Background Genome-wide association studies (GWAS) based on linkage disequilibrium (LD) provide a promising tool for the detection and fine mapping of quantitative trait loci (QTL) underlying complex agronomic traits. In this study we explored the genetic basis of variation for the traits heading date, plant height, thousand grain weight, starch content and crude protein content in a diverse collection of 224 spring barleys of worldwide origin. The whole panel was genotyped with a customized oligonucleotide pool assay containing 1536 SNPs using Illumina's GoldenGate technology resulting in 957 successful SNPs covering all chromosomes. The morphological trait "row type" (two-rowed spike vs. six-rowed spike) was used to confirm the high level of selectivity and sensitivity of the approach. This study describes the detection of QTL for the above mentioned agronomic traits by GWAS. Results Population structure in the panel was investigated by various methods and six subgroups that are mainly based on their spike morphology and region of origin. We explored the patterns of linkage disequilibrium (LD) among the whole panel for all seven barley chromosomes. Average LD was observed to decay below a critical level (r2-value 0.2) within a map distance of 5-10 cM. Phenotypic variation within the panel was reasonably large for all the traits. The heritabilities calculated for each trait over multi-environment experiments ranged between 0.90-0.95. Different statistical models were tested to control spurious LD caused by population structure and to calculate the P-value of marker-trait associations. Using a mixed linear model with kinship for controlling spurious LD effects, we found a total of 171 significant marker trait associations, which delineate into 107 QTL regions. Across all traits these can be grouped into 57 novel QTL and 50 QTL that are congruent with previously mapped QTL positions. Conclusions Our results demonstrate that the described diverse barley panel can be efficiently used for GWAS of various quantitative traits, provided that population structure is appropriately taken into account. The observed significant marker trait associations provide a refined insight into the genetic architecture of important agronomic traits in barley. However, individual QTL account only for a small portion of phenotypic variation, which may be due to insufficient marker coverage and/or the elimination of rare alleles prior to analysis. The fact that the combined SNP effects fall short of explaining the complete phenotypic variance may support the hypothesis that the expression of a quantitative trait is caused by a large number of very small effects that escape detection. Notwithstanding these limitations, the integration of GWAS with biparental linkage mapping and an ever increasing body of genomic sequence information will facilitate the systematic isolation of agronomically important genes and subsequent analysis of their allelic diversity
Within the framework of climate change mitigation by sequestrating recalcitrant carbon in soil, biochar is considered as a promising soil amendment. Testing any such soil additives is vitally important, as they should not cause abiotic stress for plants due to chemical constituents they may contain. Thus, germination tests with spring barley (Hordeum vulgare) were conducted to assess phytotoxic effects of biochar, hydrochar and process‐water from hydrothermal carbonization (HTC) as soil amendments. Additionally, single‐component tests with substances found in process‐waters were carried out with cress (Lepidium sativum). While biochars generally had no effect on germination, hydrochars and process‐waters significantly inhibited germination. The dissolved organic carbon content predicted the germination‐inhibiting effects observed. Three compounds resulted in partial (guaiacol) or total (levulinic acid and glycolic acid) inhibition of cress seed germination, and three others (acetic acid, glycolaldehyde dimer and catechol) had a negative impact on growth. Phytotoxic substances in chars appeared to be mostly water soluble and volatile. Pre‐treatments of hydrochars and process‐waters (i.e. storage and washing) were able to reduce germination inhibition. While phytotoxic substances that are generated during HTC stay in the products, biochars from kiln carbonization of the same feedstocks had no negative effects on germination, likely because volatiles evaporate during the conversion. Our study highlights the importance of comprehensively testing carbonized products for their compatibility with agricultural and horticultural systems.
Laudis 550 is a mid-late malting spring barley variety, medium resistant to lodging and medium resistant to stem brackling. It is resistant to powdery mildew, medium resistant to brown rust, leaf blotch complex and scald. The variety reached 7.2 points of the malting quality index (to the registration date) and it is recommended by the Research Institute of Brewing and Malting, Plc for production of beer with the protected geographical indication Ceske pivo (Czech beer).
► We compared nine crop simulation models for spring barley at seven sites in Europe. ► Applying crop models with restricted calibration leads to high uncertainties. ► Multi-crop model mean yield estimates were in good agreement with observations. ► The degree of uncertainty for simulated grain yield of barley was similar to winter wheat. ► We need more suitable data enabling us to verify different processes in the models. In this study, the performance of nine widely used and accessible crop growth simulation models (APES-ACE, CROPSYST, DAISY, DSSAT-CERES, FASSET, HERMES, MONICA, STICS and WOFOST) was compared during 44 growing seasons of spring barley ( L.) at seven sites in Northern and Central Europe. The aims of this model comparison were to examine how different process-based crop models perform at multiple sites across Europe when applied with minimal information for model calibration of spring barley at field scale, whether individual models perform better than the multi-model mean, and what the uncertainty ranges are in simulated grain yields. The reasons for differences among the models and how results for barley compare to winter wheat are discussed. Regarding yield estimation, best performing based on the root mean square error (RMSE) were models HERMES, MONICA and WOFOST with lowest values of 1124, 1282 and 1325 (kg ha ), respectively. Applying the index of agreement (IA), models WOFOST, DAISY and HERMES scored best having highest values (0.632, 0.631 and 0.585, respectively). Most models systematically underestimated yields, whereby CROPSYST showed the highest deviation as indicated by the mean bias error (MBE) (−1159 kg ha ). While the wide range of simulated yields across all sites and years shows the high uncertainties in model estimates with only restricted calibration, mean predictions from the nine models agreed well with observations. Results of this paper also show that models that were more accurate in predicting phenology were not necessarily the ones better estimating grain yields. Total above-ground biomass estimates often did not follow the patterns of grain yield estimates and, thus, harvest indices were also different. Estimates of soil moisture dynamics varied greatly. In comparison, even though the growing cycle for winter wheat is several months longer than for spring barley, using RMSE and IA as indicators, models performed slightly, but not significantly, better in predicting wheat yields. Errors in reproducing crop phenology were similar, which in conjunction with the shorter growth cycle of barley has higher effects on accuracy in yield prediction.
Improving the efficiency of photosynthesis is a potential strategy for increasing crop yields in the future, but this is only possible if genetic variation exists for this attribute within crop germplasm resources. A key component of photosynthetic efficiency is the plant’s ability to intercept light. This study examined the extent of genetic variation, available within barley landraces from Europe, for parameters affecting light interception. Landraces varied in time spent between emergence and full canopy establishment, with those from Northern latitudes reaching canopy closure between 2 and 8 days faster than those from Southern latitudes. There was significant variation in leaf chlorophyll content between the landraces, but this was unrelated to site of origin. Landraces originating from locations with cooler temperature over the growing season held their leaves in a more planophile manner than those from warmer climates, resulting in a negative relationship between leaf angle and mean temperature at site of origin. We conclude that substantial genetic variation in key parameters affecting light interception have evolved among barley landraces in Europe that could be utilised in future breeding programmes to improve the efficiency of photosynthesis and increase crop yields.
In order to optimize relative seed frequency of intercropped pea ( L.) and spring barley ( L.), to achieve maximum relative yields and to gain a better understanding of interactions between yield formation and accumulation of nitrogen (N) and sulphur (S) under field conditions, field trials were conducted at several sites in Germany on long-term (>10 years) organically cultivated arable land in two years. These field trials investigated the effects of intercropping and the calculation of relative seed frequency in pea-barley mixtures to achieve maximum relative seed and shoot yields, as well as N and S accumulation. Under the given environmental conditions, a high degree of complementarity over a wide range of growing resources achieved relative total seed yields (RYT) of 1.35 and an increased N and S accumulation in the shoot of the mixture of 35% and 29% compared to the means of the pure stands of pea and spring barley. The increased complementarity of S resources (RYT S shoot = 1.29) was obviously a consequence of promoted vegetative growth caused by the increased complementarity of N resources of the cereal-legume mixture. To achieve the maximum seed yield and maximum N and S accumulation in substitutive mixtures of pea and spring barley, a relative seed frequency of 42%–88% pea seeds to 12%–58% spring barley seeds of their monocrop seeding rate has been calculated to be optimal. The availability of N in the soil of the respective environment, quantified by N accumulation in barley shoots, did not influence optimal relative seed frequency of the intercrop.