桉树杂交种与其亲本的近红外光谱判别

研究桉树控制授粉后目标性状的基因作用方式是探索其基因重组规律的重要内容。常规的数量统计分析精度往往不高,而DNA分析的专业要求高,且费时费力。该研究利用近红外光谱(NIRs)研究不同基因型桉树杂交种、亲本及杂交种与亲本间近红外光谱信息的关系,探索NIRs用于桉树杂交种与其亲本判别的可行性和准确性。以控制授粉的桉树亲本及其杂交F1代材料为对象,每种基因型从各自田间试验分别选取10个单株,采集树冠中上部新鲜健康叶片。用手持式近红外仪Phazir Rx(1624)采集桉树杂交种与其亲本叶片的NIRs信息。每单株选10片完全生理成熟的健康叶片,避开叶脉扫描其正面光谱5次,以50条NIRs信息的均值代表单个叶片的NIRs信息,最终每个基因型获得10条NIRs信息。对原始NIRs采用二阶多项式S.G一阶导数预处理。预处理后的NIRs用于多元统计分析,首先对桉树杂交亲本和子代样本进行主成分分析(PCA),直观展示不同基因型的分类情况。然后运用簇类独立软模式(SIMCA)和偏最小二乘判别分析(PLS-DA)两种有监督的判别模式验证NIRs用于桉树杂交种与其亲本树种的分类判别效果。PCA结果显示,不同的亲本间、杂交种间及杂交种与亲本间样本的主因子得分可以清晰地将各基因型分开。SIMCA模式判别分析中,桉树杂交种样本到亲本PCA模型的样本距离显示,待判别样本能够形成单独的聚类,且能直观反映两者的遗传相似。PLS-DA判别结果显示,桉树杂交亲本的PLS模型能通过预测其杂交子代的响应变量将其与亲本准确分开。结果表明,桉树叶片的NIRs信息可以准确地反映桉树杂交子代遗传信息的传递规律,NIRs判别模型可以准确地将各种基因型予以区分。因此,NIRs信息不仅可用于桉树杂交种和纯种的定性判别,还可以分析桉树基因重组过程中加性遗传效应的大小,从而为桉树遗传基础分析及其育种改良研究提供理论支撑。     

浙江中部夏熟作物田主要杂草生态相似性的数量分析

应用七级目测法对浙江中部地区27个夏熟作物田样点的杂草进行了优势等级调查，将所得数据转换成重要值，以杂草在27个样点中的重要值为运算指标，应用主成分分析法和图论聚类中的最小生成树法，对24种杂草的生态学相似性进行了比较，指出了长期使用单一的除草剂导致农田杂草种群迅速更迭的原因：杂草对除草剂的敏感性差异及不同杂草间的生态学特性的差异。     

Mathematical topographical correction of XPS images using multivariate statistical methods

For rough heterogeneous samples, the contrast observed in XPS images may result from both changes in elemental or chemical composition and sample topography. Background image acquisition and subtraction are frequently utilized to minimize topographical effects so that images represent concentration variations in the sample. This procedure may significantly increase the data acquisition time. Multivariate statistical methods can assist in resolving topographical and chemical information from multispectral XPS images. Principal component analysis (PCA) is one method for identification of the highest correlation/variation between the images. Topography, which is common to all of the images, will be resolved in the first most significant component. The score of this component contains spatial information about the topography of the surface, whereas the loading is a quantitative representation of the topography contribution to each elemental/chemical image. The simple‐to‐use self‐modelling mixture analysis (Simplisma) method is a pure variable method that searches for the source of most differences in the data and therefore has the potential to distinguish between chemical and topographical phases in images. The mathematical background correction scheme is developed and validated by comparing results to the experimental background correction for samples with differing degrees of topography. Copyright © 2004 John Wiley & Sons, Ltd.     

Attenuated Total Reflection-Fourier transform infrared analysis of the fermentation process of pineapple

A direct and reagent free procedure has been developed to monitor the fermentation process of pine apple nectar using Attenuated Total Reflectance Fourier-transform mid-infrared spectrometry (FT-IR) and multivariate analysis. A classical 4² design for standards was employed for calibration using the information in the spectral range from 907 to 1531 cm⁻¹ of the first order derivative spectra after mean centering of infrared data. The root mean square error of calibration (RMSEC) of 0.040, 0.021, 0.063 and 0.074% w/w were obtained for glucose, fructose, saccharose and ethanol, respectively, and a mean relative validation error of 2.9, 2.1, 2.6 and 3.6% was achieved for glucose, fructose, saccharose and ethanol. Results obtained by the proposed procedure for the alcohol content at different fermentation levels were statistically comparable with those obtained by a reference spectrometric method. So, FT-IR spectrometry provides a fast alternative to long and tedious classical procedures to ethanol determination and sugar enzymatic analysis.     

Use of chemometrics and mid infrared spectroscopy for the selection of extraction alternatives to reference analytical methods for total fat isolation

Chemometric techniques have been used to compare two methods for fat extraction, namely focused microwave-assisted Soxhlet extraction (FMASE) and dynamic ultrasound-assisted extraction (DUAE), with the conventional Folch method, frequently used as reference. The data generated by a mid infrared spectrometer, after appropriate treatment, provide a simple and effective way for the detection of potential alterations of the fat obtained with the assistance of auxiliary energies, in this case, microwaves and ultrasounds. The results thus obtained are as compared with those from the Folch method, a mild extraction method with a view to finding faster alternatives for routine analysis. Moreover, classification of the samples between cookies and snacks based on extraction kinetics studies was possible, thus demonstrating the importance of these studies for the development of analytical methods. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were used for both purposes, namely detection of alterations and classification of the samples as a function of their extraction kinetics, while K Nearest Neighbours (KNN) and Soft Independent Modelling of Class Analogy (SIMCA), based on PCA, models were generated in order both to predict the extraction kinetics of unknown samples, thus adjusting the extraction time as a function of the matrix, and find out explanation to the different extraction kinetics.     

A Structure-activity Relationship （SAR） Study of Fluoroquinolones with Biological Activity against Anti-S.pneumoniae

1INTRODUCTION Streptococcus pneumoniae is a key pathogen in many respiratory tract infections.In a Canada-wide surveillance study published in1999,it was reported that21.2%of pneumococcal tested were interme-diately susceptible or resistant to penicillin.As the newer respiratory fluoroquinolones are active aga-inst both penicillin-susceptible and penicillin-resis-tant isolates of S.pneumoniae,they will be increa-singly important in the future treatment of infections caused by this pathoge…     

Study of cork (from Quercus suber L.)-wine model interactions based on voltammetric multivariate analysis

The cork from Quercus suber L. is the premium raw material used to produce wine-bottling stoppers; however, being a natural product, cork can be contaminated and attacked in different ways that could promote differences in its proprieties. A specific contamination is the defect known in the industry as “Mancha Amarela—Yellow spot” (MA). This cork shows modifications in its mechanical, structural and optical properties and is potentially able to cause off-flavours in wine. In this study, a new analytical approach is proposed for the rapid screening of cork-wine model interactions in order to determine if the cork were able to contaminate a wine. Cork samples classified as standard (S) and cork MA were put in contact with a wine model matrix. The model matrix was analysed by cyclic voltammetry and square wave voltammetry in function of different contact times. Considering that matrices in contact with cork S and MA exhibited different pH, the influence of this parameter on the distinction power was also evaluated. The data sets obtained from the different techniques were treated by principal component analysis (PCA) and PLS_Cluster. The major difference between samples S and MA is the occurrence of an important peak at ca. 580 mV in the MA voltammograms. This more positive peak may be assigned to lignin related phenolics; therefore, it can be proposed as a possible marker to follow lignin degradation.     

Chromatographic analysis of sugars applied to the characterisation of monofloral honey

The control of the floral quality of honey has become a priority issue as a result of the number of abuses observed and the relative ease of getting around existing control methods. We conducted chromatographic analyses of honey sugars to determine new criteria for authenticating an origin. The work involved creating databases by analysing a large number of authentic honeys from seven monofloral varieties, followed by statistical processing of the results by a principal components analysis. Differences in composition could thus be demonstrated, such as the presence of trisaccharides in fir honey, that provide an additional tool for authenticating unknow commercial honeys.     

The state of conservation of painted surfaces in the presence of accelerated ageing processes monitored by use of FT-Raman spectroscopy and multivariate control charts

A new method has been developed for monitoring the degradation of paintings. Two inorganic pigments (ultramarine blue and red ochre) were blended with linseed oil and spread on canvas. Each canvas was subjected to simulated accelerated ageing in the presence of typical degradation agents (UV radiation and acidic solution). Periodically the painted surfaces were analysed by FT-Raman, to investigate the status of the surface. The data obtained were analysed by principal component analysis (PCA). Finally the Shewhart and cumulative sum control charts based on the relevant principal components (PC) and the so called scores monitoring and residuals tracking (SMART) charts were built. The method based on the use of PC to describe the process was found to enable identification of the presence of relevant modification occurring on the surface of the samples studied.Electronic supplementary material Supplementary material is available for this article at