Saaten Union (Germany)

ABSTRACTMachine learning methods were shown to improve the prediction accuracies of genomic prediction of resistance scores compared to methods like RR‐BLUP, which were originally designed for metric rather than ordinal response values. We conducted a cross‐validation study with 361 wheat genotypes evaluated for five fungal diseases. Our objective was to compare the prediction accuracy and the ability to identify the most resistant genotypes of 19 genomic prediction approaches. Each approach consisted of a different combination of prediction method (RR‐BLUP, an alternative method with heterogeneous marker variances, Bayesian generalized linear regression with an ordinal response, support vector machine, gradient boosting machine and random forest), predictor (single SNP markers, LD‐based haplotype blocks, 250 variables generated with an autoencoder and SNPs identified with incremental feature selection) and response value (untransformed and logit‐transformed resistance scores). In our dataset, RR‐BLUP was consistently among the methods with the largest prediction accuracies and the best abilities to identify resistant genotypes in four of five investigated traits. However, in P. triticina, using gradient boosting machine and random forest instead of RR‐BLUP increased the prediction accuracy from 0.64 to 0.71, indicating that machine learning methods may have an advantage over linear models in genomic prediction. We also found that even though there was a positive correlation between the prediction accuracy and Cohen's , a measure to judge how well the most resistant genotypes can be identified, the correlation is not perfect and a large value for the prediction accuracy does not necessarily translate into an equally large value.

Abstract Hybrid breeding of wheat (Triticum aestivum L.) is limited by its self‐pollinating nature. Past cross‐pollination improvements mostly focused on optimizing male traits. We tested the hybrid seed yield of 100 diverse elite lines treated with a chemical hybridization agent (CHA) and pollinated by non‐sterilized male plants in multi‐environmental field trials. Plant height and phenological traits of female plants were also assessed. In parallel, control experiments without CHA sterilization were conducted to measure per se yield of the tested material. Hybrid seed yield variation is of quantitative genetic nature, and, despite the large environmental influence, this trait has a strong genotypic component and is highly heritable (h2 = .77). The lack of correlation between hybrid seed yield and per se yield suggests a non‐shared genetic control. Phenological traits and their interactions are important factors explaining together ~1/3 of hybrid seed yield variation. In contrast to plant height and flowering traits, which are influenced by major genetic factors, no significant marker–trait associations were found for the hybrid seed yield, thus suggesting a highly polygenic genetic architecture and the need of larger populations to investigate female hybrid seed yield.

Pionero INIA es la primera variedad de trigo doble propósito liberado por el Programa Nacional de Trigo del INIA Carillanca. Es una variedad de invierno (Triticum aestivum L.) producto de la selección de germoplasma recibido de la Empresa Saaten Union Research de Francia. Mostró excelente adaptabilidad para siembras tempranas, en zonas de inviernos largos y primaveras húmedas. La altura promedio de planta adulta alcanza los 90 cm, siendo clasificado como una variedad de trigo enano a semi enano. El rendimiento promedio, en diferentes localidades y varios años de evaluación, fue significativamente superior al testigo Kumpa INIA, destacándose por su resistencia a enfermedades y tipo agronómico. Sus características de calidad molinera y de almidón permiten utilizarlo en la industria galletera, ganadera y acuícola.

Leaf rust and barley yellow dwarf, caused by Puccinia hordei Otth and barley yellow dwarf virus (BYDV)/cereal yellow dwarf virus (CYDV), are important diseases of barley (Hordeum vulgare L.) worldwide. Screening of spring barley landraces from Serbia led to the identification of the accession ‘MBR1012’ carrying resistance to the most widespread virulent leaf rust pathotypes in Europe, while a barley line carrying an introgression derived from H. bulbosum on chromosome 2HL was found to be highly tolerant to BYDV-PAV. In a population of 91 doubled haploid lines, derived from the cross MBR1012 (R) × Scarlett (S), the resistance gene against leaf rust was mapped in the telomeric region of chromosome 1HS by using simple sequence repeats (SSR). In parallel, the population was genotyped on the newly developed Illumina iSelect custom 9K BeadChipQ1, resulting in the identification of closer linked markers. To exploit BYDV tolerance, DH lines derived from the cross (Emir x H. bulbosum) x Emir have been analysed in three steps. In a first step, out of 221 DH lines, 27 plants carrying a recombination event in the H. bulbosum fragment were selected based on nine markers specific for chromosome 2HL. In a next step, selected recombinant plants were analysed on a custom-made Illumina BeadXpress Array (384 SNPs) and on the 9k iSelect BeadChip. Finally, artificially inoculated DH lines carrying introgressions of different sizes will be screened for BYDV virus tolerance by artificial inoculation in order to map this tolerance. Results obtained revealed the presence of novel resistance/tolerance genes and in parallel provide the tools for their efficient deployment in barley breeding

This article provides new evidence on the effects of monetary policy in the euro area. With the help of a time-varying coefficient vector autoregressive model we find that monetary policy shocks have had a greater impact on real output since the mid-1980s and that their transmission has become faster. Our findings indicate a change in the monetary transmission mechanism that can be explained by the changes in the European financial system over the last 20 years.

Genetic diversity of elite breeding material can be increased by introgression of exotic germplasm to ensure long-term selection response. The objective of our study was to develop and characterize the first two rye introgression libraries generated by marker-assisted backcrossing and demonstrate their potential application for improving the baking quality of rye. Starting from a cross between inbred line L2053-N (recurrent parent) and a heterozygous Iranian primitive population Altevogt 14160 (donor) two backcross (BC) and three selfing generations were performed to establish introgression libraries A and B. Amplified fragment length polymorphisms (AFLP markers) and simple sequences repeats (SSRs) were employed to select and characterize candidate introgression lines (pre-ILs) from BC(1) to BC2S3. The two introgression libraries comprise each 40 BC2S3 pre-ILs. For analyzing the phenotypic effects of the exotic donor chromosome segment (DCS) we evaluated the per se performance for pentosan and starch content in replicated field trials at each of four locations in 2005 and 2006. Introgression library A and B cover 74 and 59% of the total donor genome, respectively. The pre-ILs contained mostly two to four homozygous DCS, with a mean length of 12.9 cM (A) and 10.0 cM (B). We detected eight (A) and nine (B) pre-ILs with a significant (P<0.05) higher pentosan content and two pre-ILs (B) with a significant (P<0.05) higher starch content than the elite recurrent parent. Thus, our results indicate that exotic genetic resources in rye carry favorable alleles for baking quality traits, which can be exploited for improving the elite breeding material by marker-assisted selection (MAS). These introgression libraries can substantially foster rye breeding programs and provide a promising opportunity to proceed towards functional genomics.