共查询到20条相似文献，搜索用时 77 毫秒
1.
Seafood processing often removes morphological properties of seafood species that enable the consumer to distinguish one type of organism from another. For this reason, species substitution is the most common form of economic adulteration in the seafood industry. Visible and near-infrared spectroscopy (Vis/NIR) has been used to detect and quantify species authenticity and adulteration in crabmeat samples. Atlantic blue crabmeat was adulterated with blue swimmer crabmeat in 10% increments. Water absorption bands dominated the main features in the crabmeat spectra, with a decrease in sample absorbance with increasing adulteration percentage. Several data pretreatments, i.e., moving average, combing, first and second derivatives, and multiplicative scatter correction, in addition to the raw data, were investigated for prediction and quantitative data analysis using partial least-squares. In addition, quantitative analysis was done using the full spectrum and a sequential approach in which 50 wavelengths were added sequentially to determine a new model and find an optimal solution. The results suggest that Vis/NIR spectroscopy is a suitable technology that can be applied to detect and quantify species authenticity and adulteration in crabmeat. 相似文献
2.
利用近红外光谱技术检测掺假豆浆 总被引：3，自引：1，他引：2
为了对豆乳内在营养指标及掺假豆乳进行快速检测,试验运用近红外光谱技术,利用偏最小二乘法进行回归分析,分别建立83个真伪豆浆样品的蛋白质和总固形物含量定标模型,并对模型的预测性能进行分析。结果表明:选取主成分数为12和14,蛋白质和总固形物含量的近红外光谱预测值与化学实测值之间的相关系数R分别为0.9756和0.9489,校正均方根误差分别为0.186和0.175,预测集样品的预测值和实测值之间的残差值均较小、接近零,残差之和分别为-0.074和-1.191,说明建立的定标模型可以准确预测豆浆中蛋白质和总固形物含量,且预测性能较好;通过对预测集样品的预测值与豆浆行业标准规定值相比较,确定预测集样品中掺假豆浆的正确判别率为100%,说明建立的蛋白质和总固形物含量定标模型可以应用于掺假豆浆的判别检测,且判别结果准确率高。本试验表明利用近红外光谱技术可实现对豆浆主要品质指标的快速无损检测,也可准确进行真伪豆浆的快速判别,本检测方法可为豆乳行业健康持续发展提供一定的技术支撑。 相似文献
3.
Fourier transform infrared (FTIR) spectroscopy and attenuated total reflection (ATR) sampling have been used to detect adulteration of honey samples. The sample set comprised 320 spectra of authentic (n = 99) and adulterated (n = 221) honeys. Adulterants used were solutions containing both d-fructose and d-glucose prepared in the following respective weight ratios: 0.7:1.0, 1.2:1.0 (typical of honey composition), and 2.3:1.0. Each adulterant solution was added to individual honeys at levels of 7, 14, and 21% w/w. Spectral data were compressed and analyzed using k-nearest neighbors (kNN) and partial least squares (PLS) regression techniques. A number of data pretreatments were explored. Best classification models were achieved with PLS regression on first derivative spectra giving an overall correct classification rate of 93%, with 99% of samples adulterated at levels of 14% w/w or greater correctly identified. This method shows promise as a rapid screening technique for detection of this type of honey adulteration. 相似文献
4.
羊肉纯度电子舌快速检测方法 总被引：3，自引：1，他引：2
为实现掺假羊肉的快速、客观评价,利用电子舌对混入不同比例鸡肉的掺假羊肉糜进行检测及定性和定量分析。3种浸提溶液分别浸提,样品量均对电子舌传感器的响应影响极显著;以数据点重复性和聚类效果为依据,采用主成分分析方法确定了电子舌检测羊肉糜样品的较佳条件为0.1 mol/L KCl溶液浸提15 g肉糜样品。在此较佳条件下,对混入不同比例鸡肉的掺假羊肉进行检测,结果表明：采用主成分分析和典则判别分析,前2个主成分累积贡献率均超过80%,电子舌均能很好地区分混入不同比例鸡肉的羊肉糜样品;采用多元线性回归分析和偏最小二乘回归分析建立的定量预测模型能有效预测混入的鸡肉比例（R2>0.99,RMSE<3%）。试验表明：电子舌在羊肉掺入鸡肉的鉴别中具有可行性,研究结果可为羊肉掺假鉴别提供参考。 相似文献
5.
Detection of hazelnut oil adulteration using FT-IR spectroscopy 总被引：1，自引：0，他引：1
Fourier transform infrared spectroscopy (FT-IR) was used to detect the adulteration of hazelnut oil with different types of oils and to detect the adulteration of extra-virgin olive oil with hazelnut oil. Spectra of hazelnut oil, seven other types of oils, extra-virgin olive oil, and the adulterated oils were collected with a FT-IR equipped with a ZnSe-ATR accessory and a MCTA detector. Discriminant analysis and partial least-squares analysis were used to analyze the data. Classification of hazelnut oil, olive oil, and the other types of oils was achieved successfully with FT-IR. The detection level for sunflower oil adulteration of hazelnut oil was 2%, and the correlation coefficient for the PLS model was 0.99. Adulteration of virgin olive oil with hazelnut oil could be detected only at levels of 25% and higher. 相似文献
6.
Selamawit Tekle smund Bj&#x;rnstad Helge Skinnes Yanhong Dong Vegard H. Segtnan 《Cereal Chemistry》2013,90(3):181-185
The potential of VIS‐NIR spectroscopy as a rapid screening method for resistance of Fusarium‐inoculated oats to replace the costly chemical measurements of deoxynivalenol (DON) was investigated. Partial least squares (PLS) regression was conducted on second‐derivative spectra (400–2,350 nm) of 166 DON‐contaminated samples (0.05–28.1 ppm, mean = 13.06 ppm) with separate calibration and test set samples. The calibration set had 111 samples, and the test set had 55 samples. The best model developed had three PLS components and a root mean square error of prediction (RMSEP) of 3.16 ppm. The residual predictive deviation (RPD) value of the prediction model was 2.63, an acceptable value for the purpose of rough screening. Visual inspection and the VIS spectra of the samples revealed that high‐DON samples tended to be darker in color and coarser in texture compared with low‐DON samples. The second‐derivative spectra showed that low‐DON samples tended to have more water and fat content than high‐DON samples. With an RMSEP value of 3.16 and RPD of value of 2.63, it seems possible to use VIS‐NIR spectroscopy to semiquantitatively estimate DON content of oats and discard the worst genotypes during the early stages of screening. 相似文献
7.
Naya Y Horiuchi M Ishiguro N Shinagawa M 《Journal of agricultural and food chemistry》2003,51(2):345-349
Bacterial tests were used to assess bacterial contamination of game meat from Japanese wild boars. The bacterial contamination of wild boar meat was less than that of domestic pork, as determined by aerobic plate counts (APC) and coliform counts. None of the meat examined in this study was contaminated by Salmonella or E. coli O-157. To detect adulteration by domestic pig meat or European wild boar meat, 46 samples of game meat sold as Japanese wild boar were examined genetically. A total of 17 samples showed genetic haplotypes of European and Asian domestic pigs in the D-loop of mitochondrial DNA (mtDNA), and 16 samples showed nuclear glucosephosphate isomerase-processed pseudogene (GPIP) genotypes of European domestic pigs. The European GPIP genotypes of these samples were confirmed by PCR-RFLP analysis. These results indicate that some game meat sold as Japanese wild boar is adulterated by cross-breeding between pigs and wild boars or by contamination with meat from domestic pigs or European wild boars. 相似文献
8.
Visible and near infrared (VIS/NIR) transmission spectroscopy and chemometric methods were utilized for the fast determination of soluble solids content (SSC) and pH of cola beverage. A total of 180 samples were used for the calibration set, whereas 60 samples were used for the validation set. Some preprocessing methods were applied before developing the calibration models. Several PLS factors, extracted by partial least squares (PLS) analysis, were used as the inputs of least squares-support vector machine (LS-SVM) model according to their accumulative reliabilities. The correlation coefficient (r), root mean square error of prediction (rmsEP), bias, and RPD were 0.959, 1.136, -0.185, and 3.5 for SSC, whereas 0.973, 0.053, 0.017, and 4.1 for pH, respectively. An excellent prediction precision was achieved by LS-SVM compared with PLS. The results indicated that VIS/NIR spectroscopy combined with LS-SVM could be applied as a rapid and alternative way for the fast determination of SSC and pH of cola beverage. 相似文献
9.
基于近红外光谱技术的蜂蜜掺假识别 总被引：7，自引：1，他引：6
为了实现蜂蜜掺假的快速识别,应用近红外光谱结合模式识别方法对蜂蜜掺假现象进行了识别分析。该研究收集了中国不同品种、不同地域的典型天然蜂蜜样品,根据目前市场上常见的蜂蜜掺假手段,掺假物质及相对含量情况配制了掺假蜂蜜样品,利用傅立叶近红外光谱仪采集其透反射近红外光谱,分别采用偏最小二乘判别分析（PLS-DA）,独立软模式法（SIMCA）,误差反向传播神经网络（BP-ANN）和最小二乘支持向量机（LS-SVM）等模式识别方法,进行蜂蜜掺假识别研究。研究结果表明：利用这4种方法在蜂蜜中掺入果葡糖浆和果葡糖水的情况下均能很好地识别出掺假蜂蜜样品,其中对于掺入果葡糖浆的掺假情况,校正集的正确判别率均达到95%以上,验证集的正确判别率均达到87%以上,对于掺入果葡糖水的掺假蜂蜜校正集的正确判别率均达到93%以上,验证集的正确判别率均达到84%以上。通过比较4种不同的识别算法,发现采用LS-SVM时,对两种掺假情况下校正集和验证集的正确判别率均达到了100%,表明基于近红外光谱的蜂蜜掺假快速准确识别是可行的。 相似文献
10.
One hundred and thirty-eight oil samples have been analyzed by visible and near-infrared transflectance spectroscopy. These comprised 46 pure extra virgin olive oils and the same oils adulterated with 1% (w/w) and 5% (w/w) sunflower oil. A number of multivariate mathematical approaches were investigated to detect and quantify the sunflower oil adulterant. These included hierarchical cluster analysis, soft independent modeling of class analogy (SIMCA method), and partial least squares regression (PLS). A number of wavelength ranges and data pretreatments were explored. The accuracy of these mathematical models was compared, and the most successful models were identified. Complete classification accuracy was achieved using 1st derivative spectral data in the 400-2498 nm range. Prediction of adulterant content was possible with a standard error equal to 0.8% using 1st derivative data between 1100 and 2498 nm. Spectral features and chemical literature were studied to isolate the structural basis for these models. 相似文献
11.
Fourier transform infrared spectroscopy (FT-IR) methods and common chemometric techniques [including discriminant analysis (DA), Mahalanobis distances, and Cooman plots] were used to classify various types of dietary supplement oils (DSO) and less expensive, common food oils. Rapid FT-IR methods were then developed to detect adulteration of DSO with select common food oils. Spectra of 14 types of DSO and 5 types of common food oils were collected with an FT-IR equipped with a ZnSe attenuated total reflectance cell and a mercury cadmium telluride A detector. Classification of DSO and some common food oils was achieved successfully using FT-IR and chemometrics. Select DSO were adulterated (2-20% v/v) with the common food oils that had the closest Mahalanobis distance to them in a Cooman plot based on the DA analysis, and data were also analyzed using a partial least-squares (PLS) method. The detection limit for the adulteration of DSO was 2% v/v. Standard curves to determine the adulterant concentration in DSO were also obtained using PLS with correlation coefficients of >0.9. The approach of using FT-IR in combination with chemometric analyses was successful in classifying oils and detecting adulteration of DSO. 相似文献
12.
电子鼻在牦牛肉和牛肉猪肉识别中的应用 总被引：7，自引：0，他引：7
为了探索电子鼻对肉类掺假识别的可行性,利用电子鼻对牦牛肉、牛肉和猪肉样品进行了分析。通过对所获得的数据进行主成分分析（principal component analysis,PCA）、判别因子分析（discriminant factor analysis,DFA）和偏最小二乘回归分析（partial least-squares analysis,PLS）。结果表明：几种肉类在电子鼻传感器上有不同的特征性响应图谱,电子鼻能够有效识别猪、牛肉;同时电子鼻能够识别不同部位的牦牛肉和普通牛肉;但不能识别不同部位的猪肉。在牛肉馅中掺入不同比例的猪肉馅时,电子鼻也能进行识别。采用偏最小二乘回归分析对数据进行处理,电子鼻响应信号和猪肉馅掺入比例之间有很好的相关性（决定系数R2为0.9762）,PLS模型预测误差在1.27%～7.00%之间。试验证明电子鼻可用于肉类的识别。 相似文献
13.
二维相关光谱结合偏最小二乘法测定牛奶中的掺杂尿素 总被引：9，自引：5，他引：4
为了检验牛奶中是否掺杂尿素并将其量化测定,配置含有尿素质量浓度范围为1～20g/L之间40个牛奶样品,以掺杂物尿素浓度为外扰,分别研究了掺杂尿素牛奶的二维相关(近红外-近红外,中红外-中红外,近红外-中红外)光谱特性,在此基础上,分别选择随浓度变化大的4200～4800cm-1和1400～1704cm-1为建模区间,采用偏最小二乘方法建立定量分析模型。研究结果表明:4200～4800cm-1建模分析效果优于1400～1704cm-1建模结果,其交叉验证均方根误差为0.266g/L,对未知样品集预测相关系数达到0.999,预测均方根误差为0.219g/L,这表明所建模型具有较好的预测效果。该方法无需样品处理,成本低,为快速判别牛奶是否掺杂提供了一种新的可能的方法。 相似文献
14.
为了探讨快速无损检测羊肉糜中狐狸肉掺假含量的可行性,该研究利用高光谱技术结合特征变量筛选方法开展了其定量检测研究。利用遗传算法、竞争性自适应重加权算法和二维相关光谱分析（Two-Dimensional Correlation Spectroscopy,2D-COS）3种方法分别对代表性样品全部846个波长进行特征波长筛选,得到207、34和14个特征波长;基于全部波长和特征波长建立羊肉糜中狐狸肉掺假含量的偏最小二乘回归（Partial Least Squares Regression,PLSR）和支持向量回归（Support Vector Regression,SVR）模型并进行比较。研究结果表明,基于全部波长和特征波长建立的SVR模型性能均优于PLSR模型。其中,利用2D-COS方法提取的14个特征波长建立的SVR模型（即2D-COS-SVR模型）性能最优,其预测集决定系数和均方根误差分别为0.928和3.00%,相对分析误差为4.85,表明高光谱结合2D-COS-SVR模型可以有效实现羊肉糜中狐狸肉掺假的定量检测。该研究结果为开发低成本肉类掺假检测系统提供技术支持和参考依据。 相似文献
15.
Alexandrakis D Downey G Scannell AG 《Journal of agricultural and food chemistry》2008,56(10):3431-3437
Near-infrared (NIR) transflectance spectra of Listeria innocua FH, Lactococcus lactis, Pseudomonas fluorescens, Pseudomonas mendocina, and Pseudomonas putida suspensions were collected and investigated for their potential use in the identification and classification of bacteria. Unmodified spectral data were transformed (first and second derivative) using the Savitzsky-Golay algorithm. Principal component analysis (PCA), partial least-squares discriminant analysis (PLS2-DA), and soft independent modeling of class analogy (SIMCA) were used in the analysis. Using either full cross-validation or separate calibration and prediction data sets, PLS2 regression classified the five bacterial suspensions with 100% accuracy at species level. At Pseudomonas genus level, PLS2 regression classified the three Pseudomonas species with 100% accuracy. In the case of SIMCA, prediction of an unknown sample set produced correct classification rates of 100% except for L. innocua FH (77%). At genus level, SIMCA produced correct classification rates of 96.7, 100, and 100% for P. fluorescens, P. mendocina, and P. putida, respectively. This successful investigation suggests that NIR spectroscopy can become a useful, rapid, and noninvasive tool for bacterial identification. 相似文献
16.
Detection of sugar adulterants in apple juice using fourier transform infrared spectroscopy and chemometrics 总被引：2，自引：0，他引：2
Fourier transform infrared spectroscopy and attenuated total reflection sampling have been used to detect adulteration of single strength apple juice samples. The sample set comprised 224 authentic apple juices and 480 adulterated samples. Adulterants used included partially inverted cane syrup (PICS), beet sucrose (BS), high fructose corn syrup (HFCS), and a synthetic solution of fructose, glucose, and sucrose (FGS). Adulteration was carried out on individual apple juice samples at levels of 10, 20, 30, and 40% w/w. Spectral data were compressed by principal component analysis and analyzed using k-nearest neighbors and partial least squares regression techniques. Prediction results for the best classification models achieved an overall (authentic plus adulterated) correct classification rate of 96.5, 93.9, 92.2, and 82.4% for PICS, BS, HFCS, and FGS adulterants, respectively. This method shows promise as a rapid screening technique for the detection of a broad range of potential adulterants in apple juice. 相似文献
17.
A collection of authentic artisanal Irish honeys (n = 580) and certain of these honeys adulterated by fully inverted beet syrup (n = 280), high-fructose corn syrup (n = 160), partial invert cane syrup (n = 120), dextrose syrup (n = 160), and beet sucrose (n = 120) was assembled. All samples were adjusted to 70 degrees Bx and scanned in the midinfrared region (800-4000 cm(-1)) by attenuated total reflectance sample accessory. By use of soft independent modeling of class analogy (SIMCA) and partial least-squares (PLS) classification, authentic honey and honey adulterated by beet sucrose, dextrose syrups, and partial invert corn syrup could be identified with correct classification rates of 96.2%, 97.5%, 95.8%, and 91.7%, respectively. This combination of spectroscopic technique and chemometric methods was not able to unambiguously detect adulteration by high-fructose corn syrup or fully inverted beet syrup. 相似文献
18.
《Communications in Soil Science and Plant Analysis》2012,43(15-16):1965-1974
Abstract The use of ultraviolet (UV), visible (VIS), near infrared reflectance (NIR), and midinfrared (MIR) spectroscopy techniques have been found to be successful in determining the concentration of several chemical properties in soils. The aim of this study was to evaluate the effect of two reference methods, namely Bray and Resins, on the VIS and NIR calibrations to predict phosphorus in soil samples. Two hundred (n=200) soil samples were taken in different years from different locations across Uruguay with different physical and chemical characteristics due to different soil types and management. Soil samples were analyzed by two reference methods (Bray and Resins) and scanned using an NIR spectrophotometer (NIRSystems 6500). Partial least square (PLS) calibration models between reference data and NIR data were developed using cross‐validation. The coefficient of determination in calibration (R2) and the root mean square of the cross validation (RMSECV) were 0.58 (RMSECV: 3.78 mg kg?1) and 0.61 (RMSECV: 2.01 mg kg?1) for phosphorus (P) analyzed by Bray and Resins methods, respectively, using the VIS and NIR regions. The R2 and RMSECV for P using the NIR region were 0.50 (RMSECV: 3.78 mg kg?1) and 0.58 (RMSECV: 2.01 mg kg?1). This study suggested that differences in accuracy and prediction depend on the method of reference used to develop an NIR calibration for the measurement of P in soil. 相似文献
19.
猕猴桃品质光谱无损检测技术研究进展 总被引：9，自引：2，他引：9
光谱无损检测技术正越来越广泛地应用在水果内部品质检测中。该文从猕猴桃光谱特性差异及光谱无损检测技术影响因素对比分析等方面出发，对目前光谱分析技术在猕猴桃品质检测中应用的研究现状进行综述。分析了猕猴桃与其它水果光谱吸收特性和散射特性的差异以及不同温度、硬度、成熟度、部位及生长期管理措施对猕猴桃光谱特性的差异。对猕猴桃样品采集、光谱检测及数据处理等方面的不同方法进行了对比分析。指出采用500～2500 nm的可见光及近红外光谱对不同产地、不同生长环境和管理条件、不同储藏期、不同成熟度猕猴桃的果肉颜色、硬度、干物质含量、可溶性固形物含量、含糖量以及水果密度等内部品质进行检测是可行的。数据处理和定标模型建立方面的研究正在从传统多元回归和数值优化方法到包括人工神经网络技术、遗传算法、小波分析和自组织理论等先进数据分析技术的非线性模式识别方向发展。今后研究重点应进一步提高定标模型预测可靠性、通用性和实用性，建议今后对不同猕猴桃品种及不同仪器之间定标模型的通用性、猕猴桃在运动条件下的光谱检测技术等方面进行研究。 相似文献
20.
为了预测鲜枣常温贮藏的保鲜期,确保鲜枣的品质要求及食用安全,应用近红外光谱建立了室温贮藏下鲜枣内部霉菌菌落总数变化的动力学模型。通过对几种数据预处理方法的比较及特征波数的选择,实现了鲜枣霉菌菌落总数变化的近红外模型的优选。结果表明:经过多元散射校正处理的鲜枣近红外光谱,应用多元线性回归方法建立的霉菌菌落总数模型预测能力较好,校正集相关系数为0.920,均方根误差为1.503,预测集相关系数为0.889,均方根误差为1.514。同时,将近红外光谱模型应用于霉菌菌落总数随贮藏时间变化的零级反应动力学模型中,得到模型的相关系数为0.981。根据近红外光谱吸光度值与贮藏时间的线性关系,当霉菌菌落总数初始值小于等于10cfu/g时,预测出鲜枣在室温下的保鲜期一般为8d。研究表明,结合动力学模型的近红外光谱技术可以作为一种无损、快速检测方法来检测鲜枣霉菌菌落总数变化。 相似文献