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Panel Performance (panel + performance)
Selected AbstractsPANEL PERFORMANCE AND NUMBER OF EVALUATIONS IN A DESCRIPTIVE SENSORY STUDYJOURNAL OF SENSORY STUDIES, Issue 4 2004JÉRÔME PAGÈS ABSTRACT The assessor performance is a key point in a sensory evaluation. In particular, at the end of a session, a decrease of the performance can be feared. We propose to analyze this performance with various criteria: usual ones as the main product effect or the error variance; a new one measuring the perceived products variability. The performance can then be studied all along the session from two points of view: in taking into account the only products tested at a given instant (named instantaneous); in taking into account all the products tested up to a given instant (named cumulative). In the presented example, in spite of the large number of products successively tested by each assessor, the instantaneous performance of the panel shows no significant deterioration. Furthermore, when the number of products tested by each assessor increases, more significant product effects can be obtained thanks to the accumulation of the amount of data. This shows that the number of products that can be reasonably studied by one assessor during one session is generally underestimated. [source] Culture-Specific Variation in the Flavor Profile of SoymilksJOURNAL OF FOOD SCIENCE, Issue 8 2006R.S.J. Keast ABSTRACT:, A modified quantitative descriptive analysis (QDA) method was used to determine sensory profiles of 8 soymilk products: 3 manufactured in Australia, 3 manufactured in Singapore, 1 manufactured in Malaysia, and 1 manufactured in Hong Kong. A panel (n= 7) was selected, trained in descriptive profiling of soymilk, and developed a soymilk language that was used to evaluate the flavor attributes of the soymilk products. A repeated-measure ANOVA showed highly reproducible panel performance, and significant differences in soymilk attributes among all soymilks. A principal component analysis (PCA) revealed 2 main groupings among the soymilks that corresponded to cultural origin: Australia and Asia (Singapore and Hong Kong/Malaysia). Products from Australia were significantly stronger in milky, astringent, salty notes and pale in color, while products from Asia were significantly stronger in beany, cooked beans, sweet, and pandan notes (P < 0.05). In addition, the Asian soymilks could be separated into 2 subgroups, with Singaporean soymilks having deeper color, greater viscosity, and less green flavor than Hong Kong/Malaysia soymilks. Australian produced soymilk is bovine-milk-like compared with Asian soymilk, presumably due to bovine milk being the primary source of milk in Australia. We conclude that culture-specific flavor preferences are a determining factor in flavor profiles of soymilks from geographically distinct regions. [source] A COMPARISON OF METHODS FOR MONITORING INDIVIDUAL PERFORMANCES IN TASTE SELECTION TESTSJOURNAL OF SENSORY STUDIES, Issue 4 2005AMALIA CALVIÑO ABSTRACT The evaluation of panel performance was made by three methods: average of correct responses (A), comparison of distances of individual standardized judgments to the average standardized responses (D) and a principal components analysis (PCA). Thirty assessors identified water and basic tastes and discriminated different sweet stimuli in neutral or acidified vehicles using R-index rating and ranking tests. By A and D methods 22 assessors were qualified as proficient. Composition of both panels was identical except for one judge. The output from PCA provided a graphical representation of the performance of the assessors and retained different subsets of 24,26 panelists for different proposals as discrimination of sweetness in acidified beverages, recognition of bitterness, sourness and discrimination of slight sweetness or evaluation of saltiness. [source] A PANEL PERFORMANCE PROCEDURE IMPLEMENTED IN RJOURNAL OF SENSORY STUDIES, Issue 3 2005EVA DERNDORFER ABSTRACT Monitoring performance is essential for the efficient use of a sensory panel both during training and while carrying out product assessments. We present a concise procedure to monitor panel performance based on classical statistical methods. The program includes tests for the ability to discriminate between products, repeatability of assessments, scale use, agreement between panelists and a principal component analysis map of panelist means across attributes. The algorithm is implemented in R , a state-of-the-art, freely available statistical software package. The program output is summarized in graphs and tables. This easily applicable panel performance procedure is aimed at improving sensory practice, especially in areas where the use of highly complex systems is not feasible. [source] A COMPARISON OF METHODS FOR EVALUATING THE PERFORMANCE OF A TRAINED SENSORY PANEL,JOURNAL OF SENSORY STUDIES, Issue 6 2001MARJORIE C. KING ABSTRACT Cluster analysis, consonance analysis, principal component analysis (PCA) and the GRAPES program (Schlich 1994) were compared for the evaluation of panel performance. Ten judges evaluated 25 Merlot wines for 24 color, aroma and flavor attributes. Cluster analysis grouped similar judges. PCA identified judges according to their attribute use. Consonance analysis determined a numerical index for attribute agreement and the GRAPES program compared judges in their use of the scale, reliability, discrimination and disagreement. Three of the four techniques provided a graphical representation of similarities and differences between judges. Methodologies were best used in conjunction with one another. Ultimately the application of these tools will serve to improve the quality of sensory evaluations. [source] Identifying Rarer Genetic Variants for Common Complex Diseases: Diseased Versus Neutral Discovery PanelsANNALS OF HUMAN GENETICS, Issue 1 2009K. Curtin Summary The power of genetic association studies to identify disease susceptibility alleles fundamentally relies on the variants studied. The standard approach is to determine a set of tagging-SNPs (tSNPs) that capture the majority of genomic variation in regions of interest by exploiting local correlation structures. Typically, tSNPs are selected from neutral discovery panels - collections of individuals comprehensively genotyped across a region. We investigated the implications of discovery panel design on tSNP performance in association studies using realistically-simulated sequence data. We found that discovery panels of 24 sequenced ,neutral' individuals (similar to NIEHS or HapMap ENCODE data) were sufficient to select well-powered tSNPs to identify common susceptibility alleles. For less common alleles (0.01,0.05 frequency) we found neutral panels of this size inadequate, particularly if low-frequency variants were removed prior to tSNP selection; superior tSNPs were found using panels of diseased individuals. Only large neutral panels (200 individuals) matched diseased panel performance in selecting well-powered tSNPs to detect both common and rarer alleles. The 1000 Genomes Project initiative may provide larger neutral panels necessary to identify rarer susceptibility alleles in association studies. In the interim, our results suggest investigators can boost power to detect such alleles by sequencing diseased individuals for tSNP selection. [source] | ||||||||||