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Estimation of Genetic Parameters of Biomass Production and Composition Traits in Miscanthus sinensis Using a Staggered-Start Design

Estimation of Genetic Parameters of Biomass Production and Composition Traits in Miscanthus sinensis Using a Staggered-Start Design
Abstract Traits for biomass production and composition make Miscanthus a promising bioenergy crop for different bioconversion routes. They need to be considered in miscanthus breeding programs as they are subjected to genetic and genetic x environment factors. The objective was to estimate the genetic parameters of an M. sinensis population grown during four years in two French locations. In each location, the experiment was established according to a staggered-start design in order to decompose the year effect into age and climate effects. Linear Mixed Models were used to estimate genetic variance, genotype x age, genotype x climate interaction variances and residual variances. Individual plant broad-sense heritability means ranged from 0.42 to 0.62 for biomass production traits, and were more heritable than biomass composition traits with means ranging from 0.26 to 0.47. Heritability increased through time for most of the biomass production and composition traits. Low genetic variance along with large genotype x age and genotype x climate interaction variances tended to decrease the heritability of biomass production traits for young plant ages. Most of the production traits showed large interaction variances for age and climate in both locations, while biomass composition traits highlighted large interaction variances due to climate in Orléans. The genetic and phenotypic correlations between biomass production and composition traits were moderate and positive, while hemicelluloses were negatively correlated with all traits. Efficient genetic progress is achievable for miscanthus breeding when plants get older. The joint improvement of biomass production and composition traits would help provide a better response of miscanthus to selection.
580, 570, Variance components, [SDV]Life Sciences [q-bio], Climate effect, 630, [SDV] Life Sciences [q-bio], Age effect, Genetic and phenotypic correlations, Broad-sense heritability
580, 570, Variance components, [SDV]Life Sciences [q-bio], Climate effect, 630, [SDV] Life Sciences [q-bio], Age effect, Genetic and phenotypic correlations, Broad-sense heritability
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