limit of detection (LOD) of Nc-MCLEIA for AFB1 were 0.089 and 0.006 ng/mL, respectively. Compared with competitive immunoassays developed by the Nb28, the sensitivity and efficiency of Nc-MCLEIA were greatly improved. The recoveries of AFB1 from spiked corn, rice, flour, peanut, peanut oil and corn oil samples ranged from 83.8% to 119.2% with coefficient of variable under 8.9%. Furthermore, parallel analysis of natural corn, rice and flour samples by Nc-MCLEIA and HPLC (high performance liquid chromatography) proved that the Nc-MCLEIA was reliable.

An ultrasensitive CH3NH3PbBr3 quantum dots@SiO2-based electrochemiluminescence sensing platform using an organic electrolyte for aflatoxin B1 detection in corn oil

Mycotoxins contamination, especially aflatoxin B1 (AFB1) in edible oils, is a health hazard. Therefore, AFB1 trace analysis methods are urgently needed. Electrochemiluminescence (ECL) is a popular sensing method because of its low background interference and high sensitivity. However, existing ECL assays for AFB1 detection are based on aqueous rather than oil systems. Herein, we report a CH3NH3PbBr3 quantum dots (MAPB QDs)@SiO2-based ECL sensor for AFB1 quantification in corn oil using an organic electrolyte. The luminophore loading and stability of the MAPB QDs@SiO2 particles were significantly improved compared to those of bulky MAPB materials, resulting in an enhanced ECL response. Further, exploiting molecular imprinting technology, an ECL sensor for AFB1 detection with an ultra-low detection limit of 8.5 fg/mL was prepared. The reliability of the sensor was confirmed by comparable recoveries of corn oil samples with those obtained by high-performance liquid chromatography, indicating its potential for food safety evaluation.

Non-destructive detection of multi-component heavy metals in corn oil using nano-modified colorimetric sensor combined with near-infrared spectroscopy

This study attempts to develop a novel nano-modified colorimetric sensor combined with near-infrared spectroscopy (NIRS) for heavy metals (Pb and Hg) detection in corn oil samples. The colorimetric sensor was made of chemical response dyes, and dimethylpyrimidine amine (DPA) with high affinity and porous silica nanospheres (PSNs) were used to modify and improve its sensitivity and stability. Colorimetric sensors sensitive to Pb and Hg for detecting mixed heavy metals (Pb and Hg) were screened using an olfactory visualization system. The colorimetric sensor data were collected using NIRS (899.20–1724.71 nm), and the reflection spectrum data of mixed heavy metals in corn oil samples were analyzed using various partial least squares (PLS) models. These results highlight the accuracy of the sensors for Hg and Pb detection. The ACO-PLS model produced the best detection result at a low concentration (10–100 ppb) of heavy metals. The Rp2 values for predicting Pb and Hg in corn oil containing interfering heavy metals (Mg2+, Zn2+, CO2+, Na2+, and K2+) were 0.9793 and 0.9510, and the limit of detection (LOD) were 5 and 7 ppb, respectively. ICP-MS was used to validate the effectiveness and stability of the methods. Finally, the developed method shows great potential for non-destructive detection of multi-component heavy metals in edible oil.

A label-free electrochemical aptasensor based on AuNPs-loaded zeolitic imidazolate framework-8 for sensitive determination of aflatoxin B1

In this study, an electrochemical aptasensor for sensitive detection of aflatoxin B1 (AFB1) was fabricated by electrodepositing gold nanoparticles (AuNPs) on the glass carbon electrode (GCE) modified with zeolitic imidazolate framework-8 (ZIF-8). The high specific surface area of AuNPs/ZIF-8 nanocomposite increased the aptamers loading on the electrode surface. When compared to other previously reported sensors, the developed aptasensor exhibited a wider linear range of 10.0 to 1.0 × 105 pg/mL with a lower limit of detection (LOD) of 1.82 pg/mL under the optimized conditions. Furthermore, the obtained results revealed that the constructed aptasensor exhibited outstanding selectivity, reproducibility and stability. Moreover, the aptasensor was successfully employed to detect the AFB1 in corn oil and peanut oil samples, with recoveries ranging from 93.49% to 106.9%, demonstrating the potential application value of this methodology.

Enhancing oxidative stability of tocopherol-enriched edible oils using short-term exposure to microwave irradiation.

The effect of microwave irradiation on the oxidative stability of tocopherol-enriched corn oil at temperatures of 60 or 100°C was evaluated using the Rancimat assay. Short durations of microwave treatment (1min) on 10-g oil aliquots were found to increase the induction period of corn oil samples containing 500 and 1000ppm tocopherol by 7.7% and 9.9%, respectively compared to control oils. The moisture content of tocopherol-enriched corn oil decreased by 15% compared to that of corn oil after 1min of microwave treatment. At 100°C, 1000ppm tocopherol-enriched corn oil received 3min of microwave treatment had 5.8% and 9.9% lower primary and secondary oxidation products than control groups, respectively while this effect was not clearly observed for oils stored at 60°C. However, 15min of microwave irradiation accelerated the rates of lipid oxidation in corn oils irrespective of the addition of tocopherol. Content of α- and γ-tocopherols in 1min of microwave irradiated samples remained more by 28.8 and 5.8%, respectively than those of controls after 9h heat treatment at 100°C. Overall, microwave irradiation within 3min can increase the oxidative stability of 10g-corn oils, especially at 100°C, which could be due to the reduced moisture content in the bulk oil matrix. Practical Application: A microwave oven is an irreplaceable home appliance and is widely used in households. Short time exposure to microwave irradiation can remove moisture efficiently from edible oils without the formation of oxidation products, which could increase the oxidative stability of these oils, especially under frying conditions. The results of this study can be utilized to ensure a longer shelf-life of fried products in the food industry by short time treatment of microwave irradiation.

Determination of Multiple Mycotoxins and Their Natural Occurrence in Edible Vegetable Oils Using Liquid Chromatography-Tandem Mass Spectrometry.

The prevalence of mycotoxins is often increased by the climatic conditions prevailing in tropical regions. Reports have revealed the contamination of mycotoxins in some types of vegetable oil. However, vegetable oil is one of the essential ingredients used in food preparation. Thus, this study determined the occurrence of multi-mycotoxins in six types of vegetable oils commercially available in Thailand to assess the consumer health risk. In total, 300 vegetable oil samples (olive oil, palm oil, soybean oil, corn oil, sunflower oil, and rice bran oil) collected from various markets in Thailand were analyzed for the presence of nine mycotoxins, namely, aflatoxin B1 (AFB1), aflatoxin B2 (AFB2), aflatoxin G1 (AFG1), aflatoxin G2 (AFG2), beauvericin (BEA), ochratoxin A (OTA), zearalenone (ZEA), fumonisin B1 (FB1), and fumonisin B2 (FB2) using a quick, easy, cheap, effective, rugged, and safe (QuEChERS)-based procedure and a triple quadrupole mass spectrometer equipped with an electrospray ionization source. The incidences of mycotoxin contamination varied among the different types of oil samples. AFB1, AFB2, ZEA, FB1, and FB2 were most frequently found in contaminated samples. AFB2, BEA, ZEA, FB1, and FB2 contaminated olive oil samples, whereas AFB1, AFB2, AFG2, and OTA contaminated palm oil samples. AFB1, AFB2, and ZEA were found in soybean oils, whereas ZEA, FB1, and FB2 contaminated corn oil samples. AFB1 and AFG1 contaminated sunflower oil samples, whereas AFB1, AFB2, AFG1, and OTA were detected in rice bran oil samples. However, the contamination levels of the analyzed mycotoxins were below the regulatory limits.

Comparative 1H NMR-Based Chemometric Evaluations of the Time-Dependent Generation of Aldehydic Lipid Oxidation Products in Culinary Oils Exposed to Laboratory-Simulated Shallow Frying Episodes: Differential Patterns Observed for Omega-3 Fatty Acid-Containing Soybean Oils.

Soybean oil is the second most exported oil from the United States and South America, and is widely marketed as a cooking oil product containing numerous health benefits for human consumers. However, culinary oils with high polyunsaturated fatty acid (PUFA) contents, are known to produce high quantities of lipid oxidation products (LOPs), including toxic aldehydes upon exposure to high-temperature frying episodes. Previous studies have demonstrated causal links between aldehyde ingestion and inhalation with deleterious health perturbations, including mutagenic and carcinogenic effects, along with cardiovascular and teratogenic actions. In this study, aldehydic LOPs were detected and quantified in commercially available samples of soybean, avocado, corn and extra-virgin olive oil products before and after their exposure to laboratory-simulated laboratory frying episodes (LSSFEs) using high-resolution 1H nuclear magnetic resonance (NMR) analysis. Results acquired demonstrated that PUFA-rich soybean and corn oils gave rise to the highest concentrations of oil aldehydes from the thermo-oxidation of unsaturated fatty acids, whereas monounsaturated fatty acid (MUFA)-laden avocado and olive oils were much more resistant to this peroxidation process, as expected. Multivariate chemometrics analyses provided evidence that an orthogonal component pattern of aldehydic LOPs featuring low-molecular-mass n-alkanals such as propanal, and 4-oxo-alkanals, arises from thermo-oxidation of the ω-3 fatty acid (FA) linolenic acid (present in soybean oils at levels of ca. 7% (w/w)), was able to at least partially distinguish this oil from corresponding samples of thermally-stressed corn oil. Despite having a similar total PUFA level, corn oil has only a negligible ω-3 FA content, and therefore generated significantly lower levels of these two aldehyde classes. In view of the adverse health effects associated with dietary LOP ingestion, alternative methodologies for the incorporation of soybean oils within high-temperature frying practices are proposed.

Effect of Chemical Refining Steps on the Some Micro and Macro Element Content and Quality Parameters in Corn Oil

In this study, it was aimed to determine some element contents and some quality properties and to compare these parameters at each stage in the chemically refining process of crude corn oil. Color (lovibond tintometer), free fatty acidity, peroxide values and fatty acid compositions were determined in the samples of corn oil taken from consecutive stages of chemically refining. Also, the content of elements (Na, Mg, K, Ca, Fe, Pb, Cd, Ni, Mn, Zn, Co, Cr, P, Cu) was analyzed, by using inductively-coupled plasma-mass spectrometry (ICP-MS) and inductively-coupled plasma-optical emission spectrometry (ICP-OES) after microwave digestion. The color (Lovibond tintometer), free fatty acidity and peroxide values in the chemically refining process varied between 2.7-16, %0.09-2.12, 10.95-1.08 mEqO2/kg, respectively. Oleic, linoleic and linolenic acid contents changed between 30.486-30.580%, 54.339-54.703% and 0.972-0.993%, respectively, in the chemically refining stages. While no trans fatty acids detected in crude corn oil and after degumming-neutralization step, very low amount of trans oleic acid (0.040%) and total trans linoleic acid (0.132%) was detected in bleached corn oil. The total trans fatty acid content little more increased in the last stage of the chemically refining. However, total trans fatty acid content of refined corn oil was &lt; 0.3%. It was clearly seen that Na, Mg, K, P, Ca, Mn, Fe, Pb, Ni, Cr, Cu element contents decreased significantly at the end of the chemically refining process. Although Cd, Co and Zn elements were determined in crude corn oil, these elements were not detected in the refined corn oil. The results obtained showed that the chemically refining process effected some of the quality properties of corn oil and especially the changes in the element contents.

Preconcentration and Determination of Zearalenone in Corn Oil by a One-Step Prepared Polydopamine-Based Magnetic Molecularly Imprinted Polymer (MIP) with High-Performance Liquid Chromatography with Fluorescence (HPLC-FLD) Detection

A polydopamine-based molecularly imprinted polymer with quercetin as the mimic template was deposited on the surface of ferroferric oxide nanoparticles (Fe3O4@PDA MIPs) and used for the purification and enrichment of zearalenone prior to the determination by high-performance liquid chromatography with fluorescence detection (HPLC-FLD). Adsorption experiments showed that the maximum capacity of Fe3O4@PDA MIPs toward zearalenone was 1.49 mg/g and the process matched the Langmuir isotherm model. Parameters of the analysis, such as the mass of MIPs, pH, ultrasonication time, elution solvent and volume, were optimized. Good linearity with the zearalenone concentration from 1 to 20 ng/mL was obtained (R = 0.9998). The limit of detection was 0.68 ng/mL. The recoveries from spiked corn oil samples were 93.8% to 101.0% with relative standard deviations from 6.5% to 9.1%. In addition, reusability experiments indicated that Fe3O4@PDA MIPs may be reemployed at least 7 times. These results demonstrate that the prepared Fe3O4@PDA MIPs were effective for the selective preconcentration of zearalenone from corn oil. The developed method was more reliable, faster, and lower cost than the National Standard Method of China.

A selective ensemble preprocessing strategy for near-infrared spectral quantitative analysis of complex samples

Preprocessing of raw near-infrared (NIR) spectra is typically required prior to multivariate calibration since the measured spectra of complex samples are often subject to overwhelming background, light scattering, varying noises and other unexpected factors. Various preprocessing methods have been developed aimed at removing or reducing the interference of these effects. However, it is usually difficult to determine the best preprocessing method for a given data. Instead of selecting the best one, a selective ensemble preprocessing strategy is proposed for NIR spectral quantitative analysis. Firstly, numerous preprocessing methods and their combinations are obtained by full factorial design in order of baseline correction, scattering correction, smoothing and scaling. Then partial least squares (PLS) model is built for each preprocessing method. The models which have better predictions than PLS are selected and their predictions are averaged as the final prediction. The performance of the proposed method was tested with corn, blood and edible blend oil samples. Results demonstrate that the selective ensemble preprocessing method can give comparative or even better results than the traditional selected best preprocessing method. Therefore, in the framework of selective ensemble preprocessing, more accurate calibration can be obtained without searching the best preprocessing method.

Comprehensive Investigation of Thermal Degradation Characteristics and Properties Changes of Plant Edible Oils by FTIR-Spectroscopy

Abstract Structural characterization of edible oils after thermal treatment was made by (FTIR) spectroscopy. Olive, corn and sunflower oil samples were thermally treated at three consecutive cycles. Each cycle consisted of heating at the boiling point for 8 h, followed by cooling at room temperature for 16 h. At the end of each cycle the characteristics of oils were studied by FTIR spectroscopy and standard methods. Study of FTIR spectra of the treated oils revealed that the heating of oils caused significant changes in the intensities of their bands and produced shifts in the position of specific bands such as 3008 cm−1 and 1745 cm−1. The level of oil oxidation during different heating period was followed by the absorbance ratio at 3530/3472 cm−1. Additionally, the absorbance ratio 2853/3008 cm−1 was used as a measure of degree of unsaturation. The thermal heating of oils produced an initial decrease in the specific absorbance ratios which could be attributed to the reduction of unsaturated fatty acid content due to oxidation process. The results in this study demonstrated that FTIR could be used for assessment of the state of oils by using specific absorbance ratios as indicators.