Maize (Zea mays L.) serves as model plant for heterosis research and is the crop where
hybrid breeding was pioneered. We analyzed genomic and phenotypic data of 1254 hybrids …

Genomic prediction is expected to considerably increase genetic gains by increasing
selection intensity and accelerating the breeding cycle. In this study, marker effects …

Key message The calibration data for genomic prediction should represent the full genetic
spectrum of a breeding program. Data heterogeneity is minimized by connecting data …

The genetic basis of heterosis for grain yield and its components was investigated at the
single-and two-locus levels using molecular markers with an immortalized F 2 (IF 2) …

The identification of superior hybrids is important for the success of a hybrid breeding
program. However, field evaluation of all possible crosses among inbred lines requires …

Identifying high performing hybrids is an essential part of every maize breeding program.
Genomic prediction of maize hybrid performance allows to identify promising hybrids, when …

Key message A new genomic model that incorporates genotype× environment interaction
gave increased prediction accuracy of untested hybrid response for traits such as percent …

This is the first large-scale experimental study on genome-based prediction of testcross
values in an advanced cycle breeding population of maize. The study comprised testcross …

Prediction of single-cross performance has been a major goal of plant breeders since the
beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising …

In hybrid breeding, the prediction of hybrid performance (HP) is extremely important as it is
difficult to evaluate inbred lines in numerous cross combinations. Recent developments …