Oil Content Of Corn Research Articles

Constructing stable emulsion gel from gelatin and sodium alginate as pork fat substitute: Emphasis on lipid digestion in vitro

This study aimed to develop a gelatin-sodium alginate (G-SA) emulsion gel that can efficiently hold corn oil, as a substitute for pork fat while controlling the digestive behaviors of lipids in vitro. UV, fluorescence, and circular dichroism spectra and surface hydrophobicity measurements of the G-SA mixtures indicated that gelatin and sodium alginate primarily form aggregates through hydrogen bonds and hydrophobic interactions, and the optimum gelatin-to-sodium alginate w/w ratio was identified as 1.9. The final emulsion gel contained 3.15% gelatin and 1.65% sodium alginate (w/w) with a corn oil content of 40% (w/w). G-SA emulsion gel had a higher proportion of polyunsaturated fatty acids (PUFAs, 53.95 g/100 g) than pork fat (15.17 g/100 g). In addition, the G-SA emulsion gel exhibited stable viscoelastic properties without storage and loss moduli changes at increasing shear rates. The G-SA emulsion gel had a higher melting temperature (42.63 °C) than pork fat (35.07 °C). In vitro digestion studies showed that corn oil had a higher free fatty acid release (40.32%) compared to the G-SA emulsion gel (12.66%) and pork fat (8.53%) (P<0.05), indicating that the digestibility of corn oil was reduced in the G-SA emulsion gel. Calcein release experiments revealed that G-SA emulsion gel released the least amount of calcein (P<0.05) during digestion at a slow rate. The G-SA emulsion gel, similar to pork fat, contained evenly distributed digestive particles encapsulating corn oil after in vitro gastric digestion, with the smallest particle size among the treatments. After the in vitro small intestinal digestion phase, the G-SA emulsion gel maintained small droplet sizes with bridging flocculation. The in vitro digesta of the G-SA emulsion gel contained a significantly higher proportion of PUFAs compared to pork fat (P<0.05). Consequently, the G-SA emulsion gel can be a potential substitute for pork fat, offering higher proportions of PUFAs, lower fat content, and controlled lipid digestion with reduced lipid digestibility.

Pickering emulsions based on ovalbumin‐ferulic acid‐sodium alginate supramolecular hydrogels: application to cookies replacing margarine

SummaryMargarine contains trans fatty acids, which have been linked to adverse effects on human health. It is therefore of the utmost importance to develop superior margarine substitutes for use in baked foods. The protein‐polyphenol‐polysaccharide ternary supramolecular system displays remarkable stability and can be utilised in the formulation of emulsions for partial margarine replacement. The aim of this study was to examine the stability of an ovalbumin (OVA)‐ferulic acid (FA)‐sodium alginate (SA) ternary supramolecular emulsion with varying water‐to‐oil ratios. The emulsion was evaluated for its potential as a substitute for margarine in cookies. The findings revealed that the specific emulsion instability of the system initially increased and subsequently decreased with an increase in corn oil content, reaching an optimal point of stability and dispersibility at a water‐to‐oil ratio of 5:11. As the emulsion was incorporated into the cookie dough at levels ranging from 0% to 100% margarine, the viscoelasticity of the dough was enhanced and the hardness was reduced. As the emulsion content increased in place of margarine, the cookies exhibited visible cracks on the surface, accompanied by an increase in hardness, baking loss rate and a notable change in colour. The cookies demonstrated the optimal quality when the emulsion content was 40%.

Functional and emulsification characteristics of phospholipids and derived o/w emulsions from peony seed meal

Peony seed phospholipids (PPLs), a kind of multifunctional plant-like phospholipids were extracted from peony seed meal. We investigated the functional properties of PPLs and compared their emulsification performance in corn oil-peony seed oil o/w emulsion systems with that of soy lecithin (DPLs). The PPLs were characterized with the higher content of phosphatidylcholine (PC) (416 ± 28 mg/g) and lyso-phosphatidylcholine (LPC) (43 ± 14 mg/g) fractions, and lower content of phosphatidylethanolamine (PE) (71 ± 13 mg/g). The polyunsaturated fatty acids showed higher content (83.25%), with the highest content of linoleic acid (46.05%) in PPLs. PPLs-emulsions showed smaller average particle size and higher loaded peony seed oil content at pH 5, temperature 50 °C, and about 60% corn oil content. PPLs-emulsions imparted better hydroxyl radical scavenging efficiency and reducing power than DPLs. Our results suggest that PPLs can be used as emulsifiers with improved antioxidant properties.

Algorithm of Stability-Analysis-Based Feature Selection for NIR Calibration Transfer.

For conventional near-infrared spectroscopy (NIR) technology, even within the same sample, the NIR spectral signal can vary significantly with variation of spectrometers and the spectral collection environment. In order to improve the applicability and application of NIR prediction models, effective calibration transfer is essential. In this study, a stability-analysis-based feature selection algorithm (SAFS) for NIR calibration transfer is proposed, which is used to extract effective spectral band information with high stability between the master and slave instruments during the calibration transfer process. The stability of the spectrum bands shared between the master and slave instruments is used as the evaluation index, and the genetic algorithm was used to select suitable thresholds to filter out the spectral feature information suitable for calibration transfer. The proposed SAFS algorithm was applied to two near-infrared datasets of corn oil content and larch wood density. Simultaneously, its calibration transfer performances were compared with two classical feature selection methods. The effects of different preprocessing algorithms and calibration transfer algorithms were also assessed. The model with the feature variables selected by the SAFS obtained the best prediction. The SAFS algorithm can simplify the spectral data to be transferred and improve the transfer efficiency, and the universality of the SAFS allows it to be used to optimize calibration transfer in various situations. By combining different preprocessing and classic feature selection methods with this, the sensitivity of the correlation between spectral data and component information are improved significantly, as well as the effect of calibration transfer, which will be deeply developed.

Increased corn oil intake during an allergy sensitization period aggravates food allergy severity after oral allergen exposure.

Egg white (EW) allergy model mice underwent 15-day oral immunotherapy (OIT) using diets with different corn-oil content and 1% EW. After OIT, mortality following an oral food challenge in OIT groups was approximately 90%. However, in previous studies, mortality was 0%. This phenomenon is to be associated with increased corn-oil intake during allergy sensitization and allergen exposure for 2 weeks.

Moving-Window-Improved Monte Carlo Uninformative Variable Elimination Combining Successive Projections Algorithm for Near-Infrared Spectroscopy (NIRS)

The MC-UVE-SPA method is commonly proposed as a variable selection approach for multivariate calibration. However, the SPA tends to select wavelength variables that are sparsely distributed over the wavelength ranges of the variables selected by the MC-UVE algorithm, and the MC-UVE-SPA cascade cannot improve the problem of wavelength point discontinuity. It is addressed in this paper by proposing a moving-window- (MW-) improved MC-UVE-SPA wavelength selection algorithm. The proposed algorithm improves the continuity of the selected wavelength variables and thereby better exploits the advantages of the MC-UVE algorithm and the SPA to obtain regression models with high prediction accuracy. The MC-UVE, MC-UVE-SPA, and MC-UVE-SPA-MW algorithms are applied for conducting wavelength variable selection for the NIR spectral absorbance data of corn, diesel fuel, and ethylene. Here, partial least squares regression (PLSR) models reflecting the oil content of corn, the boiling point of diesel fuel, and the ethylene concentration are established after conducting wavelength selection using the MC-UVE algorithm, and corresponding multiple linear regression (MLR) models are established after conducting wavelength selection using the MC-UVE-SPA and MC-UVE-SPA-MW algorithms. Experimental results demonstrate that the progressive elimination of uncorrelated and collinear variables generates increasingly simplified partial-spectrum models with greater prediction accuracy than the full-spectrum model. Among the three wavelength selection algorithms, the MC-UVE-SPA selected the least number of wavelength variables, while the proposed MC-UVE-SPA-MW algorithm provided models with the greatest prediction accuracy.

Tuning Microcapsule Shell Thickness and Structure with Silk Fibroin and Nanoparticles for Sustained Release.

Microcapsules have attracted widespread interest for their unique properties in encapsulation, protection, and separation of active ingredients from the surrounding environment. However, microcapsule carriers with controllable shell thickness, permeability, good mechanical properties, and thermostability are challenging to obtain. Herein, robust and versatile composite microcapsules were fabricated using SiO2 nanoparticle-stabilized (Pickering) oil emulsions as core templates, while silk fibroin (SF) was assembled at the oil/water interface. This process resulted in the formation of physically and chemically stable microcapsules with a thick (∼800 nm) shell that protected the encapsulated ingredient from high shear forces and high temperatures during spray-drying. SiO2 nanoparticles were randomly distributed in the shell matrix after preparation, making the microcapsules mechanically robust (4.48 times higher than control samples prepared using surfactant Tween 80 instead of the SiO2 nanoparticles), as well as thermostable (retained shape to 900 °C). The microcapsules displayed tunable drug release by adjusting the SF content in the shell. Under optimal conditions (weight ratio of SiO2/SF = 7:10, corn oil content about 55 wt %), a model drug (curcumin) was encapsulated in the SF microcapsules with an encapsulation efficiency up to 95%. The in vitro drug release from these SF microcapsules lasted longer than control microcapsules, demonstrating the capability of these novel microcapsules in sustaining drug release.

Feasibility Assessment of Synchronous Fluorescence Spectral Fusion by Application to Argan Oil for Adulteration Analysis.

Synchronous fluorescence spectroscopy (SFS) is used for quantitative analysis as well as for qualitative analysis, such as with classification methods. With SFS, determination of a useful wavelength interval between the excitation and emission wavelengths (Δλ) is required. There are a multitude of Δλ intervals that can be evaluated and optimization of the best one is complex. Presented here is a fusion approach for combining Δλ intervals, thereby negating the need to perform the selection by a skilled operator. To demonstrate the feasibility of omitting selection of the best Δλ interval, adulterated argan oil samples are studied. Argan oil is made from the argan tree, endemic to southwestern Morocco, and is well-known for its cosmetic, pharmaceutical, and nutritional applications. It is considered a luxury product and exported from Morocco around the world. Consequently, detection of argan oil adulteration followed by quantitative analysis of the adulterant concentration is important. This study uses fusion of SFS spectra obtained at ten Δλ intervals to first detect adulteration of argan oil by corn oil and then determination of the corn oil content. For detection of adulteration, 15 one-class classification methods were used simultaneously over the ten Δλ sets of SFS spectra. For tuning parameter dependent classifiers such as Mahalanobis distance, non-optimized classifiers are used. Raw classification values are used, removing the need to set classifier-dependent threshold values, albeit, ultimately, a fusion decision rule is needed for classification. For quantitative analysis, two calibration approaches are evaluated with fusion of these ten Δλ SFS spectral data sets. One is multivariate calibration by partial least squares (PLS). The second approach is a univariate calibration process where the SFS spectra are summed over respective SFS spectral ranges, also known as the area under the curve (AUC). For adulteration detection and quantitation of the corn oil, prediction errors decrease with fusion compared to individually using the ten Δλ interval SFS specific data sets. For this argan oil data set, the AUC method generally provides equivalent prediction errors to PLS.

Virgin Coconut Oil Compared to Corn Oil in World Health Organization Formula on Glutathione, TNF-α, and Body Weight Gain in Severe Malnourished Wistar Rat

Background: Severe malnutrition remains a major killer of children under five years old. On such condition, there is a lack of antioxidants, an increase in free radical agents and proinflammatory cytokine. They prolong a hypercatabolic state, hindering an increase in weight. Virgin coconut oil (VCO) contains medium chain triglyceride and antioxidants. It is expected to solve that problem compared to corn oil. There has been no published study about VCO usage for severe malnutrition. Objective: The aim of this study was to find out the influence of VCO compared to corn oil for severe malnutrition treatment in GSH level, TNF-α level, and weight gain. Methods: It was a laboratory experiment study, using a randomized post-test control group design, to compare the treatment effect of the VCO vs corn oil in Formula 75 and Formula 100 in the treatment of severe malnourished rat. Severe malnourished rats were divided randomly into 2 groups. One group was given F75 and F100 with VCO content (Group A) and another group was given F75 and F100 with corn oil content (group B). Both groups were treated for 28 days. Results: There were 19 rats in each group. One rat from group B died before the study ended. An analysis was done for the last 37 rats. There was no significant difference in the mean of weight gain, 73.45 g (SD 20.08) and 68.97 g (SD 11.49) for group A and B respectively (p=0.41). There was no significant difference in the GSH levels (p=0.70), where group A is 1.35 pg/g (SD (0.74) and group B 1.27 pg/g (SD 0.48). TNF-α level in group A (1087.2 pg/g (320.00-2525.46)) was higher than group B (711.32 pg/g (403.19-2400.91)) but not statistically significant (p=0.08). Conclusion: There is no significant difference in GSH and TNF-α level in the liver and body weight gain for VCO and corn oil groups. Virgin coconut oil can be one of the alternative vegetable oils that can be utilized in treating severe malnourishment.Â

Protective role of flaxseed oil on hypercholesterolemic rats

The present study aims to investigate the effects of replacing corn oil content (10%) in the standard diet of hypercholesterolemic rats (fed standard diet + 2% cholesterol for 4 weeks) with 50, 75 and 100% levels of flaxseed oil on the body weight gain, organ weight, blood glucose, liver and kidney functions and lipid profile. Data showed that 2% cholesterol administration caused significant increase in glucose, ALT, AST, ALP, urea, uric acid, triglyceride, total lipids, total cholesterol, LDL and VLDL levels in serum of hypercholesterolemic rats. Body weight gain and organ weight also significantly increased as compared to control rats. Consumption flaxseed oil at different replacement level diets by hypercholesterolemic rats resulted in significant decrease in body weight gain, organ weight and lipid parameters except HDL which decrease as compared to hypercholesterolemic rats fed standard diet. Blood glucose level, liver functions and kidney functions were also improved.

Quantitative Analysis of Near-Infrared Spectra by Wavelet-based Interferences Removal and Least Squares Support Vector Regression

A new hybrid algorithm named EODT-LS-SVR based on least squares support vector regression (LS-SVR) with wavelet-based EODT algorithm as preprocessed tools is proposed for removing the interferences and developing the quantitative models with high precision in near-infrared (NIR) spectra. EODT-LS-SVR algorithm is composed of two steps. In the first step, the preprocessing algorithm named EODT, which combines the ideas of wavelet packet transform (WPT), orthogonal signal correction (OSC) and information theory, is employed for the characteristic extraction of analyte information through multi-scale analysis. Entropy-based baseline signal removing (EBSR) algorithm is applied to remove the baseline of the spectra based on information theory with WPT-based analysis, and then the information orthogonal to the concentrations of analyte is removed by OSC algorithm in each frequency band of spectra. In the second step, LS-SVR method coupled with grid search and particle swarm optimization (PSO) technique for parameters optimization is used to enhancing the quality of regression models. EODT-LS-SVR algorithm was validated by two NIR spectral datasets, one used for measuring the fat concentration of milk and the other used for measuring the oil content of corn. The comparison of prediction results demonstrated that the performance of calibration models developed by EODT-LS-SVR algorithm is better than that developed by other conventional algorithms, showing the high efficiency and the high quality for quantitative model development in NIR spectra of complex samples.

Effect of pH and addition of corn oil on the properties of gelatin-based biopolymer films

Response surface methodology (RSM) was used to investigate pH and corn oil (CO) addition on gelatin film properties. Test films were evaluated for thickness ( T), tensile strength (TS), puncture strength (PT), percentage elongation at break point ( E), water vapour permeability (WVP) and oxygen permeability (OP). T, TS and PT increased linearly ( P < 0.01) with increasing CO content, but were not significantly affected by pH. pH had both linear and quadratic effects on E values ( P < 0.01), while CO content had a lesser effect. WVP decreased as the pH of the film-forming solutions was adjusted away from pH 7.0 or CO addition level increased above 27.25%. OP was affected in both a quadratic and linear manner by pH adjustment and CO addition, respectively. Optimal film-forming conditions were pH (10.54) and CO level (55.18%, w/w), as predicted by response surface methodology. Scanning electron microscopy (SEM) was performed to investigate the microstructures of gelatin films, and confocal scanning laser microscopy (CSLM) was used to investigate fat distributions and protein phase in gelatin films.

Synthesis of long-chain polyunsaturated fatty acids in lactating mammary gland: role of Δ5 and Δ6 desaturases, SREBP-1, PPARα, and PGC-1

The purpose of this work was to study whether rat lactating mammary gland can synthesize PUFAs through the expression of Delta5 and Delta6 desaturases (Delta5D and Delta6D), whether these enzymes are regulated by the transcription factors sterol-regulatory element binding protein 1 (SREBP-1) and peroxisome proliferator-activated receptor alpha (PPARalpha) and the coactivator peroxisome proliferator-activated receptor gamma coactivator 1beta (PGC-1beta), and whether these desaturases are regulated by the lipid concentration in the diet. The results showed that on day 12 of lactation, approximately 35% of the linoleic acid in the diet, which is the precursor of PUFAs, is transferred to the mammary gland. There was expression of Delta5D and Delta6D in mammary gland, and it was regulated by the corn oil content in the diet. The higher the corn oil content in the diet, the lower the expression of both desaturases. Induction of Delta5D and Delta6D was associated positively with similar changes in SREBP-1 and PGC-1beta. Expression of PPARalpha was barely detected and was not affected by the corn oil content in the diet, whereas PGC-1beta expression increased as the corn oil in the diet increased. These results indicate that the lactating mammary gland has the capacity to synthesize PUFAs and can be regulated by the lipid content in the diet.

Improvement of the gelling properties of meat emulsion gel by the addition of porcine sarcoplasmic proteins

ABSTRACTThe effects of porcine sarcoplasmic proteins (SP) on the physicochemical properties of meat emulsion gel were examined. Meat emulsion was prepared from water‐washed pork meat (WWM), corn oil and SP. Whole SP (W‐SP) enhanced the breaking stress of the WWM emulsion gel as well as other animal proteins in the presence of 0.2 mol/L NaCl. The breaking stress of the emulsion with W‐SP increased with an increase in corn oil content. Furthermore, this tendency was more noticeable at a lower NaCl concentration (0.15 mol/L) rather than at 0.45 mol/L NaCl. Ammonium sulfate (AS) treatment fractionated W‐SP into three portions (SP‐f1, SP‐f2 and SP‐f3), which were the precipitates at 0–50% and 50–75% AS saturation and the supernatant at 75% AS saturation, respectively. The fractions SP‐f2 and SP‐f3 increased the gel strength more than W‐SP. In particular, the fraction SP‐f3 increased the gel strength approximately 10‐fold compared to the control. Sodium dodecyl sulfate‐polyacrylamide gel electrophoresis analysis showed that SP‐f3 had several kinds of proteins and a main protein with a molecular mass of 35 kDa, which corresponded to glyceraldehyde 3‐phosphate dehydrogenase. These results indicate that the influence of SP should not be ignored when processing of low‐salt meat products and the fraction SP‐f3 has a gel‐enhancing factor for myofibrillar proteins.

Fracture and textural properties of low fat egg yolk gels containing emulsion droplets

The influence of corn oil content and the type of emulsifier on the fracture and textural properties and the expressible liquid of gels prepared by heat-treatment of low-fat yolk protein concentrate (YPC) containing emulsified oil has been investigated. Oil incorporation in the form of fine droplets results in a decrease of gel network strength, the textural parameter values depending on the amount of added oil. Tween 20 (polyoxyethylene sorbitan monolaurate) when used as the oil emulsifier brings about a reduction in gel textural parameter values compared to liquid egg yolk, the result depending on the emulsion droplet size. Additionally, the gels differ in their yielding behaviour since the latter yield but do not fracture at strain values as high as 0.7 while the former fracture at relatively low strains and their fracture stress and strain parameter values depend on oil droplet size. This behaviour is explained in terms of the effect of the surfactant on the yolk constituents and, particularly, its interactions with the yolk apoproteins, which result in stiffer bulk gel network structure.

Effect of Dietary Corn Oil Content on the Urinary Excretion Ratio of N^1-Methylnicotinamide and Its Pyridones in Rats

Effect of Dietary Corn Oil Content on the Urinary Excretion Ratio of N^1-Methylnicotinamide and Its Pyridones in Rats

Hepatic prolactin binding in female Sprague-Dawley rats fed a diet high in corn oil.

The relationship between dietary fat content and hepatic prolactin (PRL) binding during the four stages of the estrous cycle was examined. Serum 17 beta-estradiol, PRL, and progesterone were also monitored in the same animals. Female SD rats were fed 5 or 24% corn oil in nutritionally balanced diets, given 2.5 mg 7,12-dimethylbenz[a]anthracene [(DMBA) CAS: 57-97-6] or vehicle by gavage at 8 weeks of age, and decapitated at noon on 1 of the 4 days of the estrous cycle 2-5 weeks later. Analysis of hepatic PRL binding data by Scatchard plots revealed no effect of diet or DMBA. PRL binding was lowest at proestrus, increased at estrus, remained elevated at metestrus, and declined at diestrus. Diet also had no effect on serum hormone concentrations, which showed the expected pattern during the estrous cycle in all treatment groups. Results reported by others of an effect of dietary corn oil content on hepatic PRL binding may have been due to use of control diets low in essential fatty acids.

Commercial Herbicide Influence on Corn Oil Composition

Qualitative and quantitative oil content of corn (Zea maysL.) kernels as influenced by herbicides was measured by gas-liquid chromatography. Alachlor [2-chloro-2′,6′-diethyl-N-(methoxymethyl) acetanilide] at 0 to 6.7 kg/ha, atrazine [2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine] at 0 to 5.6 kg/ha, linuron [3-(3,4-dichlorophenyl)-1-methoxy-1-methylurea] at 0 to 3.4 kg/ha, prometryne [2,4-bis(isopropylamino)-6-(methylthio)-s-triazine] at 0 to 3.4 kg/ha, and cyanazine [2-[4-chloro-6-(ethylamino)-s-triazine-2-yl]amino-2-methylpropionitrile] at 0 to 7.8 kg/ha were evaluated. Oil quantity was not greatly influenced by any of the herbicides; however, percentage corn oil fatty acid composition was altered to a minor but statistically significant degree by each of the herbicides. The use of alachlor, cyanazine, atrazine, linuron, or prometryne on corn at recommended rates or at rates greater than currently recommended field application rates did not induce serious changes in either total oil content or fatty acid distribution in corn.

Effect of Kernel Position on Oil Content in Corn (Zea mays L. )1

Amount of oil per kernel in maize is affected by position on the ear. Kernels highest in oil are located at mid‐ear position. Due to larger mass, the basal kernels possess a greater total amount of oil than the kernels of the central and tip positions.

Heritability of Variations in Oil Content of Individual Corn Kernels

Nuclear magnetic resonance spectroscopy was used to determine oil content of individual corn kernels in order to evaluate this technique as an aid in the development of strains having greater oil content. This method is rapid and does not impair viability. Individual kernels from a selfed single-cross ear ranged from 2.7 to 5.4 percent oil and were significantly correlated (r = +0.75) with the oil content of their progeny ears. This indicates that the single-kernel differences in oil content were heritable, and this method may greatly increase selection efficiency in breeding for higher oil content in corn.