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Mixed model to multiple Harvest-Location trial applied to genomic prediction in Coffea canephora.

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P1168

Janudfy 9-13,2016 Soln Dlego, CA www.lntlpag.org

Mixed Model to Multiple Harvest-location Trial Applied to Genomic Prediction in Coffea canephora

Luis Felipe V.

Fe"ão

,

University of São Paulo (ESALQ/USP), PIRACICABA,

Sp,

Brazil

Romario G. Ferrão, Instituto Capixaba de Pesquisa,Assistência Técnica

e

Extensão Rural, Vitoria, Brazil

Maria A. G. Ferrão, Instituto Capixaba de Pesquisa

e

Assistência Técnica

e

Extensão Rural/ Embrapa

Café, Vitoria, Brazil

Aymbire Fonseca, Instituto Capixaba de Pesquisa

e

Assistência Técnica

e

Extensão Rural/ Embrapa Café, Vitoria, Brazil

Antônio Augusto Franco Garcia, University of São Paulo (ESALQ/USP), Piracicaba -

Sp,

Brazil

Genomic Selection (GS) has been studied in several crops with potential to increase the rates of genetic gain and reduce the length of breeding cycle. Despite the relevance, there is a modest number of reports applied to the genus Coffea. Nevertheless, the effective implementation depends on the ability to consider genomic

models that represent with adequate reliability the breeding scenario in which the specie are inserted. Coffee

experimentation, in general, is represented for evaluations in multiples sites and harvests (MET), in order to understand the interaction magnitude and predicting the performance of untested genotypes. Therefore, the main objective ofthis study was investigate GS models that accommodate MET modeling. A expansion of the traditional GBLUP was proposed in arder to accommodate the interactions in the GS model. Different scenarios that mimic the coffee breeding and models commonly used in the analysis were compared. In lerms of goodness of fit this approach showed the lowest AIC and BIC values and, consequently, the best goodness of fito The predictive capacity was measured by cross-validation and, in contrast with the GBLUP, lhe incorporation ofthe MET modeling showed higher predictive accuracy (on average 10-17% higher) and lower prediction errors. Ali the genomic analysis were performed using the Genotyping-by-sequencing (GBS)

approach, which showed a good potential to be used in coffee breeding programs. Thus, as conclusion, the

results achieved may be used as basis for additional studies into the Genus Coffea and expanded for other perennial crops, that have a similar experimentation designo

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