The 2012 ASHS Annual Conference

The University of Florida strawberry (Fragaria x ananassa Duch.) breeding population has been continuously improved via recurrent selection since 1968.  However, there is a lack of information on genetic parameters which may inform breeding decisions.  Parameters were estimated in this population using 19 full-sib families from a 5 x 4 factorial mating design plus six additional biparental crosses and 13 parental genotypes.  During the 2010–11 season, four clonal replicates of each seedling and parental genotype were distributed within and among two field locations in west-central Florida.  Twelve commercially important traits were measured including fruit chemical traits (soluble solids content and titrateable acidity), other fruit and yield traits (average fruit weight, early and total marketable yields, proportion of total cull fruit, proportion of misshapen fruit, proportion water damaged fruit, and shape score), and vegetative traits (plant height and total runners).  Heritabilities, genotype by environment interactions and multiple correlations (phenotypic, genotypic, and genetic) were estimated using general mixed model analyses.  Narrow sense heritabilities varied from low to moderate (h² = 0.13 to 0.32) except for shape score (h² = 0.06) and average fruit weight (h² = 0.52).  Broad-sense heritabilities were larger (H² = 0.18 to 0.53).  Large amounts of non-additive variance for some traits show the potential for gains from clonal selection, such as for titrateable acidity (d² + i² = 0.23) and total runners (d² + i² = 0.20).  In contrast, no non-additive genetic variance was estimated for average fruit weight.  Genotype by environment interaction was minimal across the locations for all traits, suggesting that testing in one location may be sufficient.  Large genetic correlations were found for some traits, most notably between soluble solids content and early marketable yield (–0.68 ± 0.22).  This indicates that there may be a tradeoff between soluble solids concentration in the fruit and the total fruit load on the plant.  Genetic gains for this pair of traits based on a Monte Carlo simulation showed that moderate gains can be made in both traits using the appropriate index coefficients.