The selection of superior strawberry genotypes is a complex process due to the high variability after hybridization that is caused by the octoploid nature and the heterozygosis, making the selection of multiple traits difficult. This study aimed to select strawberry hybrids with the potential for fresh consumption and/or processing by applying multivariate analysis to obtain traits of interest simultaneously. Hybrids were obtained from the crossing among seven commercial cultivars, defining a selection of 10% of them. The experimental design consisted of an augmented block design, with two commercial cultivars, Camarosa and Camino Real, as the controls. Different variables, including the number and average mass of commercial fruits, total fruit mass, pH, soluble solids (SS), titratable acidity (TA), SS/TA ratio, reducing sugars, pectin, ascorbic acid, phenolic compounds, and anthocyanin’s, were assessed. The selection of hybrids was based on the Mulamba and Mock rank-summation index, principal component analysis, and Ward’s hierarchical cluster analysis. The selection index was based on different weights being adopted for fresh market and processing. The assessed traits had high variability between hybrids. The highest selection gains were obtained for production traits, but the different weight assignment resulted in different classifications of hybrids for both fresh consumption and processing. Most of the hybrids selected by the index remained in the same group in the principal component and hierarchical cluster analyses, which indicates that multivariate analysis is a valuable tool for assisting in the selection of superior hybrids in the strawberry crop.

Methods of multivariate analysis is a powerful approach to assist the initial stages of crops genetic improvement, particularly, because it allows many traits to be evaluated simultaneously. In this study, heat-tolerant genotypes have been selected by analyzing phenotypic diversity, direct and indirect relationships among traits were identified, and four selection indices compared. Diversity was estimated using K-means clustering with the number of clusters determined by the Elbow method, and the relationship among traits was quantified by path analysis. Parametric and non-parametric indices were applied to selected genotypes using the magnitude of genotypic variance, heritability, genotypic coefficient of variance, and assigned economic weight as selection criteria. The variability among materials led to the formation of two non-overlapping clusters containing 40 and 154 genotypes. Strong to moderate correlations were found between traits with direct effect of the number of commercial fruit on the mass of commercial fruit. The Smith and Hazel index showed the greatest total gains for all criteria; however, concerning the biochemical traits, the Mulamba and Mock index showed the highest magnitudes of predicted gains. Overall, the K-means clustering, correlation analysis, and path analysis complement the use of selection indices, allowing for selection of genotypes with better balance among the assessed traits.

Strawberry (Fragaria x ananassa) stands out among small fruits as the most planted in Brazil, generating considerable income and employment. However, producers are dependent on cultivars originating from international breeding programs and imported seedlings. This entails high costs and plants poorly adapted to the edaphoclimatic conditions of Brazil. In addition, the consumer market demands superior organoleptic and nutritional qualities. We assessed the potential of 194 hybrids for production and physicochemical characteristics from a population of seedlings obtained from intraspecific crosses of the short-day cultivars Dover, Camarosa, Sweet Charlie, Oso Grande, Milsei Tudla, and Festival Florida and the day-neutral cultivar Aromas. The experimental design was an augmented block design that had as control treatments the cultivars Camarosa and Camino Real. Five production and nine physicochemical characteristics were assessed. The mean comparison was performed by the Dunnett test. Among the 14 characteristics analyzed, eight presented significance. The significant production characteristics were the number of commercial fruits, mass of commercial fruits, mass of non-commercial fruits, and the total mass ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 18 (2): gmr18156 E. Barth et al. 2 of fruits, with values of 45.03 fruits/plant, 13.17 g, 72.22 g/plant, and 720.77 g/plant, respectively. The physicochemical characteristics that varied significantly were soluble solids to titratable acidity ratio, pectin, ascorbic acid, and anthocyanin, which presented values of 10.23, 2.06 g total pectin/100 g pulp, 71.12 mg ascorbic acid/100 g pulp, and 39.51 mg cyanidin 3-glycoside/100 g pulp, respectively. The crosses that involved Camarosa and Aromas gave a greater number of hybrids with superior positive effects when compared to the controls in terms of production and physicochemical characteristics, respectively. Among the 194 hybrids, 30 were superior to the controls and were selected to advance in the breeding program.

Methods of multivariate analysis is a powerful approach to assist the initial stages of crops genetic improvement, particularly, because it allows many traits to be evaluated simultaneously. In this study, heat-tolerant genotypes have been selected by analyzing phenotypic diversity, direct and indirect relationships among traits were identified, and four selection indices compared. Diversity was estimated using K-means clustering with the number of clusters determined by the Elbow method, and the relationship among traits was quantified by path analysis. Parametric and non-parametric indices were applied to selected genotypes using the magnitude of genotypic variance, heritability, genotypic coefficient of variance, and assigned economic weight as selection criteria. The variability among materials led to the formation of two non-overlapping clusters containing 40 and 154 genotypes. Strong to moderate correlations were found between traits with direct effect of the number of commercial fruit (NCF) on the mass of commercial fruit (MCF). The Smith and Hazel index showed the greatest total gains for all criteria; however, concerning the biochemical traits, the Mulamba and Mock index showed the highest magnitudes of predicted gains. Overall, the K-means clustering, correlation analysis, and path analysis complement the use of selection indices, allowing for selection of genotypes with better balance among the assessed traits.