Volker Hahn

BreedVision--a multi-sensor platform for non-destructive field-based phenotyping in plant breeding.

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies.

Detection of segregation distortion loci in triticale (x Triticosecale Wittmack) based on a high-density DArT marker consensus genetic linkage map

BackgroundTriticale is adapted to a wide range of abiotic stress conditions, is an important high-quality feed stock and produces similar grain yield but more biomass compared to other crops. Modern genomic approaches aimed at enhancing breeding progress in cereals require high-quality genetic linkage maps. Consensus maps are genetic maps that are created by a joint analysis of the data from several segregating populations and different approaches are available for their construction. The phenomenon that alleles at a locus deviate from the Mendelian expectation has been defined as segregation distortion. The study of segregation distortion is of particular interest in doubled haploid (DH) populations due to the selection pressure exerted on the plants during the process of their establishment.ResultsThe final consensus map, constructed out of six segregating populations derived from nine parental lines, incorporated 2555 DArT markers mapped to 2602 loci (1929 unique). The map spanned 2309.9 cM with an average number of 123.9 loci per chromosome and an average marker density of one unique locus every 1.2 cM. The R genome showed the highest marker coverage followed by the B genome and the A genome. In general, locus order was well maintained between the consensus linkage map and the component maps. However, we observed several groups of loci for which the colinearity was slightly uneven. Among the 2602 loci mapped on the consensus map, 886 showed distorted segregation in at least one of the individual mapping populations. In several DH populations derived by androgenesis, we found chromosomes (2B, 3B, 1R, 2R, 4R and 7R) containing regions where markers exhibited a distorted segregation pattern. In addition, we observed evidence for segregation distortion between pairs of loci caused either by a predominance of parental or recombinant genotypes.ConclusionsWe have constructed a reliable, high-density DArT marker consensus genetic linkage map as a basis for genomic approaches in triticale research and breeding, for example for multiple-line cross QTL mapping experiments. The results of our study exemplify the tremendous impact of different DH production techniques on allele frequencies and segregation distortion covering whole chromosomes.

Precision phenotyping of biomass accumulation in triticale reveals temporal genetic patterns of regulation.

To extend agricultural productivity by knowledge-based breeding and tailor varieties adapted to specific environmental conditions, it is imperative to improve our ability to assess the dynamic changes of the phenome of crops under field conditions. To this end, we have developed a precision phenotyping platform that combines various sensors for a non-invasive, high-throughput and high-dimensional phenotyping of small grain cereals. This platform yielded high prediction accuracies and heritabilities for biomass of triticale. Genetic variation for biomass accumulation was dissected with 647 doubled haploid lines derived from four families. Employing a genome-wide association mapping approach, two major quantitative trait loci (QTL) for biomass were identified and the genetic architecture of biomass accumulation was found to be characterized by dynamic temporal patterns. Our findings highlight the potential of precision phenotyping to assess the dynamic genetics of complex traits, especially those not amenable to traditional phenotyping.

QTL mapping of Sclerotinia midstalk-rot resistance in sunflower.

In many sunflower-growing regions of the world, Sclerotinia sclerotiorum (Lib.) de Bary is the major disease of sunflower (Helianthus annuus L.). In this study, we mapped and characterized quantitative trait loci (QTL) involved in resistance to S. sclerotiorum midstalk rot and two morphological traits. A total of 351 F3 families developed from a cross between a resistant inbred line from the germplasm pool NDBLOS and the susceptible line CM625 were assayed for their parental F2 genotype at 117 codominant simple sequence repeat markers. Disease resistance of the F3 families was screened under artificial infection in field experiments across two sowing times in 1999. For the three resistance traits (leaf lesion, stem lesion, and speed of fungal growth) and the two morphological traits, genotypic variances were highly significant. Heritabilities were moderate to high (h2=0.55–0.89). Genotypic correlations between resistance traits were highly significant (P<0.01) but moderate. QTL were detected for all three resistance traits, but estimated effects at most QTL were small. Simultaneously, they explained between 24.4% and 33.7% of the genotypic variance for resistance against S. sclerotiorum. Five of the 15 genomic regions carrying a QTL for either of the three resistance traits also carried a QTL for one of the two morphological traits. The prospects of marker-assisted selection (MAS) for resistance to S. sclerotiorum are limited due to the complex genetic architecture of the trait. MAS can be superior to classical phenotypic selection only with low marker costs and fast selection cycles.

BSTA: a targeted approach combines bulked segregant analysis with next- generation sequencing and de novo transcriptome assembly for SNP discovery in sunflower

BackgroundSunflower belongs to the largest plant family on earth, the genomically poorly explored Compositae. Downy mildew Plasmopara halstedii (Farlow) Berlese & de Toni is one of the major diseases of cultivated sunflower (Helianthus annuus L.). In the search for new sources of downy mildew resistance, the locus PlARG on linkage group 1 (LG1) originating from H. argophyllus is promising since it confers resistance against all known races of the pathogen. However, the mapping resolution in the PlARG region is hampered by significantly suppressed recombination and by limited availability of polymorphic markers. Here we examined a strategy developed for the enrichment of molecular markers linked to this specific genomic region. We combined bulked segregant analysis (BSA) with next-generation sequencing (NGS) and de novo assembly of the sunflower transcriptome for single nucleotide polymorphism (SNP) discovery in a sequence resource combining reads originating from two sunflower species, H. annuus and H. argophyllus.ResultsA computational pipeline developed for SNP calling and pattern detection identified 219 candidate genes. For a proof of concept, 42 resistance gene-like sequences were subjected to experimental SNP validation. Using a high-resolution mapping population, 12 SNP markers were mapped to LG1. We successfully verified candidate sequences either co-segregating with or closely flanking PlARG.ConclusionsThis study is the first successful example to improve bulked segregant analysis with de novo transcriptome assembly using next generation sequencing. The BSTA pipeline we developed provides a useful guide for similar studies in other non-model organisms. Our results demonstrate this method is an efficient way to enrich molecular markers and to identify candidate genes in a specific mapping interval.

Repeatability of a laboratory batch method to determine the specific biogas and methane yields

To evaluate the potential of a substrate to form biogas, it is essential to have a fast and accurate method to determine the specific biogas yield (SBY) and specific methane yield (SMY). The objectives of this study were to assess the repeatability of the Hohenheim Biogas Yield Test (HBT) and to assess the influence of sample withdrawal and preparation on the determined SBY and SMY. Samples of dried maize whole plant material, maize cob, and power fodder, with up to six different treatments for preparation, were analyzed for their SBY and SMY using a discontinuous fermentation assay. Further, chemical composition of the whole plant sample was examined and different calculation models were used to predict SMY. The HBT showed a strong repeatability and a high precision for SMY. Two of the tested chemical composition models showed a satisfactory performance compared to the mean of the measured methane values. Significant effects caused by different sample treatments could be observed.

Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping.

Midstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F3 families from cross CM625 (susceptible) × TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F3 families for stem lesion. For genotyping of the respective F2 plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between resistance traits were moderate to high. Three to four putative QTL were detected for each resistance trait explaining between 40.8% and 72.7% of the genotypic variance (

Mapping dynamic QTL for plant height in triticale

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