Application of a Bayesian ordinal animal model for the estimation of breeding values for the resistance to Monilinia fruticola (G.Winter) Honey in progenies of peach [Prunus persica (L.) Batsch]

• Published in: Breeding Science 2017, Vol.67(2), pp.110-122
• Main Authors: Fresnedo-Ramírez, Jonathan, Famula, Thomas R., Gradziel, Thomas M.
• Format: Article
• Language: English
• Subjects: Bayesian analysis; Brown rot; Crop improvement; Cultivars; Disease resistance; Environmental management; Fruit rot; Fruits; Genetic improvement; Genotype & phenotype; Gibbs sampler; Heritability; Infections; JAGS; logit function; mixed linear models; ordinal logistic regression; ordinal response; Pedigree; Phenotyping; Plant breeding; Research Paper
• ISSN: 1344-7610; 1347-3735
• DOI: 10.1270/jsbbs.16027

Fruit brown rot caused by Monilinia spp. is the most important fungal disease of stone fruits worldwide. Several phenotyping protocols to accurately characterize and evaluate brown rot infection have been proposed; however, the outcomes from those studies have not led to consistent advances in resistance breeding programs. Breeding for disease resistance is one of the most challenging objectives for crop improvement because disease expression is tetrahedral: it is simultaneously influenced by agent, host, environment, and human management. The present study presents a strategy based on Bayesian inference to analyze a peach breeding progeny for resistance to brown rot, evaluated using a polytomous ordinal scale. A pedigree containing two sources of resistance, one from peach and the other from almond, several commercial cultivars, and two segregating populations were analyzed to estimate the narrow-sense heritability (h2) and breeding values (EBVs) for brown rot resistance in progenies. Results show promise for genetic improvement of disease resistance and other traits characterized by strong environmental interactions.