Feasibility of conventional and Roundup Ready® soybeans discrimination by different near infrared reflectance technologies

Identification and proper labelling of genetically modified organisms is required and increasingly demanded by legislation and consumers worldwide. In this study, the feasibility of three near infrared reflectance technologies (a chemical imaging unit, a commercial diode array instrument, and a light tube non-commercial instrument) were compared for discriminating Roundup Ready® and not genetically modified soybean seeds. Over 200 seeds of each class (Roundup Ready® and conventional) were used. Principal Component Analysis with Artificial Neural Networks (PCA–ANN) and Locally Weighted Principal Component Regression (LW-PCR) were used for creating the discrimination models. Discrimination accuracies when new tested seeds belonged to samples included in the training sets achieved accuracies over 90% of correctly classified seeds for LW-PCR models. The light tube performed the best, while the imaging unit showed the worse accuracies overall. Models validated with new seeds from samples not included in the training set had accuracies of 72–79%.     

枇杷蜂蜜中饴糖的近红外光谱检测

实验通过对纯枇杷蜂蜜及主动掺入1%、2%……30%饴糖的假枇杷蜂蜜进行近红外光谱扫描,采用TQAnalysisv6对数据进行预处理,建立饴糖含量的定性及偏最小二乘法和主成分回归法定量分析模型,并将模型应用于蜂蜜样品的分析预测。结果显示,采用原始光谱或一阶微分处理建立的判别分析模型均能够较好地区分掺饴糖蜂蜜与纯蜂蜜。根据PLS算法、PCR算法建立的定量模型相关系数分别为0.99771、0.98654,用于预测的蜂蜜样品实际值与预测值之间的决定系数分别为0.992、0.974。由此可见,用近红外光谱技术鉴别蜂蜜中是否添加饴糖是可行的,在实际操作中可以采用近红外光谱法快速定性判别蜂蜜中是否含有饴糖,也可根据化学计量法确定饴糖的含量,为蜂蜜打假提供依据。     

Principles for the risk assessment of genetically modified microorganisms and their food products in the European Union

Genetically modified microorganisms (GMMs) are involved in the production of a variety of food and feed. The release and consumption of these products can raise questions about health and environmental safety. Therefore, the European Union has different legislative instruments in place in order to ensure the safety of such products. A key requirement is to conduct a scientific risk assessment as a prerequisite for the product to be placed on the market. This risk assessment is performed by the European Food Safety Authority (EFSA), through its Scientific Panels. The EFSA Panel on Genetically Modified Organisms has published complete and comprehensive guidance for the risk assessment of GMMs and their products for food and/or feed use, in which the strategy and the criteria to conduct the assessment are explained, as well as the scientific data to be provided in applications for regulated products. This Guidance follows the main risk assessment principles developed by various international organisations ( and ). The assessment considers two aspects: the characterisation of the GMM and the possible effects of its modification with respect to safety, and the safety of the product itself. Due to the existing diversity of GMMs and their products, a categorisation is recommended to optimise the assessment and to determine the extent of the required data. The assessment starts with a comprehensive characterisation of the GMM, covering the recipient/parental organism, the donor(s) of the genetic material, the genetic modification, and the final GMM and its phenotype. Evaluation of the composition, potential toxicity and/or allergenicity, nutritional value and environmental impact of the product constitute further cornerstones of the process. The outcome of the assessment is reflected in a scientific opinion which indicates whether the product raises any safety issues. This opinion is taken into account by the different European regulatory authorities prior to a decision regarding authorisation to commercialise the product.     

近红外光谱分析技术在动物源性食品检测中的应用进展

近年来动物源性食品的消费量日益增大,关于动物源性食品的质量安全也受到人们的高度重视。近红外光谱(NIR)分析技术具有分析速度快、非破坏性、所需样品量小、多组分同时测定,且可对生产过程进行实时监控等优点。本文对NIR分析技术进行了简介,并列举了常用的光谱预处理方法;综述了该技术在动物源性食品检测中的研究进展,包括品质评价和安全评价;并对该技术在动物源性食品检测中的发展趋势进行了阐述。表明NIR分析技术适合评价动物源性食品的品质和安全。      

Non-destructive prediction of hardening pericarp disorder in intact mangosteen by near infrared transmittance spectroscopy

A non-destructive technique to predict a hardening pericarp disorder in intact mangosteen is proposed by using near infrared (NIR) transmittance spectroscopy in the wavelength range of 660-960 nm. The study found that the spectral features of normal pericarp mangosteen and hardening pericarp mangosteen were different. The averaged spectra and individual spectra of hardening pericarp mangosteen from a calibration set (N = 560) were used to develop classification models, using partial least squares discriminant analysis (PLS-DA). A model based on individual spectra obtained better classification. The overall accuracy of classification for a prediction set (N = 358) was 91%. Out of 179 samples of normal pericarp fruits, 167 were identified correctly, while 159 samples out of 179 samples with hard pericarp were predicted correctly. The results showed that NIR transmittance spectroscopy can be used to predict hard pericarp disorder in intact mangosteen fruit accurately.     

近红外快速测定饲料原料淀粉含量

利用近红外光谱技术(NIR)测定玉米、豆粕、DDGS等10种饲料原料淀粉含量。对于玉米、小麦、大麦、高粱四种原粮类样品,分别以不经任何处理和粉碎0.5 mm后进行建模比较,结果显示粉碎后效果有明显提升。探索性的尝试了4种原粮类样品建立通用模型,粉碎0.5 mm前后建模的R、RMSECV、RPD分别为0.983、0.861、5.48和0.988、0.738、6.48,优于单独建模,说明建立通用模型是可行的,特别是在建模样品量较少的情况下,可以起到较好的作用。     

2011年深圳转基因大豆及其制品的市场占有率和标识情况调查

目的 了解深圳市场转基因大豆及其制品的市场占有率和标识情况,为政府监管转基因大豆提供科学依据.方法 按照监测计划,定期在深圳市场随机抽取大豆及其制品,采用实时荧光PCR方法对其进行定性和定量检测,评估深圳市场转基因大豆的市场占有率和标识情况,并与2006年的监测结果进行比较和分析.结果 2011年共监测样品106份,检出2份转基因阳性样品,市场占有率为1.89％;两份阳性样品中转基因大豆的含量分别为0.93％和0.51％,定量检出限为0.1％.所有检出转基因阳性样品均没有转基因标识;与2006年结果比较,转基因大豆及其制品的市场占有率以及标识情况差异均无统计学意义.结论 目前深圳市场转基因大豆及其制品(食用油脂除外)的市场占有率还很低,并且5年来未发现明显上升;转基因产品标识的管理还有待加强,政府应该加大这方面的执法力度.     

Authentication of pure camellia oil by using near infrared spectroscopy and pattern recognition techniques

Abstract: Total of 4 pattern recognition methods for the authentication of pure camellia oil applying near infrared (NIR) spectroscopy were evaluated in this study. Total of 115 samples were collected and their authenticities were confirmed by gas chromatography (GC) in according to China Natl. Standard (GB). A preliminary study of NIR spectral data was analyzed by unsupervised methods including principal component analysis (PCA) and hierarchical cluster analysis (HCA). Total of 2 supervised classification techniques based on discriminant analysis (DA) and radical basis function neural network (RBFNN) were utilized to build calibration model and predict unknown samples. In the wavenumber range of 6000 to 5750 cm^?1, correct classification rate of both supervised and unsupervised solutions all can reach 98.3% when smoothing, first derivative, and autoscaling were used. The good performance showed that NIR spectroscopy with multivariate calibration models could be successfully used as a rapid, simple, and nondestructive method to discriminate pure camellia oil.     

近红外定量分析青烟叶中K、Ca、Mg含量的研究

本文利用近红外光谱仪(NIR)结合偏最小二乘法,用漫反射方法测定了青烟叶中K、Ca、Mg三种化学成分,试验证明,NIR可以用于测试青烟叶中这三种化学成分的含量。      

蜂蜜中羟甲基糠醛的近红外光谱快速测定方法

为实现蜂蜜中羟甲基糠醛的快速测定,利用近红外（NIR）光谱分析技术结合偏最小二乘法（PLS）建立了蜂蜜中羟甲基糠醛的定量分析模型,并进行了预测。通过光谱扫描,波数范围为7706⁴009cm-1、一阶导数、norris derivative平滑及10个因子数进行光谱预处理,偏最小二乘法（PLS）,交叉验证。结果表明,羟甲基糠醛定量模型的交叉验证相关系数（Rcv2）=0.99620、交叉验证均方差（RMSECV）=2.40;预测相关系数（Rp2）=0.99874、预测均方差（RMSEP）=2.02;预测值与测定值之间无显著差异,该方法适用于蜂蜜中羟甲基糠醛的快速测定。      

三倍体毛白杨木素和苯醇抽提物的近红外光谱法测定

选取了有代表性的78个三倍体毛白杨样品,先用国家标准方法测定样品的Klason木素和苯醇抽提物含量,然后用近红外光谱仪进行快速检测。所得扫描光谱进行＂二阶导数、减去一条直线＂预处理后,运用偏最小二乘法PLS、完全交互验证以及外部验证方式建立相应预测模型。木素校正模型的相关系数达到了0.8883,标准误差SEC=0.612,预测模型的相关因子达到0.8634,均方根误差RMSEP为0.944。苯醇抽提物校正模型的相关系数达到了R=0.9007,校正标准误差SEC=0.39,预测模型的相关因子达R=0.8857,均方根误差RMSEP为0.603。结果表明,用近红外光谱技术可以实现对三倍体毛白杨木素和苯醇抽提物含量的快速分析。     

Determination of fermentative volatile compounds in aged red wines by near infrared spectroscopy

The purpose of this work was to study the possibility of determination of fermentative volatile compounds in aged red wines using NIR spectroscopy. To achieve this, 240 wines belonging to different geographic zones and elaborated with one or two varieties were analyzed. The volatile compounds were quantified by SBSE-GC–MS. Spectra obtained by NIR were co-related with these values using partial least square (PLS) regression. Calibration and validation statistics showed the quality of the model, after all when is done separately for each of the four geographic zones, and in the case of wines elaborated with two varieties. Consequently, near infrared spectroscopy can be used as an easy and rapid tool to determine fermentative volatile compounds in aged red wines.     

Comparison of visible and near infrared reflectance spectroscopy to discriminate between pasture-fed and concentrate-fed lamb carcasses

We compared visible and near infrared spectroscopy to distinguish pasture-fed (P) from stall concentrate-fed (S) lamb carcasses. A total of 120 P and 139 S lambs were used. The reflectance spectrum of perirenal fat was measured at wavelengths between 400 and 700 nm using a portable spectrophotometer, and at wavelengths between 400 and 2500 nm using a laboratory monochromator NIRSystem. In method W_450–510, the reflectance data were used at wavelengths between 450 and 510 nm. In methods W_400–700 and W_400–2500, a multivariate analysis was performed over the full set of reflectance data, at wavelengths in the range 400–700 nm and 400–2500 nm, respectively. The proportion of correctly classified P lambs was 89.1%, 90.8% and 97.5% for W_450–510, W_400–700 and W_400–2500, W_400–2500 performing best. The proportion of correctly classified S lambs was not significantly different between methods (98.6%, 98.6% and 97.8% for W_450–510, W_400–700 and W_400–2500, respectively).     

The determination of protein,fat and moisture in bread by near infrared reflectance spectroscopy

Near infrared (n.i.r.) reflectance spectroscopy has been employed for the determination of protein, fat and moisture in sliced white bread. N.i.r. reflectance at six wavelengths was measured using circular samples from each of six alternate slices taken from one half of each of 30 loaves of different composition. The six readings for each loaf at each wavelength were averaged and used to produce calibrations which, on prediction of the compositions of a further 30 loaves sampled in the same way, gave rise to standard deviations of differences between n.i.r. and standard procedures of 0.20% for protein, 0.18% for fat and 0.51% for moisture. Calibrations derived from the other halves of the loaves, which had been air-dried and ground to a powder, resulted in similar standard deviation of differences for protein and fat.     

Theory and application of near infrared spectroscopy in assessment of fruit quality: a review

Fruits provide nutrients for human body and are able to prevent sorts of non-communicable diseases. The fruit quality test is an area that both technology and market section concern about. Near infrared spectroscopy (NIR) is a rapid, precise, and non-destructive technique which can be well utilized in determination of fruit quality. This review paper summarizes the theory of NIR analysis, and the fundamental structure of instruments based on NIR for fruit quality assessment. Chemometrics for NIR spectroscopy involving analysis methods of data pre-processing, calibration, model transfer and evaluation, is also included. In recent 11 years, significant progresses were achieved in fruit quality assessment via NIR spectroscopy, which is the main focus in this review. Furthermore, urgent problems in this research field are discussed, expecting to be solved in the near future.     

Using near infrared spectroscopy for the determination of total solids and protein content in cheese curd

In-line or on-line monitoring requires fast and reliable methods for determining composition or processing variables. A near infrared spectroscopic method for the determination of solids and protein content in cheese curd has been developed. Based on approximately 250 curd samples, calibration models were built using partial least squares regression. The calibration models resulted in coefficients of determination of R² = 0.994 for total solids and R² = 0.985 for protein content for unhomogenized curd, which improved only slightly after subjecting the curd to homogenization. As confirmed by results that were obtained from a validation set, this suggests that near infrared spectroscopy is a potential and powerful method for the rapid monitoring of curd composition.     

近红外光谱技术在南极磷虾粉水分、脂肪和蛋白质含量快速检测中的应用

利用傅里叶近红外光谱分析技术,以磷虾粉样品的实测值与模型预测值为基础,研究了采用最小二乘法建立磷虾粉原始样品与磷虾粉混合样品中水分、脂肪和蛋白含量近红外定标模型的可行性和准确性.结果表明,磷虾粉近红外图谱最佳预处理方式为:标准正态变换预处理+一阶导数+Norris导数滤波;以磷虾粉混合样品构建的近红外模型较磷虾粉原始样...     

近红外光谱结合偏最小二乘法快速测定糖果中水分含量

采用近红外光谱(NIR)结合偏最小二乘法(PLS)建立了一种糖果中水分含量快速准确的测定方法。在12500~3600 cm^-1光谱范围内采集116批糖果的近红外漫反射光谱,并用减压干燥失重法测定其水分含量。通过比较不同参数对建模的影响,发现用多元散射校正法进行预处理,在11682.2~9826.1、8939.0~6267.9、5378.8~4487.8 cm^-1光谱范围内,主成分数为15时,应用PLS方法建立的糖果水分的定量分析模型效果最佳。所建立模型的相关系数为0.9716,校正均方根误差和验证均方根误差分别为0.97%和1.03%。该方法结果准确可靠、操作简便,可用于糖果中水分含量的快速检测。