PRESTO Researcher

Shiori Yabe

Institute of Crop Science,
National Agriculture and Food Research Organization
Researcher

Outline

I develop an ecophysiological genomic prediction model for grain-filling of rice. First, a crop model of panicle structure and grain weight is bulit based on the field test with various cropping seasons and cutting off flag leaves. Second, a genomic prediction model is built to predict the parameters of the crop model based on the genome-wide marker genotype. The combination of crop modeling and modeling based on quantitative genetics enables us to predict the phenotype of selection candidates under various environmantal conditions. On the basis of the genomic prediction model, crossbreeding simulation reveals the suitable parents to obtain offsprings that performe well under a certain environment. The present study aims to realize the effective and efficient strategy of plant breeding.