A COMPARISON OF METHODOLOGY APPLIED TO THE SELECTION OF A PANEL FOR SENSORY EVALUATION OF INSTANT COFFEE

Twenty judges performed a variety of chemosensory tasks in order to select the best scores to form a panel for coffee evaluation. An average of correct responses (P%), one-way analysis of variance (ANOVA) and principal components analysis (PCA) were compared. The tests involved: ability to recognize the four basic tastes, identification and matching of odors, taste intensity evaluation and perception of small differences in taste. P% accounted for 71.17 ± 4.34% and 10 of the judges had scores greater than the final average. ANOVA and PCA resulted in 2 different panels consisting of 9 and 12 judges, respectively. The panel was composed by the nine panelists selected by the three methods. The other three panelists that were doubtful could improve to the point of acceptance with additional training. These methods should be used simultaneously to have more security in the acceptance or rejection of panelists.     

EVALUATION OF WINE COMPETITION JUDGE PERFORMANCE USING PRINCIPAL COMPONENT SIMILARITY ANALYSIS

Principal component similarity (PCS) analysis was used to evaluate judge performance from a wine competition. Data were analyzed for five international judges and seven wine makers, for 42 white, 30 red and 25 specialty wines, using a 20-point quality scoring system. Principal similarity plots were used to group judges according to judging 'style' and to identify outliers, for each wine category. Judge groupings were consistent when three different references were used; however, the most interpretable PCS plot was obtained when the overall mean-judge-score was used as the reference. Results from PCS were compared to principal component analysis (PCA). PCS analysis allowed the information from all significant principal components to be graphically represented in two dimensions and was more successful in classifying judges than plots based on the first three principal components. The technique of PCS is an important complement to existing methodologies, and can provide wine competition coordinators with an objective technique for judge evaluation and selection.     

GRAPES: A METHOD AND A SAS® PROGRAM FOR GRAPHICAL REPRESENTATIONS OF ASSESSOR PERFORMANCES

GRAPES computes individual and global analyses of variance for sensory profiling data, consisting of several sessions in which all the panelists gave scores to all the products for a number of attributes. The fitted model takes into account the session effect. GRAPES summarizes the results by means of graphical assessor scatterplots which allow to check and to compare panelist performances, such as the way of using scale, the reliability, the discrimination power and the agreement with the panel. In addition, GRAPES detects the outliers for each of these criterion. The usefulness of GRAPES for the panel leader will be demonstrated using texture and flavor profiling of 4 restructured steaks by 12 assessors for 15 attributes. The SAS® program GRAPES, available by e-mail from the author, requires the SAS/BASE®, SAS/STAT®, SAS/GRAPH® and SAS/IML® softwares.     

SELECTION AND SCREENING OF A DESCRIPTIVE PANEL FOR EWES MILK CHEESE SENSORY PROFILING

The aim of this work was to select a competent sensory panel considering its ability to describe ewes milk cheese sensory properties. The panelists evaluated the sensory characteristics of several ewes milk cheeses in terms of odor, flavor and texture. The performance of judges was assessed taking into account the following aspects: (1) individual discriminatory ability and reproducibility for each sensory attribute; (2) group discriminatory ability and reproducibility and agreement between judges for each attribute; (3) panel homogeneity; (4) panel consonance; and (5) overall panel discriminatory ability. The panel performance was checked with a set of statistical procedures. The results obtained by the selected group were better than the initial panel from the point of view of discriminant power, reproducibility and agreement. The suggested method can be easily applied in routine control of assessors performance and to discover deviant behavior or differences in individual perception of the samples.     

海南岛热带草地的数量分类和排序研究

本文用一些数量分类和排序的方法对海南岛鹦歌岭热带草地进行了分类和排序。所用的方法包括两种多元等级聚合分类--最近邻体法(NN)和最远邻体法(FN),极点排序(PO)和主分量分析(PCA)排序。结果表明：把19个样地分为三大类型、9个群落,其分布格局与坡度、放牧强度和土壤肥力密切相关。所用的四种方法在热带草地的研究中均有一定的适用性。     

Petal micromorphology and its relationship to pollination

• The characteristics of petal epidermal conical cells affect the quality of the signals perceived by various pollinators. This study aimed to identify variations in micromorphological characteristics of flower petals and their relationship to melittophily, ornithophily and chiropterophily pollination systems.
• The petals of 11 species were analysed using scanning electron microscopy and optical microscopy and the micromorphological traits were described, measured and compared using Tukey's test, PCA and cluster analysis.
• Unlike chiropterophily, all melittophilous and some ornithophilous species possessed adaxial epidermal conical cells. Cluster grouping separated chiropterophilous flowers from melittophilous and ornithophilous. PCA analysis showed that the two morphometric profile of conical cells was the attribute that most strongly influenced the grouping of species. When considering the data set of the three pollination systems, melittophilous and ornithophilous plants were more similar to each other than they were to chriopterophilous species. The distance between conical cell apices is an important parameter in interactions with pollinators.
• This study facilitated recognition of smoothing pollinator resource access through petal micromorphological characteristics. Further research regarding the biometry of micromorphological traits related to pollination is required.

     

EVALUATION OF PANELIST PERFORMANCE IN DESCRIPTIVE PROFILING OF RANCID SAUSAGES: A MULTIVARIATE STUDY

This paper illustrates an application of principal component analysis (PCA), partial least squares regression (PLS) and generalized procrustes analysis (GPA) to evaluate the ability of a trained group of assessors to perceive rancidity in foods. PCA and regression PLS were utilized to determine to which extent sensory attributes capture the information perceived by a trained sensory panel, and if this can be developed into a predictive model for rancidity in sausages. The data were submitted to a GPA to obtain a map of the products for each subject as compared with a consensus products map. Assessors plots for the sensory attributes were also obtained to reveal the dissimilarities between panelists and to explore clustering.     

稀有濒危植物翅果油树种群黄酮类化合物多样性研究

以稀有濒危植物翅果油树叶中黄酮类化合物为标记,探索翅果油树种群与其生境的相互关系。通过对濒危植物翅果油树的主要分布区,山西省的乡宁、翼城、平陆等三种群及环境的调查,并采集三个种群的24个样品。用水提法、甲醇提法,经聚酰胺薄层层析法分离,并将层析结果作1/0的二元数据化处理,用于聚类分析和PCA排序。结果表明:1)翅果油树叶中黄酮类化合物的种类比较稳定,可以作为研究种群分化的标记物;2)聚类分析表明乡宁、翼城、平陆三个种群间所含的黄酮类化合物已有分化,乡宁种群与翼城种群之间的相异性较小,在截取值为20时,乡宁与翼城种群首先聚为一支,当截取值为25时,平陆种群归并,表明平陆种群与其他种群的相异性较大;3)各种群内个体间的共享率有明显的差异4)PCA分析表明:不同种群内的黄酮类化合物的差异与其地理位置、温度、地形地貌及土壤养分等因子有关。     

Analysis of the genetic diversity of garlic (Allium sativum L.) by simple sequence repeat and inter simple sequence repeat analysis and agro-morphological traits

The genetic diversity of 39 garlic accessions was investigated using eight simple sequence repeat (SSR) primer combinations and 17 inter-simple sequence repeat (ISSR) primer combinations. A total of 109 polymorphic loci were detected among these accessions, with an average of 4.63 polymorphic loci per SSR primer combination and 4.29 polymorphic loci per ISSR primer combination. The mean effective number of alleles, the mean Nei's genetic diversity, and the mean Shannon's information index for SSR were 1.4799, 0.2870, and 0.4378, respectively; and those for ISSR were 1.4847, 0.2898 and 0.4415, respectively. Cluster analysis, using the unweighted pair-group method with arithmetic averages (UPGMA) based on the allele frequency data, classified the accessions into three groups. The results of principal component analysis (PCA) were consistent with those of the cluster analysis. PCA showed that each of these three groups exhibited significant variation in agro-morphological traits. These findings suggest that the eight SSR and 17 ISSR primers identified could define valuable markers for genetic diversity for use by plant breeders.     

Multivariate analysis of the selected metals in the hair of cerebral palsy patients versus controls

Seventeen metals were measured in scalp hair samples from cerebral palsy patients (CPPs) and controls. Samples were collected from 95 CPPs and 93 controls. The nitric acid-perchloric acid wet digestion procedure was used for quantification of the selected metals by flame atomic absorption spectrophotometry. The concentrations of Ag, Ca, Cd, Co, Cr, Li, and Mg were significantly higher and those of Cu, Fe, K, Mn, Na, Ni, Pb, and Sb were lower in the hair of CPPs compared with controls. A strong positive correlation was found between Ca and Mg in the hair of controls but not in that of CPPs. Antimony was found significantly negative in terms of its correlation with Co and Cu in CPPs group but not in the controls. Principal component analysis (PCA) of the data extracted seven factors for CPPs and six factors for controls. Cluster analysis (CA) was also used to support the PCA results. The study evidenced some specific source of Mg and Sb in the hair of CPPs.     

Principal-Component Analysis for Assessment of Population Stratification in Mitochondrial Medical Genetics

Although inherited mitochondrial genetic variation can cause human disease, no validated methods exist for control of confounding due to mitochondrial population stratification (PS). We sought to identify a reliable method for PS assessment in mitochondrial medical genetics. We analyzed mitochondrial SNP data from 1513 European American individuals concomitantly genotyped with the use of a previously validated panel of 144 mitochondrial markers as well as the Affymetrix 6.0 (n = 432), Illumina 610-Quad (n = 458), or Illumina 660 (n = 623) platforms. Additional analyses were performed in 938 participants in the Human Genome Diversity Panel (HGDP) (Illumina 650). We compared the following methods for controlling for PS: haplogroup-stratified analyses, mitochondrial principal-component analysis (PCA), and combined autosomal-mitochondrial PCA. We computed mitochondrial genomic inflation factors (mtGIFs) and test statistics for simulated case-control and continuous phenotypes (10,000 simulations each) with varying degrees of correlation with mitochondrial ancestry. Results were then compared across adjustment methods. We also calculated power for discovery of true associations under each method, using a simulation approach. Mitochondrial PCA recapitulated haplogroup information, but haplogroup-stratified analyses were inferior to mitochondrial PCA in controlling for PS. Correlation between nuclear and mitochondrial principal components (PCs) was very limited. Adjustment for nuclear PCs had no effect on mitochondrial analysis of simulated phenotypes. Mitochondrial PCA performed with the use of data from commercially available genome-wide arrays correlated strongly with PCA performed with the use of an exhaustive mitochondrial marker panel. Finally, we demonstrate, through simulation, no loss in power for detection of true associations with the use of mitochondrial PCA.     

Development of a target component extraction method from GC-MS data with an in-house program for metabolite profiling

After gas chromatography-mass spectrometry (GC-MS) analysis, data processing, including retention time correction, spectral deconvolution, peak alignment, and normalization prior to statistical analysis, is an important step in metabolomics. Several commercial or free software packages have been introduced for data processing, but most of them are vendor dependent. To design a simple method for Agilent GC/MS data processing, we developed an in-house program, "CompExtractor", using Microsoft Visual Basic. We tailored the macro modules of an Agilent Chemstation and implanted them in the program. To verify the performance of CompExtractor processing, 30 samples from the three species of the genus Papaver were analyzed with Agilent 5973 MSD GC-MS. The results of CompExtractor processing were compared with those of AMDIS-SpectConnect processing by hierarchical cluster analysis (HCA) and principal component analysis (PCA). The two methods showed good classification according to their species in HCA. The PC1+PC2 scores were 54.32-63.62% for AMDIS-SpectConnect and 56.65-85.92% for CompExtractor in PCA. Although the CompExtractor processing method is an Agilent GC-MS-specific application and the target compounds must be selected first, it can extract the target compounds more precisely in the raw data file with batch mode and simultaneously assemble the matrix text file.     

Neuroecology of cyprinids: comparative,quantitative histology reveals diverse brain patterns

Synopsis Brain patterns are compared by quantitative histology in 28 native and introduced mid-European cyprinid species, considering 17 primary sensory and higher order brain areas. Cluster analysis (CLA) and principal component analysis (PCA) based on relative volumes of these brain areas indicate that cyprinid brains are diversified into four major groups, basic cyprinid, abramine, octavo-lateralis and chemosensory. PCA recognizes the brain of Phoxinus phoxinus as a fifth group. Interspecific differences in brain morphology are mainly caused by variability in relative sizes of the brain stem lobes for external and internal taste (lobus facialis and lobus vagus), as well as of octavo-lateralis and visual areas. Higher order brain areas show little interspecific variation in relative size, and were grouped by PCA according to inter- and intraspecific allometries. Hypotheses on brain functions are based on brain area correlations. We propose that the processing of external taste information in the valvula cerebelli may be particularly important for benthivorous cyprinids, whereas the integration of octavo-lateralis input with visual information via the torus longitudinalis-stratum marginale system may play a key role in the planktivores. Brain patterns suggest two major pathways of cyprinid evolutionary and ecological radiation, one leading from the basic cyprinids towards octavo-lateralis dominated midwater and surface planktivores, the second towards taste-dominated benthivores.     

On Aggregating Species for Risk Assessment

Different combinations of species characteristics like dietary strategies and foraging tactics define unique pathways for material cycling and energy flow in ecosystems. I used multivariate cluster analysis on a species attribute matrix to identify groups of species with similar vulnerabilities of exposure to contaminants. The clusters of species may also have similar functions in ecosystems, because they use similar resources in similar ways. Cluster analyses produced hierarchical dendrograms of species relationships that were difficult to characterize with simple labels like herbivore or insectivore. Regardless of whether multivariate analyses are used for aggregating species into exposure guilds, the species attribute matrix is a concise statement of assumptions about how species function in ecosystems. By using species characteristics to aggregate and define assessments, it is hoped that assessment endpoints will be ecologically relevant.     

花椰菜自交系主要形态性状的主成分分析和聚类分析

通过对54个花椰菜自交系材料进行主成分分析和聚类分析研究,以期为花椰菜育种中亲本选配提供帮助。结果表明:在主成分分析中,选取方差累积贡献率为70.024%的前6个主成分来评价花椰菜自交系资源;现球期、采收期、叶长、叶宽、株高、花球纵径、花球横径、球重、球形、球紧实度、叶色、蜡粉、内叶数、始花期和株幅是花椰菜亲本选择的主要形态指标。进一步通过系统聚类,将54个花椰菜自交系分为3类:第Ⅰ类表现为早熟、株幅小、叶片狭窄、蜡粉较少、球重和紧实度中等;第Ⅱ类表现为中熟、株幅中等、叶片灰绿、蜡粉较厚和花球半圆紧实且重;第Ⅲ类表现为晚熟、株幅大、株形高、叶片宽阔、蜡粉中等和花球扁圆。3个类群自交系性状之间的差异较为明显,有利于杂交育种亲本材料的选择。