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This study explores the potential of Spanish germplasm for the development of hybrids adapted to southern Europe, a new region for hybrid barley (Hordeum vulgare). A set of 140 locally adapted, advanced breeding lines, developed in a Spanish public breeding program, were evaluated for their potential to widen the germplasm available for hybrid barley development. A subset of 24 lines was introduced into three‐way hybrid combinations and tested in a field trial network of four locations and 2 yr. The hybrid performance of the rest of the lines was estimated based on genomic prediction models. No three‐way hybrid exceeded the best check. We succeeded in identifying lines with high general combining ability, which could produce promising two‐way hybrids. Some were among those tested in the field, whereas others resulted from genomic predictions, validating the strategy followed of mining locally adapted breeding lines. Rachis brittleness detected in field trials revealed a low but detrimental effect of the presence of alternative brittle mutations in the hybrid combination. The success of hybrid breeding in southern Europe requires further investigation of the underlying heterotic patterns, and appropriate management of brittle genes through prebreeding, to widen the germplasm accessible for hybrid barley breeding. Core Ideas: A combination of field testing and genomic prediction successfully mined local germplasm for hybrid development.Reduced expression of local diversity and heterosis in three‐way hybrids hampered obtaining superior hybrids.High‐yielding, widely adapted, parental lines for the development of promising two‐way hybrids were identified.Field‐estimation of rachis fragility indicates risk of grain loss in hybrids with alternative brittle mutations.The success of hybrid barley in southern Europe requires managing flowering time and studying heterotic patterns. [ABSTRACT FROM AUTHOR]

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs. [ABSTRACT FROM AUTHOR]

Background: Fusarium head blight (FHB) and Septoria tritici blotch (STB) severely impair wheat production. With the aim to further elucidate the genetic architecture underlying FHB and STB resistance, we phenotyped 1604 European wheat hybrids and their 135 parental lines for FHB and STB disease severities and determined genotypes at 17,372 single-nucleotide polymorphic loci., Results: Cross-validated association mapping revealed the absence of large effect QTL for both traits. Genomic selection showed a three times higher prediction accuracy for FHB than STB disease severity for test sets largely unrelated to the training sets., Conclusions: Our findings suggest that the genetic architecture is less complex and, hence, can be more properly tackled to perform accurate prediction for FHB than STB disease severity. Consequently, FHB disease severity is an interesting model trait to fine-tune genomic selection models exploiting beyond relatedness also knowledge of the genetic architecture.

Abiotic stress tolerance in plants is pivotal to increase yield stability, but its genetic basis is still poorly understood. To gain insight into the genetic architecture of frost tolerance, this work evaluated a large mapping population of 1739 wheat (Triticum aestivum L.) lines and hybrids adapted to Central Europe in field trials in Germany and fingerprinted the lines with a 9000 single-nucleotide polymorphism array. Additive effects prevailed over dominance effects. A two-dimensional genome scan revealed the presence of epistatic effects. Genome-wide association mapping in combination with a robust cross-validation strategy identified one frost tolerance locus with a major effect located on chromosome 5B. This locus was not in linkage disequilibrium with the known frost loci Fr-B1 and Fr-B2. The use of the detected diagnostic markers on chromosome 5B, however, does not allow prediction of frost tolerance with high accuracy. Application of genome-wide selection approaches that take into account also loci with small effect sizes considerably improved prediction of the genetic variation of frost tolerance in wheat. The developed prediction model is valuable for improving frost tolerance because this trait displays a wide variation in occurrence across years and is therefore a difficult target for conventional phenotypic selection.