NDLI: Comparison of efficiency of distance measurement methodologies in mango (Mangifera indica) progenies based on physicochemical descriptors.

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Comparison of efficiency of distance measurement methodologies in mango (Mangifera indica) progenies based on physicochemical descriptors.

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Comparison of efficiency of distance measurement methodologies in mango (Mangifera indica) progenies based on physicochemical descriptors.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Souza, A. M. Corrêa, R. X. Santos, C. A. F. Cerqueira-Silva, C. B. M. Lima Neto, F. P. Alves, E. O. S.
Description	Country affiliation: Brazil Author Affiliation: Alves EO ( Departamento de Ciências Biológicas, Universidade Estadual de Santa Cruz, Ilhéus, BA, Brasil.)
Abstract	We investigated seven distance measures in a set of observations of physicochemical variables of mango (Mangifera indica) submitted to multivariate analyses (distance, projection and grouping). To estimate the distance measurements, five mango progeny (total of 25 genotypes) were analyzed, using six fruit physicochemical descriptors (fruit weight, equatorial diameter, longitudinal diameter, total soluble solids in °Brix, total titratable acidity, and pH). The distance measurements were compared by the Spearman correlation test, projection in two-dimensional space and grouping efficiency. The Spearman correlation coefficients between the seven distance measurements were, except for the Mahalanobis' generalized distance (0.41 ≤ rs ≤ 0.63), high and significant (rs ≥ 0.91; P < 0.001). Regardless of the origin of the distance matrix, the unweighted pair group method with arithmetic mean grouping method proved to be the most adequate. The various distance measurements and grouping methods gave different values for distortion (-116.5 ≤ D ≤ 74.5), cophenetic correlation (0.26 ≤ rc ≤ 0.76) and stress (-1.9 ≤ S ≤ 58.9). Choice of distance measurement and analysis methods influence the.
e-ISSN	16765680
Journal	Genetics and Molecular Research
Issue Number	1
Volume Number	11
Language	English
Publisher	Fundação de Pesquisas Científicas de Ribeirão Preto
Publisher Date	2012-03-14
Publisher Place	Brazil
Access Restriction	Open
Subject Keyword	Genetic Variation Mangifera Genetics Genotype Classification Models, Genetic Models, Statistical Phenotype Statistics, Nonparametric Research Support, Non-u.s. Gov't Discipline Genetics Discipline Molecular Biology Discipline Bioinformatics
Content Type	Text
Resource Type	Article

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