Characterization of tomato generations according to a three-way data analysis

Abstract

Availability of a three-way data analysis to characterize two consecutive tomato (Solanum lycopersicum) generations is necessary to continue a plant breeding program with less uncertainty. The aim of this work was to analyze tomato fruit quality from F 2 and F 3 populations by two three-way data analysis: multiple factorial analysis (MFA) and generalized procrustes analysis (GPA). These techniques have the same main objective, searching for a common structure, but they achieve it in different ways. This work evaluated 18 tomato genotypes, represented by individual plants in F 2 and selfed families in F 3. The same quantitative traits related to fruit quality were measured in both generations. The first two axes of the MFA represented 51.0% of the total variability. From the representation of the genotypes on these axes, traits differing from one generation to another were identified. The first two axes of the GPA represented 56.4% of the total variability. This analysis provided a table of analysis of variance (ANOVA), which corroborated the graphic and analytical interpretations of the MFA, a technique that provides the composition of the obtained axes. The comparison between the results obtained from these techniques indicated that both MFA and GPA allowed the detection of genotypes with discrepancies between the two generations. The MFA technique presented the advantage of studying graphically and analytically the nature and degree of phenotypic differences among genotypes in both generations, while the GPA complemented the analysis with an ANOVA, achieving the quantification of statistical significances for the discrepancies or similarities between them.

Combining Image-Based Phenotyping and Multivariate Analysis to Estimate Fruit Fresh Weight in Segregation Lines of Lowland Tomatoes

“…In this context, the selection intensity [63,86,87], percentage of genetic progress [5,65,88] and the effectiveness of secondary traits [66,67,89] genetic approaches were applied to enhance the precision of identifying optimal predictor in segregating tomato populations. Previous researches consistently underscored the effective shared ability of such genetic methodologies to compare secondary traits, particularly in F2 populations [6,14,90,91]. In this study, despite WFW displaying higher direct influence and heritability values compared to whole fruit area WFA, this superiority was deemed genetically insufficient to consider WFW as a valuable predictor.…”

Tomato F3 lines development and its selection index based on narrow-sense heritability and factor analysis

“…Single selection with productivity is considered very risky because the yield is polygenic with a complex genetic pattern (Anisa et al 2022). This indicates that multi-character selection needs to be carried out systematically on the F3 tomato population (Medico et al 2020). One approach that can be used in multi-character selection is the index selection approach.…”