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A segregation population of 184 genotypes derived from a pseudo-testcross of table grapes ( Vitis vinifera), together with 203 AFLP and 110 SSR markers was used to detect quantitative trait loci (QTLs) for fruit yield components. Diffferent QTLs, a low percentage of phenotypic variance explained by the QTLs detected and QTL instability over years were detected for each fruit yield component. These results confirm the complex genetic architecture of the yield components in grapevine due to the perennial nature of this species, which has to adapt to yearly variations in climate. Phenotypic correlation analyses between fruit yield components were also performed. The negative correlation between berry weight and the number of berries per cluster seems to have an indirect negative effect on cluster weight, as revealed by the path coefficient analysis; however, this negative correlation was not supported at the molecular level because no coincident QTLs were observed between these traits. Nonetheless, the possibility to select seedless genotypes with large berries without affecting cluster weight needs to be substantiated in future experiments because factors such as sample size and heritability might influence QTL identification in table grapes. [ABSTRACT FROM AUTHOR]

Genotypic diversity has been detected among aromatic grapevines (Vitis vinifera) by molecular markers (AFLPs). The 22 primer-pairs generated a total of 1,331 bands of which 564 (40%) were polymorphic over all the genotypes. The bootstrap analysis pointed out that a large number of polymorphic bands (200–400) has to be used for a better estimation of the genetic distances among genotypes; 383 polymorphic AFLP bands were used for the cluster and the principal coordinate analyses because they did not present missing data across all the genotypes. The cluster analysis (UPGMA), based on polymorphic AFLP markers, revealed no relationship between the Moscato and Malvasia grapevines. The Malvasias, unlike the Moscatos distinguished by their distinct muscat aroma, have to be considered a more complex group because it includes muscat and non-muscat grapevines. The principal coordinate analysis (PCO) confirmed the pattern of the cluster analysis only for those varieties which presented a low coefficient of dissimilarity, while for the other varieties there was no correspondence between the two analyses. The pattern of aggregation among aromatic grapevines in the cluster and principal coordinate analyses does not support any classification that might include an aromatic grapevine group in V. vinifera. Even though some synonyms and homonyms are present among aromatic grapevines (V. vinifera), genetic diversity exists among genotypes in AFLP markers. [ABSTRACT FROM AUTHOR]

Presents a mathematical function to study the growth of berry growth variability in grapes. Pattern of berry growth; Incorporation of the growth curve function of individual berry growth to whole plant; Advantages of a mathematical approach in the study of fruit growth; Kinetics of berry growth in grapes.