Abstract
In multisite forest genetic experiments, the presence of genotype × environment interaction (GEI) is common. GEI may negatively affect the estimates of genetic variance and hamper selection decisions in tree breeding programs. Several measures exist to evaluate the stability of tested genotypes’ performance across environments with a choice of the method likely affecting breeders’ decisions. In this study, we evaluated variation in diameter and height growth performance in the progeny test established at 4 sites with 80 open-pollinated half-sib families of Scots pine. We found significant variation among examined progeny at age 10, reaching up to 31% for diameter and 20% for height depending on site, and significant GEI in both traits. We estimated contribution of each family to GEI using various methods and tools of GEI analysis—AMMI, GGE biplots, heterogeneity of regression coefficients (bi’s), the deviation mean squares from regression (s2di) and Kang’s yield-stability index (YSi). Despite the presence of the cross-over interaction, family ranks did not vary much among sites. The selections based on the phenotype, YSi and restricted bi corresponded well to each other leading to the expected response to selection up to 7.8% on diameter and 4.4% on height, whereas those based on the AMMI stability variance were different and lead to a slight loss in both traits. We discuss our results in the context of the usefulness of those measures of genotype stability for tree breeding programs and propose the procedure to follow for making selection decisions in forest experiments with GEI.
Highlights
Progress in tree breeding programs is made by evaluation of genetic worth of selections through progeny testing (White et al 2007)
The primary objective of this study was to evaluate variation in diameter and height growth performance in the progeny test established at 4 sites with 80 open-pollinated half-sib families of Scots pine (Pinus sylvestris L.), an important European coniferous species
We refer to them as to families or genotypes for clarity. This nomenclature is common in forestry applications of genotype × environment interaction (GEI) analysis, those half-sib families represent the mixtures of genotypes, in contrast to pure lines used in agriculture
Summary
Progress in tree breeding programs is made by evaluation of genetic worth of selections through progeny testing (White et al 2007). Estimation of genetic variance and genetic effects is commonly hampered in multisite experiments by the presence of genotype × environment interaction (GEI). These interactions arise from a differential response of genotypes to environmental factors and biotic and abiotic stresses (Kang 2002; Li et al 2017). Presence of GEI complicates breeding and deployment decisions, especially when important cross-overs occur in genotype rankings among sites. If the objective is to evaluate the performance of genotypes over many environments, it requires appropriate ways of dealing with genotype × site interaction
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