基于氨基酸组成的黄酒酒龄电子舌鉴别（英文）

该研究采用电子舌结合化学计量学方法用于黄酒酒龄的快速鉴别。为确证黄酒样品酒龄,采用氨基酸分析仪分析了1年陈、3年陈和5年陈黄酒中20种氨基酸,并利用主成分分析(principal component analysis,PCA)对氨基酸数据进行了分析。采用电位型电子舌采集了不同酒龄黄酒样品的味觉指纹信息,并采用判别分析(discriminant analysis,DA)方法结合味觉指纹信息建立黄酒酒龄快速鉴别模型。采用偏最小二乘法(partial least squares regression,PLSR)建立电子舌响应信号与氨基酸含量之间的相关关系。氨基酸数据结合PCA分析表明所有样品均标注正确;电子舌结合DA所建黄酒酒龄鉴别模型可将3个年份预测集样品正确区分;异亮氨酸(Ile)、天门冬氨酸(Asp)、酪氨酸(Tyr)和缬氨酸(Val)与电子舌相关性高,模型的相对分析误差(Residual predictive deviation,RPD)高于2。研究表明电位型电子舌结合判别分析是黄酒龄鉴别的稳健方法。     

电喷雾萃取及电离质谱法分析大豆水提液快速鉴别种子活力

为快速评价大豆种子活力,该文以人工加速老化后的大豆种子为原料,采用电喷雾萃取电离质谱（extractive electrospray ionization-mass spectrometry,EESI-MS）直接检测不同活力大豆种子水提液,获得其正离子模式下指纹图谱,结合主成分分析（principal component analysis,PCA）、聚类分析（cluster analysis,CA）和判别分析（discriminant analysis, DA）,建立鉴别大豆种子活力的方法。结果表明,在正离子模式下,电喷雾萃取电离质谱结合多变量分析方法可以有效鉴别不同活力大豆种子。主成分分析提取了前3个主成分因子,累计贡献率达到94.80%,聚类分析和判别分析的正确率都为100%,对外部验证样本进行判别分析,正确率为95%。电喷雾萃取电离质谱能快速鉴别不同活力大豆种子,为种子活力检测提供了一种快速、准确、高效的新方法。     

表面解吸常压化学电离质谱结合人工神经网络鉴别新陈莲子

为实现对新陈莲子的快速鉴别,该文采用自行研制的表面解吸常压化学电离质谱（DAPCI-MS）,在无需样品预处理的前提下,直接对新鲜和陈年莲子切面进行质谱检测,获得其化学指纹图谱,并通过主成分分析（PCA）和反向传输人工神经网络技术（BP-ANN）对所获指纹谱图信息进行分析,获得新鲜和陈年莲子的质谱信息特征。结果表明,在负离子模式下,DAPCI-MS结合化学计量学方法,实现了新鲜和陈年莲子的快速鉴别,其测试样本准确率分别为95.0%和91.7%;对不同年份莲子也能够有效地分类判别,2012、2011、2010和2009年莲子测试样本准确率分别为90%,85%,85%和90%。该方法具有分析速度快,信息提取准确,识别精度高等优点,为其他粮食谷物品质的鉴定提供参考。     

羊肉纯度电子舌快速检测方法

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。     

典型掺假蜂蜜的电子鼻信息变化特征及判别能力

为建立蜂蜜掺假快速检测方法,该文利用电子鼻并结合主成分分析（principal component analysis,PCA）数据处理方法研究了掺入10%、20%、30%、40%、50%、60%、70%油菜蜜和大米糖浆的掺假蜂蜜的电子鼻信息变化特征,并以掺假蜂蜜的电子鼻信息变化特征为指导,结合判别因子分析（linear discriminant analysis,LDA）模式识别算法研究了电子鼻对掺假蜂蜜的定性识别分析能力。结果表明,掺假蜂蜜的电子鼻信息呈现线性变化,并且电子鼻对掺假蜂蜜有较强的敏感力。LDA模式识别算法可以将纯蜂蜜样品与掺假蜂蜜样品很好的区分开,LDA掺假判别模型正确识别率为94.7%,该技术可以为蜂蜜掺假鉴别提供技术支撑。     

低场核磁共振结合化学模式识别方法判别休闲豆干品牌

为了探求一种能快速准确地判别豆干品牌的方法,本研究采用低场核磁共振仪,对休闲豆干样品进行测量获取横向弛豫数据,结合主成分分析法(principal component analysis,PCA)、偏最小二乘判别分析(partial least squares-discriiminate analysis,PLS-DA)和贝叶斯正则化误差反向传播人工神经网络(bayesian regularization back-propagation artificial neural network,BR-BP-ANN)等化学模式识别方法对试验数据进行模式识别分析。选用4个常见的休闲豆干品牌,每个品牌分别收集5个批次的样品。每个批次随机选择16小包作为测试样品,共获得320个样品。使用低场核磁共振仪对这些样品进行测量,然后采用模式识别方法进行品牌判别。试验结果表明:对预测集豆干样品采用PCA进行判别分析时,从三维投影图中难以对各品牌进行人眼识别;运用PLS-DA方法对训练集样品的品牌识别率为86.3%,预测集样品的识别率为81.3%;然而使用BR-BP-ANN方法对预测集样品进行判别预测,预测值与实际期望值高度吻合,判别正确率均为100%,能够很好的实现对豆干品牌的判别。因此,采用BR-BP-ANN方法能够快速而准确地对豆干品牌进行识别,可为休闲豆干的品牌判别提供较好的技术支持。     

独立分量分析融合小波能量阈值的电子鼻信号去漂移方法

电子鼻在长期使用过程中,由于受到传感器老化和温湿度波动等因素的影响,使得电子鼻信号存在着漂移现象,制约了电子鼻的准确检测。为了提高电子鼻鉴别多组分复杂食品时的长期稳健性,提出了一种独立分量分析（independent component analysis,ICA）融合小波能量阈值的去漂移信号方法。首先,运用ICA分解电子鼻信号以获得各个独立成分;其次,根据各个独立成分的小波能量值选择独立成分,以剔除漂移信号;最后,运用所选择的独立成分重构电子鼻信号。选用6种白酒样品和6种食醋样品进行电子鼻鉴别验证：在分别提取2类样品去漂移前后的电子鼻信号积分值（integral value,INV）特征后,分别对6种白酒样品和6种食醋样品进行了Fisher判别分析（fisher discriminant analysis,FDA）,FDA的鉴别正确率分别由去漂移前的34.3%（白酒样品）、75.7%（食醋样品）提升到去漂移后的100%（白酒样品）、99.7%（食醋样品）。Fisher判别分析结果表明,所提出的电子鼻信号去漂移方法是有效的。与其他独立分量分析方法相比,该方法不受先验信息的影响,更便于实际应用,研究结果不仅适用于白酒、食醋样品的鉴别,也为其他类型的样品鉴别提供参考。     

鸟氨酸氨甲酰基转移酶对黄酒贮藏过程中氨基甲酸乙酯的调控及品质变化研究

氨基甲酸乙酯（EC）是存在于黄酒发酵和贮藏过程中的一种潜在致癌物，其前体物为尿素和瓜氨酸。鸟氨酸氨甲酰基转移酶（OTC）是一种在乳酸菌精氨酸代谢过程中参与瓜氨酸降解的酶。前期研究发现OTC与EC呈负相关性，并构建了若干个OTC定点突变菌株。本研究在黄酒贮藏过程中添加突变/野生型OTC，分别分析了自然发酵组、不添加OTC酶的对照组、单位点突变组和双位点突变组中EC、主要代谢物、挥发性风味物质、氨基酸、电子舌等含量的变化规律，探究其对EC代谢和黄酒品质变化的影响。结果表明，与对照组相比，添加双位点突变的H140A-Q143W-OTC可显著降低EC浓度至20%；同时，黄酒的味觉、氨基酸和有机酸差异不显著，但对风味物质有所影响。本研究结果为黄酒企业进行EC阻遏提供了新思路。     

基于近红外光谱的烤烟烟叶自动分组方法

为了探索烤烟烟叶收购质量的无损检测技术,提出了一种基于近红外光谱技术快速鉴别烟叶分组（部位、颜色）的方法。分析了近红外光谱技术应用于完整烤烟烟叶质量评价的可行性,用不同波段范围、不同光谱预处理方法（多元散射校正MSC、标准正态变量变换SNV、微分光谱）和不同主成分因子数分别对烟叶部位和颜色分类结果的影响进行了对比分析,分别建立了烟叶部位和颜色的定性判别模型。结果表明：用判别分析（discrimant analysis,DA）方法在1?101～2?395?nm范围结合原始光谱建立的DA判别模型最优,该方法对烟叶部位、烟叶颜色的校正集分类正确率均达100%,预测集分类正确率分别达到98.57%和97.14%。说明所提出的方法具有很好的分组作用,近红外光谱技术为烤烟烟叶收购质量等级评价提供了一种新方法。     

基于近红外光谱技术的淡水鱼品种快速鉴别

为探索淡水鱼品种的快速鉴别方法,该文应用近红外光谱分析技术,结合化学计量学方法,对7种淡水鱼品种的判别分类进行了研究。采集了青、草、鲢、鳙、鲤、鲫、鲂等7种淡水鱼,共665个鱼肉样品的近红外光谱数据,经过多元散射校正(multiplicative scatter correction,MSC)、正交信号校正(orthogonal signal correction,OSC)、数据标准化(standardization,S)等20种方法预处理,在1 000~1 799 nm范围内分别采用偏最小二乘法(partial least square,PLS)、主成分分析(principal component analysis,PCA)和BP人工神经网络技术(back propagation artificial neural network,BP-ANN)、偏最小二乘法和BP人工神经网络技术对7种淡水鱼原始光谱数据进行了鉴别分析。结果表明,近红外光谱数据,结合主成分分析和BP人工神经网络技术建立的淡水鱼品种鉴别模型最优,模型的鉴别准确率达96.4%,对未知样本的鉴别准确率达95.5%。模型具有较好的鉴别能力,采用该方法能较为准确、快速地鉴别出淡水鱼的品种。     

Prediction of enological parameters and discrimination of rice wine age using least-squares support vector machines and near infrared spectroscopy

The use of least-squares support vector machines (LS-SVM) combined with near-infrared (NIR) spectra for prediction of enological parameters and discrimination of rice wine age is proposed. The scores of the first ten principal components (PCs) derived from PC analysis (PCA) and radial basis function (RBF) were used as input feature subset and kernel function of LS-SVM models, respectively. The optimal parameters, the relative weight of the regression error gamma and the kernel parameter sigma 2, were found from grid search and leave-one-out cross-validation. As compared to partial least-squares (PLS) regression, the performance of LS-SVM was slightly better, with higher determination coefficients for validation ( Rval2) and lower root-mean-square error of validation (RMSEP) for alcohol content, titratable acidity, and pH, respectively. When used to discriminate rice wine age, LS-SVM gave better results than discriminant analysis (DA). On the basis of the results, it was concluded that LS-SVM together with NIR spectroscopy was a reliable and accurate method for rice wine quality estimation.     

Analysis of sugars in Chinese rice wine by Fourier transform near-infrared spectroscopy with partial least-squares regression

The feasibility of rapid analysis for oligosaccharides, including isomaltose, isomaltotriose, maltose, and panose, in Chinese rice wine by Fourier transform near-infrared (FT-NIR) spectroscopy together with partial least-squares regression (PLSR) was studied in this work. Forty samples of five brewing years (1996, 1998, 2001, 2003, and 2005) were analyzed by NIR transmission spectroscopy with seven optical path lengths (0.5, 1, 1.5, 2, 2.5, 3, and 5 mm) between 800 and 2500 nm. Calibration models were established by PLSR with full cross-validation and using high-performance anion-exchange chromatography coupled with pulsed amperometric detection as a reference method. The optimal models were obtained through wavelength selection, in which the correlation coefficients of calibration (r(cal)) for the four sugars were 0.911, 0.938, 0.925, and 0.966, and the root-mean-square errors of calibrations were 0.157, 0.147, 0.358, and 0.355 g/L, respectively. The validation accuracy of the four models, with correlation coefficients of cross-validation (r(cv)) being 0.718, 0.793, 0.681, and 0.873, were not very satisfactory. This might be due to the low concentrations of the four sugars in Chinese rice wine and the influence of some components having structures similar to those of the four sugars. The results obtained in this study indicated that the NIR spectroscopy technique offers screening capability for isomaltose, isomaltotriose, maltose, and panose in Chinese rice wine. Further studies with a larger Chinese rice wine sample should be done to improve the specificity, prediction accuracy, and robustness of the models.     

Analysis of diacetyl in wine using solid-phase microextraction combined with gas chromatography-mass spectrometry

Analytical difficulties in the rapid and accurate determination of diacetyl (DA), an important flavor compound in wine, at low concentrations have been overcome by the use of solid-phase microextraction (SPME) with deuterated diacetyl-d(6) (d6-DA) as an internal standard followed by gas chromatography-mass spectrometry (GC-MS). The GC-MS analyses showed that the values of the ion response ratio of DA to d6-DA were consistent regardless of the conditions of SPME headspace and were not influenced by the presence of sulfur dioxide in wine. The quantitation value of DA was represented as the concentration of free plus bound with sulfur dioxide forms of DA. The detection limit of DA in wine was as low as 0.01 microg/mL with linearity through to 10 microg/mL.     

Rapid method for the discrimination of red wine cultivars based on mid-infrared spectroscopy of phenolic wine extracts

Mid-infrared spectroscopy and UV-vis spectroscopy combined with multivariate data analysis have been applied for the discrimination of Austrian red wines, including the cultivars Cabernet Sauvignon, Merlot, Pinot Noir, Blaufr?nkisch (Lemberger), St. Laurent, and Zweigelt. Both authentic wines and their phenolic extracts were investigated by attenuated total reflectance (ATR)-mid-infrared spectroscopy. Phenolic extracts were also investigated by UV-vis spectroscopy. The wine extracts were obtained by solid-phase extraction with C-18 columns and elution by methanol containing 0.01% hydrochloric acid. Hierarchical cluster analysis was performed with mid-infrared spectra of both wines and extracts, as well as with UV-vis spectra of the phenolic extracts. Data processing involved vector normalization and derivation of the spectra. Due to varying concentrations of main components including sugar and organic acids, satisfactory classification of untreated wines was not achieved. However, when using mid-infrared spectra of the phenolic extracts, almost complete discrimination of all cultivars investigated was achieved. The use of UV-vis spectroscopy for cultivar discrimination was found to be limited to the authentication of the Burgundy species Pinot Noir. In addition, soft independent modeling of class analogy was applied to the mid-infrared spectra of the extracts. It was possible to establish class models for five different wine cultivars and to classify test samples correctly.     

西北地区干红葡萄酒产地与酒龄的理化判别方法

西北地区具有独特的风土条件，适宜酿酒葡萄的种植，已形成"大产区大品牌"的产业规划。但西北地区葡萄酒的地域风格尚不明晰，导致产业的规范性不足，可持续发展存在隐患。该研究分析西北地区干红葡萄酒的23项重要的色泽-味感理化指标，旨在开发一种基于机器学习技术的葡萄酒判别方法，实现西北地区干红葡萄酒产地和酒龄的精准判别。首先，以西北地区200款干红葡萄酒为研究对象，通过理化试验测定了总酚、总花色苷、滴定酸等23项色泽-味感理化指标；然后，采用Pearson相关系数分析了西北产区葡萄酒质量特征的一致性，并耦合随机森林（Random Forest, RF）分析理化指标对干红葡萄酒产地和酒龄表征的贡献度；最后，基于人工神经网络（Artificial Neural Networks, ANN）构建了西北地区干红葡萄酒产地和酒龄的精准判别模型。结果表明，色泽相关指标的模型贡献率合计31%，花色苷相关指标的模型贡献率合计26%，酚类物质相关指标的模型贡献率合计21.1%。模型对宁夏产区酒样判别的灵敏度（Sensitivity, SEN）为98.72%，准确率（Accuracy, CCR）98.72%；对新疆产区酒样判别的SEN为95.45%，CCR为100%；对甘肃产区酒样判别的SEN为100%，CCR为95.45%。该方法可以实现西北产区干红葡萄酒产地和酒龄的精准判别，可为中国西北地区优质葡萄酒的生产和产品的市场监管提供科学依据。     

辐照加速黄酒陈化效果的研究

用适宜剂量辐照黄酒,经半年贮藏,达到陈化一年半的效果。辐照可使黄酒增香、味醇厚、爽口、鲜美。辐照酒的化学指标符合轻工部标准,色、香、味、格保持黄酒特有风味。辐照酒中游离氨基酸总量和人体必需氨基酸量有明显增加。卫生安全性试验表明,对健康无害,符合国家标准。辐照酒中H_2O_2含量无明显增加,未发现长寿命自由基,小白鼠急性LD_(50)>10g/kg体重,属实际无毒,微核实验为阴性。辐照陈化黄酒方法简便,成本低,具有很大的经济效益,有希望在生产中推广应用。     

Nuclear magnetic resonance profiling of wine blends

Nuclear magnetic resonance (NMR) profiling is used for characterization of monocultivar binary wine mixtures. Classification and quantification of the relative amount of wine in the mixture are made in two steps. First, each sample is classified as a mixture of a determined type by solving the appropriate classification problem using NMR profiles. The relative amount of the two corresponding monovarietal wines is then evaluated by multilinear regression of a selected set of NMR variables. Linear discriminant analysis (LDA), used in the classification step, gives a very good separation among the different mixture classes. On the other hand, a single layer artificial neural network, used to solve the multilinear problem, gives the relative amount of wine type in the mixture with a precision of about 10%.     

Analysis of ethylidene-bridged flavan-3-ols in wine

A method was developed to determine the amount of ethylidene-bridged flavan-3-ols in wine. The method was based upon the analysis of 2,2'-ethylidenediphloroglucinol (EDP), a product formed after acid-catalyzed cleavage of wine flavan-3-ols in the presence of excess phloroglucinol. In the developed analytical method, the wine was purified and concentrated using C18 solid-phase extraction before the phloroglucinolysis reaction was carried out. This procedure was used to quantify ethylidene-bridged flavan-3-ols in wine and the molar ratio between ethylidene-bridged linkages and native interflavan linkages. The method validation showed 9.2% repeatability. The recovery of the ethylidene-bridged flavanols in wine was 90% for concentrations up to 4.5 mg.L-1 of ethylidene-bridged linkages, and it decreases to 83% above and until the concentration reached 7.6 mg.L-1. Initial results showed that the concentration of ethylidene-bridged flavan-3-ols measured in wines was very low (less than 1.3 mg.L-1) and that they represented less than 1.3% of the total interflavonoid linkages on a molar ratio.     

Effect of a polyphenols-enriched chardonnay white wine in diabetic rats

A Chardonnay white wine enriched in polyphenols was obtained by modification of winemaking and characterized by its enrichment in total polyphenolic content (1346 mg/L as compared to 316 mg/L for traditional Chardonnay) and in various individual polyphenols (catechin, epicatechin, procyanidins dimers B1-B4, gallic acid, cafeic acid, and caftaric acid), as determined from HPLC coupled to a diode array detector. The polyphenols-enriched white wine (W) or its ethanol-free derivative (EFW) was then administered by gavage (10 mL/kg, twice a day) for 6 weeks to rats that have been rendered diabetic by a single iv injection of streptozotocin (55 mg/kg). Treatments had no effect on the symptoms associated with hyperglycemia. However, while a reduction in plasma antioxidant capacity was associated with the diabetic state, administration of W or EFW restored plasma antioxidant capacities to a level not significantly different from that of nondiabetic control animals. In addition, the effect of both treatments was manifested by the enlargement of mesenteric arteries, as determined by quantitative histomorphometry. In summary, our study indicates that white wine, when enriched in polyphenols, is able to induce ethanol-independent in vivo effects in a model of insulin-deficient diabetes characterized by a major oxidative stress.     

Prediction of wine color attributes from the phenolic profiles of red grapes (Vitis vinifera)

Knowledge about the relation between grape and wine phenolics is of key interest for the wine industry with respect to being able to predict wine quality from analyses of grapes. Prediction of the phenolic composition and color of experimentally produced red wines from the detailed phenolic composition of the corresponding grapes was investigated using a multivariate approach. Grape extracts and wines were produced from 55 different grape samples, covering 8 different Vitis vinifera cultivars: Alicante, Merlot, Syrah, Cinsault, Grenache, Carignan, Cabernet Sauvignon, and Mourvedre. The phenolic composition of the grapes and wines showed that the average ratios between wine and grape phenolics ranged from 0.25 to 7.9 for the different phenolic compounds. Most interestingly, the average ratios were low for anthocyanins (0.31) and tannins (0.32), intermediate for (+)-catechin (0.75) and polymeric pigments (0.98), and high for gallic acid (7.9). Individual wine phenolics in general correlated well with several grape phenolics, indicating that a multivariate approach might be advantageous for prediction of wine phenolics from grape phenolics analysis. However the use of multivariate prediction of individual wine phenolics from the complete grape phenolic composition only improved the prediction of wine polymeric pigments, whereas wine anthocyanins were predicted with the same precision as from the direct relation with grape anthocyanins. Prediction of color attributes of pH normalized experimental wines from the phenolic profiles of grapes was accomplished using a multivariate approach. The correlation between predicted and measured total wine color was high ( r = 0.958) but was very similar to the correlation coefficient obtained for the direct relation between grape anthocyanins and total wine color ( r = 0.961). Color due to copigmentation, color due to anthocyanins, and color intensity were also predicted well.