Multifaceted analysis of the effects of roasting conditions on the flavor of fragrant Camellia oleifera Abel. seed oil.

Fragrant Camellia oleifera Abel. seed oil (FCSO), produced by a roasting process, is popular for its characteristic aroma. This study investigated the effects of various roasting temperatures (90℃, 120℃, 150℃, 180℃) and durations (20 min, 40 min, 60 min) on the flavor of FCSO by physicochemical properties, hazardous substances, sensory evaluation, and flavor analyses. The results showed that FCSO roasted at 120℃/20 min had a reasonable fatty acid composition with a lower acid value (0.16 mg/g), peroxide value (0.13 g/100 g), p-anisidine value (2.27), dibutyl phthalate content (0.04 mg/kg), and higher 1,1-diphenyl-2-picrylhydrazyl free radical scavenging activity (224.51 µmol TE/kg) than other samples. A multivariate analysis of FCSO flavor revealed that the 120℃/20 min group had a higher grassy flavor score (5.3 score) from nonanoic acid and a lower off-flavor score (2.2 score) from 2-methylbutyric acid. The principal component analysis showed that 120℃/20 min could guarantee the best flavor and quality of FCSO. Therefore, this information can guide the preparation of FCSO.

Effect of enzymatic Maillard reaction conditions on physicochemical properties, nutrition, fatty acids composition and key aroma compounds of fragrant rapeseed oil.

BACKGROUND: A new enzymatic hydrolysis-based process inspired by the Maillard reaction can produce strong flavored, high-value rapeseed oil that meets safety requirements. In the present study, the effect of reaction time (10-30 min) and temperature (130-160 °C) on the physicochemical properties, nutritional status, fatty acids composition and key aroma compounds of fragrant rapeseed oil (FRO) was investigated. RESULTS: An increasing reaction time and temperature substantially decreased the total tocopherol, polyphenol and sterol contents of FRO, but increased benzo[a]pyrene content, as well as the acid and peroxide values, which did not exceed the European Union legislation limit. Among the volatile components, 2,5-dimethyl was the main substance contributing to the barbecue flavor of FRO. The 150 °C for 30 min reaction conditions produced a FRO with a strong, fragrant flavor, with high total tocopherol (560.15 mg kg-1 ), polyphenol (6.82 mg kg-1 ) and sterol (790.65 mg kg-1 ) contents; acceptable acid (1.60 mg g-1 ) and peroxide values (4.78 mg g-1 ); and low benzo[a]pyrene (1.39 mg g-1 ) content. These were the optimal conditions for the enzymatic Maillard reaction, according to the principal component analysis. Furthermore, hierarchical cluster analysis showed that reaction temperature had a stronger effect on FRO than reaction time. CONCLUSION: The optimal enzymatic Maillard reaction conditions for the production of FRO are heating at 150 °C for 30 min. These findings provide new foundations for better understanding the composition and flavor profile of FRO, toward guiding its industrial production. © 2023 Society of Chemical Industry.

Optimization of Composite Decolorizer Efficacy Based on Decolorization Efficiency, Toxicity, and Nutritional Value of Rice Bran Oil.

This study compared the effect of five different adsorbents (activated clay, activated carbon, attapulgite clay, bentonite, diatomite) on the levels of nutrients, harmful substance retention, and decolorization in rice bran oil. Among the adsorbents tested, activated carbon displayed the highest decolorization efficiency (82.90%) and adsorption effect on 3,4-benzopyrene (BaP, 89.53%) and 3-monochloropropane-1,2-diol ester (41.55%), whereas activated clay had the highest oryzanol retention percentages (85.98%) and affordability. Activated carbon and activated clay were therefore selected as composite decolorizing agents. Based on single-factor and Box-Behnken response surface tests, the optimal conditions for decolorization efficiency (97.08%), oryzanol retention (89.62%), sterol retention (90.16%), vitamin E retention (79.91%), and benzo(a)pyrene adsorption percentages (95.98%) were determined to be achieved by using a 5% (w/w) composite decolorant (activated clay:activated carbon=5:1), at a temperature of 116℃, with an incubation time of 33 min. This study provides evidence to support the efficacy of compound decolorants, which may have practical use in large-scale industrial applications of edible oil decolorization during refinement.

Assessment of the Physicochemical Properties of Fragrant Rapeseed Blended Hotpot Oil by Principal Component Analysis.

In this study, a nutritious, healthy Chongqing hotpot oil with excellent flavor was blended while considering nutrition, flavor, and health aspects. Four blended hotpot oils prepared from fragrant rapeseed, palm, sesame, and chicken oils were analyzed to determine their physicochemical properties, antioxidant capacities, levels of harmful substances, and nutritional compositions, and their sensory qualities were evaluated. Principal component analysis was performed to identify the best hotpot oil (10% chicken oil + 20% palm oil + 10% sesame oil + 60% fragrant rapeseed oil), which exhibited good antioxidant capacity (Oxidation Stability Index: 7.95 h; 2,2-diphenyl-1-picrylhydrazyl: 168.6 µmol/kg, 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonate): 116.7 µmol/kg, and ferric-reducing/antioxidant power: 63.9 µmol/kg), a high sensory score (7.7/10), stable physicochemical properties (acid value: 0.27 mg/g and peroxide value: 0.01 g/100 g), and high tocopherol (54.22%), and phytosterol retention (98.52%) after boiling for 8 h. Although the 3,4-benzopyrene content of this hotpot oil exceeded the EU standard after boiling for 7 h, the increase in the amount of harmful substances was the lowest.

Physicochemical properties of rice bran blended oil in deep frying by principal component analysis.

This study aimed to obtain a rice bran blended oil with good quality in deep frying. The thermal stability, nutrients and harmful substances of rice bran oil (RBO) and other four oils (palm oil, PO; cottonseed oil, CO; sunflower oil, SuO; soybean oil, SO) were analyzed. Besides, the blended oil formulas were established by the principal component analysis method, and their physicochemical properties, frying characteristic indicators, nutrients, and harmful substances were compared. The results provided that two suitable blended oil formulas (F1: 50% RBO + 40% PO + 10% CO; F2: 60% RBO + 35% PO + 5% CO) of good frying performance were attained by principal component analysis. The acid value (1.19 mg/g), peroxide value (0.09 meq/kg), residual oil rate (8.07%), 3-MCPD ester reduction content (2.33 mg/kg), benzopyrene concentration content (0.95 µg/kg) and vitamin E consumption rate (67.86%) in F2 were lower than that in F1. Moreover, the oryzanol retention rate (87.84%) of F2 was higher than that of F1. In summary, F2 was more conducive to human health and more suitable than F1 in deep-frying. This information had an important directive on the industrial production of rice bran blend oil. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-022-05472-7.

Comparison of Different Extraction Processes on the Physicochemical Properties, Nutritional Components and Antioxidant Ability of Xanthoceras sorbifolia Bunge Kernel Oil.

In this study, we investigated and compared the oil yield, physicochemical properties, fatty acid composition, nutrient content, and antioxidant ability of Xanthoceras sorbifolia Bunge (X. sorbifolia) kernel oils obtained by cold-pressing (CP), hexane extraction (HE), aqueous enzymatic extraction (AEE), and supercritical fluid extraction (SFE). The results indicated that X. sorbifolia oil contained a high percentage of monounsaturated fatty acids (49.31-50.38%), especially oleic acid (30.73-30.98%) and nervonic acid (2.73-3.09%) and that the extraction methods had little effect on the composition and content of fatty acids. X. sorbifolia oil is an excellent source of nervonic acid. Additionally, the HE method resulted in the highest oil yield (98.04%), oxidation stability index (9.20 h), tocopherol content (530.15 mg/kg) and sterol content (2104.07 mg/kg). The DPPH scavenging activity rates of the oil produced by SFE was the highest. Considering the health and nutritional value of oils, HE is a promising method for X. sorbifolia oil processing. According to multiple linear regression analysis, the antioxidant capacity of the oil was negatively correlated with sterol and stearic acid content and positively correlated with linoleic acid, arachidic acid and polyunsaturated fatty acid content. This information is important for improving the nutritional value and industrial production of X. sorbifolia.

Effects of roasting and deodorisation on 3-monochloropropane-1, 2-diol esters, 3, 4-benzopyrene and trans fatty acids in peanut oil.

Hazardous substances are readily produced during roasting and deodorisation in the preparation of peanut oil. The aim of this work was to investigate the variation of 3-monochloropropane-1, 2-diol ester (3-MCPDE), 3, 4-benzopyrene (BaP) and trans fatty acid (TFA) contents in the roasting and deodorisation segments of peanut oil production process. Roasting temperatures and durations significantly affected the contaminants contents in peanut oil; they increased significantly at a roasting temperature >210°C and time >60 min. In the deodorisation segment, the BaP and TFA contents were over the standard limits at a deodorisation temperature >210°C and time >140 min. Analysis showed that 3-MCPDE was significantly correlated with the formation of C18:2T (r = 0.979) and there was a linear relationship between BaP and C18:1T (Y = 0.509 C18:1T). This information will provide guidance for the precise and appropriate processing of peanut oil.

Comparative Analysis of Rapeseed Oils Prepared by Three Different Methods.

Flavoured rapeseed oils prepared using traditional technologies (oils A and B) and a fragrant rapeseed oil obtained using an enzymatic Maillard reaction (oil C) were analysed to show that oil C featured basic indicators and a fatty acid composition similar to those of traditional oils while exhibiting a higher comprehensive sensory evaluation score. Volatile component, odour activity value (OAV), and relative odour activity value (ROAV) analyses revealed that oil C had an elevated content of pyrazines (20.83%) and aldehydes (38.15%), which resulted in stronger charred and caramel flavours. The aroma of oil C was directly impacted by 3-methylbutyraldehyde (OAV > 1) and was modified by 3-methylthiopropionaldehyde and nonanal (RAOV > 1 in both cases). Thus, the developed technology was found to be well suited for the production of novel and safe fragrant rapeseed oil.

The modulatory effect of infusions of green tea, oolong tea, and black tea on gut microbiota in high-fat-induced obese mice.

Tea consumption has been identified to have an anti-obesity effect. Whether it is associated with gut microbiota modulation is investigated in this study. Phenolic profiles of infusions of green tea, oolong tea and black tea were comprehensively compared first, by utilizing ultra-performance liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOFMS). Subsequently, high-fat-diet induced obese C57BL/6J mice were orally administered these three types of tea infusions for 13 weeks to evaluate their anti-obesity and gut microbiota modulatory effects. In general, 8 phenolic acids, 12 flavanols, 9 flavonols, 2 alkaloids and 1 amino acid were identified from the three types of tea infusions. Though they possess diverse phenolic compounds, no significant differences in the prevention of the development of obesity in high-fat-fed mice were discovered among the three types of tea. Based on high-throughput MiSeq sequencing and multivariate statistical analysis, it was revealed that tea infusion consumption substantially increased diversity and altered the structure of gut microbiota. The linear discriminant analysis effect size algorithm identified 30 key phylotypes in response to high-fat diet and tea, including Alistipes, Rikenella, Lachnospiraceae, Akkermansia, Bacteroides, Allobaculum, Parabacteroides, etc. Moreover, Spearman's correlation analysis indicated that these key phylotypes might have a close association with the obesity related indexes of the host. This study provides detailed information regarding the impact of tea consumption on gut microbiota, which may be helpful in understanding the anti-obesity mechanisms of tea.

[Qualitative-Quantitative Analysis of Rice Bran Oil Adulteration Based on Laser Near Infrared Spectroscopy].

The purpose of this study is mainly to have qualitative-quantitative analysis on the adulteration in rice bran oil by near-infrared spectroscopy analytical technology combined with chemo metrics methods. The author configured 189 adulterated oil samples according to the different mass ratios by selecting rice bran oil as base oil and choosing soybean oil, corn oil, colza oil, and waste oil of catering industry as adulterated oil. Then, the spectral data of samples was collected by using near-infrared spectrometer, and it was pre-processed through the following methods, including without processing, Multiplicative Scatter Correction(MSC), Orthogonal Signal Correction(OSC), Standard Normal Variate and Standard Normal Variate transformation DeTrending(SNV_DT). Furthermore, this article extracted characteristic wavelengths of the spectral datum from the pre-processed date by Successive Projections Algorithm(SPA), established qualitatively classified calibration methods of adulterated oil through classification method of Support Vector Machine(SVM), optimized model parameters(C, g) by Mesh Search Algorithm and determined the optimal process condition. In extracting characteristic wavelengths of the spectral datum from pretreatment by Backward interval Partial Least Squares(BiPLS) and SPA, quantitatively classified calibration models of adulterated oil through Partial Least Squares(PLS) and Support Vector Machine Regression(SVR) was established respectively. In the end, the author optimized the combination of model parameters(C, g) by Mesh Search Algorithm and determined the optimal parameter model. According to the analysis, the accuracy of prediction set and calibration set for SVC model reached 95% and 100% respectively. Compared with the prediction of the adulteration oil content of rice bran oil which was established by the PLS model, the SVR model is the better one, although both of them could implement the content prediction. Furthermore, the correlation coefficient R is above 0.99 and the Root Mean Square Error (MSE) is below 5.55 x 10(-4). The results show that the near-infrared spectroscopy technology is effective in qualitative-quantitative analysis on the adulteration of rice bran oil. And the method is applicable to analyze adulteration in other oils.

[Low carbon number fatty acid content prediction based on near-infrared spectroscopy].

The rapid prediction of the low-carbon fatty acids (C < or = 14) content in grease samples was achieved by a mathematical model established by near infrared spectroscopy combined with support vector machine regression (SVR). In the present project, near-infrared spectrometer SupNIR-5700 was used to collect near-infrared spectra of 58 samples; partial least square (PLS) was applied to remove the strange samples, and principal component analysis (PCA) was conducted on the measurements; radial basis function (RBF) kernel function was selected to establish a regression model supporting vector machine, and then detailed analysis and discussions were conducted concerning their spectral preprocessing and parameters optimization methods. Experimental results showed that by applying particle swarm optimization (PSO) the model demonstrated improved performance, stronger generalization ability, better prediction accuracy and robustness. In the second pretreatment method after PSO, when the optimization parameters are: C = 2.085, gamma = 22.20, the prediction set and calibration set correlation coefficient (gamma) reached 0.998 0 and 0.925 8, respectively; and root mean square errors (MSE) were 0.000 4 and 0.014 3, respectively. Research results proved that the method based on near infrared spectroscopy and PSO-SVR for accurate and fast prediction of the low-carbon fatty acid content in vegetable oil is feasible.