No abstract

Development of new cultivars and agronomic improvements are key factors of increasing in future grain yield in maize grown in environments affected by climate change. Assessment of value for cultivation and use (VCU) reflects the results of latest breeding efforts showing yield trends, whereby external environmental covariates were rarely used. This study aimed to analyze several environmental effects including stress degree days (SDD) on grain yields in Croatian VCU trials in three maturity groups using linear mixed model for the estimation of fixed and random effects. Best linear unbiased predictions (BLUPs) of location-year interaction showed no pattern among maturity groups. SDD showed mostly non-significant coefficients of regression on location BLUPs for yield. Analyzing location BLUPs, it was shown that the effect became consistently stronger with later maturity, either positive or negative. The effects of management might play more critical role in maize phenology and yield formation compared with climate change, at least in suboptimum growing conditions often found in Southeast Europe. To facilitate more robust predictions of the crop improvement, the traditional forked approach dealing with G×E by breeders and E×M by agronomists should be integrated to GxExM framework, to assess the full gradient of combinations forming the adaptation landscape.

SUMMARYAssessment of the value for cultivation and use (VCU) of a new cultivar, essential for its official registration, is done through a series of trials carried out over a 2–3-year period and across many locations. In a set of multi-environment VCU trials, evaluation of new genotypes can be a laborious task due to the presence of genotype by environment interactions, which can hide their true genetic value. In an attempt to reveal the true genetic value of new cultivars, a good starting point is investigation of the importance of various genetic and environmental sources of variation, which can be done by estimating relative magnitude of corresponding variance components within the mixed model framework.Genotype × location × year (G × L × Y) data set for seven crops taken from the 10-year period 2001–10 was used in the present study to estimate the variance components for main effects and their interactions in Croatian VCU trials. Depending on the crop, the most important and least important components were Y or LY, and L or GL, respectively. Genotypic effect was relatively small, ranging from 2·1 to 13·4% of the total variation. The current results are comparable with the relative sizes of the variance components obtained in studies from four- to sixfold larger countries, indicating that the environments within Croatia, if sufficiently widely sampled, can provide as extreme cultivar responses as a geographically more dispersed set of VCU trials. The gap range in different crops is much wider (30–60%) than in Western Europe (up to 30%), but it remained constant over the 10-year period.