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Simultaneous Agronomic and Molecular Characterization of Genotypes via the Generalised Procrustes Analysis

An Application to Cucumber

^a Facultad de Ciencias Agrarias, Universidad Nacional del Comahue, 8303 Cinco Saltos, Río Negro, Argentina
^b Instituto Valenciano de Investigaciones Agrarias (IVIA), Apartado Oficial, E-46113 Moncada (Valencia), Spain

View larger version (30K): [in a new window]   Fig. 1. Two-dimensional agronomic ordination of the 41 entries of cucumber and Minimum Spanning Tree (MST): (a) Principal Coordinate (PcoA) for qualitative traits and (b) Principal Component Analysis (PCA) for quantitative traits.

View larger version (27K): [in a new window]   Fig. 2. Two-dimensional ordination of the 41 entries of cucumber after a Principal Coordinates Analysis using RAPD markers data and Minimum Spanning Trees (MST).

View larger version (32K): [in a new window]   Fig. 3. Configuration of consensus matrix of Generalized Procrustes Analysis (GPA) in first two axes with Minimum Spanning Trees (MST): (a) consensus between qualitative and quantitative agronomic data, and (b) consensus between agronomic traits and molecular traits.

View larger version (22K): [in a new window]   Fig. 4. Configuration of consensus matrix of Generalized Procrustes Analysis (GPA) in first and third axis.

View larger version (24K): [in a new window]   Fig. 5. Cluster analysis for 41 entries of cucumber for agronomic traits and random amplified polymorphic DNA (RAPDs) using Euclidean distance for consensus configuration obtained of Generalized Procrustes Analysis (GPA) and unweighed pair-group method using arithmetic averages (UPGMA) groping method. Encircled entry labels correspond to external controls.