[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.

[Association between parainfluenza virus infection and climatic factors in children].

OBJECTIVE: To study the association between acute respiratory human parainfluenza virus (HPIV) infection and climatic factors in children. METHODS: A total of 2 526 throat swab samples were collected from children with acute respiratory infection who visited the Pediatric Clinic of Shanghai Jiading Nanxiang Hospital between 2011 and 2013. HPIV was detected by multiplex RT-PCR. Related meteorological data were collected, including monthly mean temperature, monthly mean humidity, and monthly total rainfall. The association between HPIV detection rate and climatic factors was analyzed by Spearman's or Pearson test. RESULTS: During the three years, the overall HPIV detection rate was 5.62% (142/2 526), and HPIV-1 was the most common type (46.5%), followed by HPIV-3 (31.0%), HPIV-2 (17.6%), and HPIV-4 (4.9%). There were significant differences in the detection rates of HPIV-1 and HPIV-2 in different seasons, and the detection rates of both were the highest in summer (P<0.05). HPIV positive rate was positively correlated with monthly mean temperature (r=0.598; P<0.01) and monthly total rainfall (rs=0.602; P<0.01). CONCLUSIONS: The activity of HPIV in children is correlated with climatic factors, particularly temperature and rainfall.

Synthesis and Characterization of Emulsifiers Based on the Maillard Reaction and Its Application in Stabilized DHA Algal Oil Nanoemulsions.

The aim of this study was to optimize the formation of sodium caseinate (CS) and gum arabic (GA) complexes through the Maillard reaction and to evaluate their effectiveness in improving the emulsification properties and stability of docosahexaenoic acid (DHA) nanoemulsions. First, the best target polysaccharides were selected, and the best modification conditions were determined using orthogonal experiments. Secondly, the response surface experiments were used to optimize the preparation process of the emulsion. The stability, in vitro digestion characteristics, and rheological characteristics of the emulsion prepared by means of CS-GA were compared with the emulsion prepared using a whey protein isolate (WPI). After the orthogonal test, the optimal modification conditions were determined to be a reaction time of 96 h, a CS-GA mass ratio of 1:2, a reaction temperature of 60 °C, and a degree of grafting of 44.91%. Changes in the infrared (IR), Raman, ultraviolet (UV), and endogenous fluorescence spectra also indicated that the complex structure was modified. The response surface test identified the optimal preparation process as follows: an emulsifier concentration of 5 g/L, an oil-phase concentration of 5 g/L, and a homogenization frequency of five, and the emulsion showed good stability. Therefore, the use of a nanoemulsion as a nanoscale DHA algal oil delivery system is very promising for extending the shelf life and improving the stability of food.

[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.

Selection of Salt-Tolerance and Ester-Producing Mutant Saccharomyces cerevisiae to Improve Flavour Formation of Soy Sauce during Co-Fermentation with Torulopsis globosa.

Soy sauce, as a traditional seasoning, is widely favoured by Chinese and other Asian people for its unique colour, smell, and taste. In this study, a salt-tolerance Saccharomyces cerevisiae strain HF-130 was obtained via three rounds of ARTP (Atmospheric and Room Temperature Plasma) mutagenesis and high-salt based screening. The ethanol production of mutant HF-130 was increased by 98.8% in very high gravity fermentation. Furthermore, ATF1 gene was overexpressed in strain HF-130, generating ester-producing strain HF-130-ATF1. The ethyl acetate concentration of strain HF-130-ATF1 was increased by 130% compared to the strain HF-130. Finally, the soy sauce fermentation performance of Torulopsis globosa and HF-130-ATF1 was compared with T. globosa, HF-130, HF-130-ATF1, and Torulopsis and HF-130. Results showed ethyl acetate and isoamyl acetate concentrations in co-fermentation of T. globosa and HF-130-ATF1 were increased by 2.8-fold and 3.3-fold, respectively. In addition, the concentrations of ethyl propionate, ethyl caprylate, phenylethyl acetate, ethyl caprate, isobutyl acetate, isoamyl alcohol, phenylethyl alcohol, and phenylacetaldehyde were also improved. Notably, other three important flavour components, trimethylsilyl decyl ester, 2-methylbutanol, and octanoic acid were also detected in the co-fermentation of T. globosa and HF-130-ATF1, but not detected in the control strain T. globosa. This work is of great significance for improving the traditional soy sauce fermentation mode, and thus improving the flavour formation of soy sauce.

Preparation of liposome encapsulating angiotensin-I-converting enzyme inhibitory peptides from sunflower protein hydrolysates.

Liposomal angiotensin-I-converting enzyme inhibitory (ACEI) peptides were prepared from sunflower protein hydrolysates by the thin­film ultrasonic method. Response surface methodology (RSM), in combination with fractional factorial designs and central composite design methods were utilized to optimize entrapment efficiency and balance the drug release. We found that the ratio of phospholipids to cholesterol, ultrasound time and the ratio of phospholipids to ACEI peptides were significant factors affecting entrapment efficiency (P<0.001). Optimal preparation conditions of liposomal­ACEI peptides were the ratio of soybean phospholipids to cholesterol (w/w) of 4.1:1, PEG­2000 dosage (%) of 4, NaCl concentration in PBS (mM) of 50, hydration temperature of 45˚C, ultrasound time of 8.05 min and the ratio of soybean phospholipids to ACEI peptides of 15:1 (w/w). The experimental entrapment efficiency of liposomal­ACEI peptides was (91.25±0.182%). Moreover, the balanced release rate of liposome encapsulated ACEI in phosphate buffer was 77.83% after 12 h.

Determination of florfenicol amine residues in animal edible tissues by an indirect competitive ELISA.

Florfenicol (FF) is a broad-spectrum antibiotic used increasingly in aquaculture, livestock, and poultry to treat diseases. To avoid using labor-intensive instrumental methods to detect residues of FF in food and food products, a simple and convenient indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) method for florfenicol's major metabolite, florfenicol amine (FFA), was developed using a polyclonal antibody prepared in this study. FFA was covalently attached to carrier protein as immunogen by using the glutaraldehyde method. The antibodies obtained were characterized by an ELISA method and showed excellent specificity and sensitivity with the 50% inhibition values (IC 50) of 3.34 microg/L for FFA in PBS buffer. In the ELISA, sample extractions were performed by ethyl acetate/ammonium hydroxide (90 + 10, v/v) following combined acid hydrolysis of FF and its known metabolites. The limits of detection (LOD) calculated from the analysis of 20 known negative swine muscle, chicken muscle, and fish samples were 3.08, 3.3, and 3.86 microg/kg (mean + 3 SD), respectively. Recoveries of FFA fortified at the levels of 5, 50, 100, and 300 microg/kg ranged from 64.6 to 124.7%, with coefficients of variation of 11.3-25.8% over the range of FFA concentrations studied. Validation of the ELISA method with FFA-fortified swine muscle at the levels of 10, 50, 100, and 200 microg/kg was carried out using GC, resulting in a similar correlation in swine muscle ( r = 0.97). The results suggest that this ELISA is a specific, accurate, and sensitive method, which is suitable for use as a screening method to detect residues of FFA in animal edible tissues.