Relative quantification of walnuts and hazelnuts in bakery products using real-time polymerase chain reaction

Two versions of real-time polymerase chain reaction (PCR) for relative quantification of walnuts and hazelnuts in bakery products were developed. The first method is a duplex real-time PCR with 5′-nuclease (TaqMan) probes labelled with FAM and JOE for walnuts and hazelnuts, respectively. The second method uses two real-time PCR assays for walnuts and hazelnuts with TaqMan probes labelled with FAM, carried out in separate microtubes, with normalisation of the results achieved by adding wheat as an internal standard. The internal standard is quantified in a duplex format using the TaqMan probe labelled with JOE. Both methods produced linear calibration curves (r² = 0.9813 for the former method, r² = 0.9992 for the latter) in the range 10–90% (w/w) for walnut–hazelnut mixtures. Almost identical calibration curves were obtained also for walnut–hazelnut mixtures diluted with inert matrix (oat flakes; the inert matrix accounting for 80 and 96% (w/w), respectively). Practical applicability of the developed methods was demonstrated on bakery products from the market. The developed methods will be useful for food control laboratories to facilitate authentication of bakery products with nut filling.     

Semi-quantitative estimation of the walnut content in fillings of bakery products using real-time polymerase chain reaction with internal standard material

A method for absolute quantification of walnuts in fillings of bakery products was developed. Macadamia nuts were used as an internal standard material. A duplex real-time polymerase chain reaction (PCR) with 5′-nuclease (TaqMan) probes labelled with FAM and JOE for walnuts and the internal standard, respectively, was used. Difference between threshold cycle values (Δc _T) for the analyte and the internal standard, plotted against logarithm of contents, was used to construct the calibration line. A level of 5?% (w/w) of the internal standard material was found to be suitable for quantification of walnuts in nut fillings, the calibration line being linear. The developed method was applied to bakery products from the market, and crucial factors for its routine applicability have been identified in sampling and sample preparation. The present study demonstrates that quantification of walnuts in the fillings of bakery products should be achievable by real-time PCR with an internal standard material when the reference filling, which is used for calibration, is comparable to the fillings of the samples, a calibration line of low variability is obtained, and the sample material is properly homogenized before weighing the analytical sample.     

A novel real-time polymerase chain reaction (PCR) method for the detection of hazelnuts in food

A real-time PCR (polymerase chain reaction)-based method for the detection of hazelnuts (nuts of Corylus avellana or C. maxima) in confectionery and bakery products is described. The method consists of DNA isolation by chaotropic solid phase extraction and the subsequent PCR with hazelnut-specific primers and a TaqMan fluorescent probe. The primers and the probe are targeted to the hsp1 gene encoding for a low molecular weight heat-shock protein. The method was positive for five hazelnut varieties approved in Slovakia and negative for all other tested plant materials used in food industry including peanuts, walnuts, almonds, pistachio nuts, cashews and chestnuts. The intrinsic detection limit of the method was 13 pg hazelnut DNA, which corresponds to approximately 27 genome equivalents (1C). Using a series of model pastry samples with defined hazelnut contents, a practical detection limit of 0.01% (w/w) hazelnut was determined. Practical applicability of the PCR method was tested by the analysis of 20 food samples (confectionery and bakery products) along with ELISA. For all of the food samples, identical results were obtained by both methods, which conformed to the labelling. The presented PCR method is useful for sensitive and selective detection of hazelnuts in food samples and can be performed in one working day.     

High-resolution Orbitrap™-based mass spectrometry for rapid detection of peanuts in nuts

Peanut represents one of the most harmful allergenic foods capable of triggering severe and sometimes lethal reactions in allergic consumers upon ingestion of even small amounts. Several proteins capable of inducing allergic reactions that have been recognised by patients’ IgE antibodies have been identified from this nut source. Methods mainly based on ELISA assays have been developed in order to detect peanuts in several food commodities. In addition LC-MS/MS methods based on different mass analysers have also been devised for tracing peanut contamination in different foods achieving low limits of detection. The applicability of a benchtop high-resolution Exactive? mass spectrometer has never been investigated for the rapid screening of peanut contamination in complex food matrices like mixtures of nuts. We report in this paper the design of suitable peanut markers and the development of an high-resolution Orbitrap? mass spectrometer-based method for peanut detection in a mixture of nuts species. With this aim, different types of samples were prepared: (1) nuts-based powder made up of a mixture of hazelnuts, pistachios, almonds and walnuts; and (2) nuts powder fortified with peanuts. Different levels of fortifications were produced and the applicability of the method was tested. Finally, a subset of six peptides fulfilling specific analytical requirements was chosen to check the suitability of the method tailored to the detection of peanuts in nuts-based products, and two of them, peptides VYD and WLG, were selected as quantitative markers. The method proved to be a suitable screening tool to assess the presence of traces of peanuts in other tree nuts with a limit of detection as low as 4 µg of peanuts proteins or 26 µg of peanuts in 1 g of matrix.     

特征峰斜率还原模型快速测定水产品中硝酸盐含量的研究(英文)

Nitrate is closely related to the content of nitrosamine,which is known to be toxic and is determined in aquatic products.In this paper,a new sensitive UV spectrophotometry method based on K-model for rapid determination of nitrate in different kinds of samples was developed.The UV characteristic absorbance points of nitrate were selected and optimized.Under the optimized experimental conditions the calibration equation and K-model were obtained.The calibration curve is linear in the concentration range of 1 to 100μg/ml(R2=0.9973).This method was found to exhibit good accuracy,precision and repeatability.The developed method could be applied to the determination of nitrate in aquatic products and other food products.     

基于高光谱图像特征融合的榛子水分含量测定

采用高光谱图像技术对榛子水分含量进行快速无损检测。采集200个榛子在400~1 000 nm波段的高光谱图像,提取榛子图像区域的平均光谱信息。利用K-S算法划分样品验证集和预测集,使用四种预处理方法对光谱进行预处理。通过竞争自适应加权算法（Competitive Adaptive Reweighted Sampling,CARS）和逐次投影法（Successive Projection Algorithm,SPA）进行光谱特征的提取;灰度共生矩阵法（Gray Level Co-occurrence Matrix,GLCM）提取图像的纹理特征;分别建立基于光谱特征,图像纹理特征以及两者串联融合的偏最小二乘回归（Partial Least Squares Regression,PLSR）和支持向量回归（Support Vector Regression,SVR）模型对榛子水分进行预测。结果表明,CARS和SPA算法能够有效选择特征波长并提升预测性能;图像特征能够对榛子水分进行预测,基于主成分图像提取的图像特征信息建立的模型预测效果更好。光谱图像特征融合能明显提高对榛子水分含量预测的准确率,CARS提取的特征波段结合主成分图像的纹理特征显示出了更好的效果,SVR模型的RMSECV为0.03,RC 为0.97,RMSEP为0.04,RP为0.96。利用高光谱图像和纹理特征能够对榛子水分进行有效预测,为榛子水分含量检测提供了新的方法。     

Simultaneous Determination of Trace Amounts of Cobalt and Nickel in Water and Food Samples Using a Combination of Partial Least Squares Method and Dispersive Liquid–Liquid Microextraction Based on Ionic Liquid

A new, sensitive, and simple combined method including ionic liquid (IL)-based dispersive liquid–liquid microextraction and partial least squares method (PLS) was developed for simultaneous preconcentration and determination of cobalt and nickel in water and food samples. In this work, a small amount of an IL 1-hexyl-3-methylimmidazolium bis (trifluormethylsulfonyl)imid ([Hmim][Tf₂N]) as an extraction solvent was dissolved in ethanol as a disperser solvent and then the binary solution was rapidly injected by a syringe into the water sample containing Co²⁺ and Ni²⁺, which were complexed by 1-(2-pyridylazo)-2-naphthol. After preconcentration, the absorbance of the extracted ions was measured in the wavelength range of 200–700 nm. The partial least squares method was then applied for simultaneous determination of each individual ion. The parameters controlling the behavior of the system were investigated and optimum conditions were selected. Eleven binary mixtures of cobalt and nickel were selected as the calibration set. The calibration models were validated with four synthetic mixtures containing the metal ions in different proportions, which were randomly designed. The best calibration model was obtained by using PLS-1 regression. Calibration graphs were linear in the range of 2.0–20.0 and 2.0–15.0 ng mL^?1 with a limit of detection of 0.65 and 0.32 ng mL^?1 for cobalt and nickel, respectively. The root mean square errors of prediction for cobalt and nickel were 0.4032 and 0.2980, respectively. Satisfactory results were reported for simultaneous determination of trace levels of cobalt and nickel in water, food, and geological certified reference material samples.     

Rapid Analysis of Glucose,Fructose, Sucrose,and Maltose in Honeys from Different Geographic Regions using Fourier Transform Infrared Spectroscopy and Multivariate Analysis

ABSTRACT: Quantitative analysis of glucose, fructose, sucrose, and maltose in different geographic origin honey samples in the world using the Fourier transform infrared (FTIR) spectroscopy and chemometrics such as partial least squares (PLS) and principal component regression was studied. The calibration series consisted of 45 standard mixtures, which were made up of glucose, fructose, sucrose, and maltose. There were distinct peak variations of all sugar mixtures in the spectral “fingerprint” region between 1500 and 800 cm⁻¹. The calibration model was successfully validated using 7 synthetic blend sets of sugars. The PLS 2nd-derivative model showed the highest degree of prediction accuracy with a highest R² value of 0.999. Along with the canonical variate analysis, the calibration model further validated by high-performance liquid chromatography measurements for commercial honey samples demonstrates that FTIR can qualitatively and quantitatively determine the presence of glucose, fructose, sucrose, and maltose in multiple regional honey samples.     

FRACTURE BEHAVIOR AND MECHANISM OF PUFFED CEREAL DURING COMPRESSION

Texture of puffed cereals was determined to develop an instrumental method and to provide a mechanism of compaction under compressive stress. A model solidlike puffed rice at different moisture contents (2.0–8.5%) was subjected to compression testing to determine the fracture/failure characteristics. The force–deformation curves showed three zones and two firmnesses during compression. The different textural parameters were sensitive to moisture content above 6%. The microstructure of puffed rice consisted of many closed air cells having thin cell walls (10–15  µ m) while a compressed sample showed breaking of cell walls with simultaneous development of fracture lines. A mechanism of compaction or failure at macromolecular level for puffed rice has been proposed based on texture data and microstructure.

PRACTICAL APPLICATION

The acceptance of a snack food largely depends on the texture which in turn is related to fracture characteristics. The present paper offers a general method for determining the texture of snacks and similar brittle food products. The developed indices can describe the texture of a snack food. The mechanism of failure, developed in the present work, can also be applied for low-density foods and for prediction of their behavior during compression.     

Rapid screening for pesticides using automated online sample preparation with a high-resolution benchtop Orbitrap mass spectrometer

For pesticide analysis in food products a common approach is to develop a fast multi-residue method that is capable of identifying and quantifying a large number of analytes in various matrices. This study demonstrates rapid screening and accurate mass confirmation of 116 pesticides in oranges and hazelnuts using an automated online sample preparation method with turbulent-flow chromatography technology coupled to a high-resolution benchtop Orbitrap? mass spectrometer. The limits of quantification (LOQs) for the majority of analytes are well below the maximum residue limit (MRL) set by the European Union and the Japanese government. The recoveries were in the range of 70-120% for over 75% of analytes in both matrices. The present methodology is suitable for routine pesticides analysis in food safety laboratories.     

An Analysis of the Non-Volatile Reaction Products of Aqueous Maillard Model Systems at pH 5, using Reversed-Phase HPLC with Diode-Array Detection

An HPLC-diode array detection (HPLC-DAD) method was developed for the direct analysis of reaction products of aqueous Maillard model systems. The method was applied to mixtures of xylose or glucose refluxed with glycine or lysine for up to 120 min with the pH maintained at 5 throughout heating. Four types of chromatographic behaviour were apparent, ie unretained peaks, resolved peaks and two broad bands. Glycine systems were dominated by unretained peaks while systems based on lysine showed all four types of behaviour. By reference to HPLC-DAD data for standard compounds, some of the resolved peaks were tentatively attributed to pyrrole-like and furanone-like compounds.     

A SYBR Green real-time PCR assay to detect and quantify pork meat in processed poultry meat products

Species identification in meat products has grown in interest in recent years since these foodstuffs are susceptible targets for fraudulent labelling. In this work, a real-time PCR approach based on SYBR Green dye was proposed for the quantitative detection of pork meat in processed meat products. For the development of the method, binary meat mixtures containing known amounts of pork meat in poultry meat were used to obtain a normalised calibration model from 0.1 to 25% with high linear correlation and PCR efficiency. The method revealed high specificity by melting curve analysis, being successfully validated through its application to blind meat mixtures, which confirmed its adequacy for pork meat determination. The fully applicability of the method was further demonstrated in commercial meat products, allowing verification of labelling compliance and identification of meat species in processed foods.     

超高效液相色谱法检测焙烤食品馅料中的 二氧化硫脲

目的 建立馅料中二氧化硫脲的超高效液相色谱测定方法。方法 用0.05%乙酸水溶液提取,样品提取液经过离心,乙腈稀释过滤膜过滤后,以HILIC色谱柱为分析柱分离,采用超高效液相色谱-二极管阵列检测器(UPLC - PDA)检测,以乙腈和水为流动相,梯度洗脱,检测波长为284 nm。采用外标法定量。结果 二氧化硫脲的线性范围为0.4 ~ 20 mg/L,相关系数不小于0.999,空白样品的加标回收的回收率为80.6% ~ 102.2%,相对标准偏差为2.6% ~ 5.0%。结论 该方法简便、快速、准确、重现性好,适用于馅料中二氧化硫脲的检测。     

Microstructural changes in hazelnuts during roasting

The microstructure of raw and roasted hazelnuts was investigated with light microscopy (LM). Tissue sections were fixed chemically using a mixture of formaldehyde, glutaraldehyde and buffer. Polyester was used as a resin. Thin sections were prepared by using a grinding method. Thermal changes in the microstructure developed gradually with increasing air temperature, air velocity and roasting time. Roasting led to some degree of cell wall separation and intercellular spaces, partial disruption of cytoplasmic network, swollen and aggregated protein bodies. These changes were observed in the microstructure of extremely liked quality of hazelnuts (roasted at 165 °C, 1 m/s, 25 min.). Due to the increase in the volume of intercellular spaces, crispness and crunchiness of roasted hazelnuts were increased.     

Real-time PCR multiplex method for the quantification of Roundup Ready soybean in raw material and processed food

This paper describes a quantitative real-time multiplex PCR method optimised for the ABI PRISM^® 7700 Sequence Detection System (SDS) and TaqMan^® chemistry for Roundup Ready^® Soybean (RRS) in raw material and processed food. This method has the advantage of performing the amplification of the target taxon lectin gene and the genetically modified (GM) target sequence in the same test tube. The quantification is based on a calibration curve obtained with the DNA extracted from Certified Reference Material standards (CRM IRMM-410: R) in the range 0.1–5% RRS. The method was validated in-house by using CRMs and the applicability was verified on three mixtures of soybean flour at 1, 5, 10% of RRS respectively and on prepared baked products (biscuits and plum cakes). The statistical parameters of the method were found to be satisfactory both for soybean flour and baked products. In the process the absolute LOD and LOQ was 7.1 and 35.5 copy number respectively; the relative LOD and LOQ was 0.03 and 0.01% of RRS respectively.     

A novel real-time polymerase chain reaction method for the detection of macadamia nuts in food

A real-time PCR-based method for the detection of macadamia nuts (fruits of Macadamia integrifolia or M. tetraphylla or their hybrids) in food products is described. The method consists of DNA isolation by chaotropic solid phase extraction and subsequent PCR with macadamia-specific primers and a TaqMan fluorescent probe. The primers and the probe were targeted to the gene encoding for vicilin precursor. The method was positive for M. integrifolia and M. tetraphylla and negative for 16 other plant species used in food industry, including peanuts, walnuts, hazelnuts, almonds, pistachio nuts, cashew nuts, Brazil nuts, and chestnuts. The DNA-based detection limit of the method was 1.45 pg. Using a series of model samples with defined macadamia nut contents, a practical detection limit of 0.02% (w/w) macadamia nuts was determined. Practical applicability of the PCR method was tested by the analysis of 14 confectionery samples. For all of the samples, results conforming to the labeling were obtained. The presented PCR method is useful for relatively fast, highly selective, and moderately sensitive detection of macadamia nuts in food samples.     

Fast aroma profiling to detect invert sugar adulteration with zNose™

Rapid aroma profiling of food products is a potential technique for at‐line food quality evaluation. In this work the potential of zNose^?, a surface acoustic wave‐based sensor, was tested for honey quality assessment. Buckwheat honey was purposely adulterated with different levels of beet and cane invert sugar, and its aroma profile was measured after different periods of headspace equilibration. PCA using the relative peak areas as well as the full zNose^? spectra resulted in a clear separation between honey, and beet and cane invert sugar adulterants in the mixtures. PLS models were developed for quantitative estimation of adulterants using the entire spectra as well as the relative peak areas. Better predictions were obtained with the PLS models based on spectra than with those based on relative peak areas. A correlation of validation of 0.98 was obtained between predicted and measured percentage of adulteration. This model was also successfully validated with an external set of honey mixtures, resulting in an average deviation of 3% adulteration between the predicted and reference values. Copyright © 2004 Society of Chemical Industry     

Visible micro-Raman spectroscopy for determining glucose content in beverage industry

The potential of Raman spectroscopy with excitation in the visible as a tool for quantitative determination of single components in food industry products was investigated by focusing the attention on glucose content in commercial sport drinks. At this aim, micro-Raman spectra in the 600–1600 cm⁻¹ wavenumber shift region of four sport drinks were recorded, showing well defined and separated vibrational fingerprints of the various contained sugars (glucose, fructose and sucrose). By profiting of the spectral separation of some peculiar peaks, glucose content was quantified by using a multivariate statistical analysis based on the interval Partial Least Square (iPLS) approach. The iPLS model needed for data analysis procedure was built by using glucose aqueous solutions at known sugar concentrations as calibration data. This model was then applied to sport drink spectra and gave predicted glucose concentrations in good agreement with the values obtained by using a biochemical assay. These results represent a significant step towards the development of a fast and simple method for the on-line glucose quantification in products of food and beverage industry.     

Determination of trichothecenes in cereals and cereal-based products by liquid chromatography-tandem mass spectrometry

A sensitive, accurate and precise method for the simultaneous determination of nivalenol (NIV), deoxynivalenol (DON), T-2 toxin (T-2) and HT-2 toxin (HT-2) in different food matrices, including wheat, maize, barley, cereal-based infant foods, snacks, biscuits and wafers, has been developed. The method, using liquid chromatography coupled with atmospheric pressure chemical ionization triple quadrupole mass spectrometry (LC-APCI-MS/MS), allowed unambiguous identification of the selected trichothecenes at low µg per kg levels in such complex food matrices. A clean-up procedure, based on reversed phase SPE Oasis® HLB columns, was used, allowing good recoveries for all studied trichothecenes. In particular, NIV recoveries significantly improved compared to those obtained by using Mycosep® #227 columns for clean-up of the extracts. Limits of detection in the various investigated matrices ranged 2.5-4.0 µg kg^-1 for NIV, 2.8-5.3 µg kg^-1 for DON, 0.4-1.7 µg kg^-1 for HT-2 and 0.4-1.0 µg kg^-1 for T-2. Mean recovery values, obtained from cereals and cereal products spiked with NIV, DON, HT-2 and T-2 toxins at levels from 10 to 1000 µg kg^-1, ranged from 72 to 110% with mean relative standard deviation lower than 10%. A systematic investigation of matrix effects in different cereals and cereal products was also carried out by statistically comparing the slopes of standard calibration curve with matrix-matched calibration curve for each of the four toxins and the eight matrices tested. For seven of the eight matrices tested, statistically significant matrix effects were observed, indicating that, for accurate quantitative analysis, matrix-matched calibration was necessary. The method was applied to the analysis of 57 samples of ground wheat originated from South Italy and nine cereal food samples collected from retail markets.     

Fast detection of cyclopiazonic acid in cheese using Fourier transform mid-infrared ATR spectroscopy

A simple and rapid Fourier transform mid-infrared spectroscopic method with attenuated total reflection was developed for the detection of cyclopiazonic acid in ewe's cheese samples. A partial least-squares calibration model for the prediction of cyclopiazonic acid content in ewe medium-ripened cheese, based on spectra data, revealed to be the best approach. The PLS model was tested by cross-validation in order to minimize standard error of the model and the relevant RMSECV (root of mean-squared error in cross-validation) was calculated to be 0.05 μg/g. In parallel experiments, cyclopiazonic acid content was estimated using the developed SPME-HPLC/UV method and different cheese samples were analysed using both techniques. The method appears to be useful for a qualitative and semi-quantitative screening of a large number of cheese samples, important in food contaminants monitoring. Since no sample pretreatment is required at all, the analysis times are dramatically shortened in comparison with any chromatographic procedure.