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Performing a thorough security risk assessment of an organisation has always been challenging, but with the increased reliance on outsourced and off-site third-party services, i.e., ``cloud services'', combined with internal (legacy) IT-infrastructure and -services, it has become a very difficult and time-consuming task. One of the traditional tools available to ease the burden of performing a security risk assessment and structure security analyses in general is attack trees, a tree-based formalism inspired by fault trees, a well-known formalism used in safety engineering. In this paper we study an extension of traditional attack trees, called attack-defense trees, in which not only the attacker's actions are modelled, but also the defensive actions taken by the attacked party. In this work we use the attack-defense tree as a goal an attacker wants to achieve, and separate the behaviour of the attacker and defender from the attack-defense-tree. We give a fully stochastic timed semantics for the behaviour of the attacker by introducing attacker profiles that choose actions probabilistically and execute these according to a probability density. Lastly, the stochastic semantics provides success probabilitites for individual actions. Furthermore, we show how to introduce costs of attacker actions. Finally, we show how to automatically encode it all with a network of timed automata, an encoding that enables us to apply state-of-the-art model checking tools and techniques to perform fully automated quantitative and qualitative analyses of the modelled system.

This chapter contains sections titled: Position of Barley Production and Breeding, Current Spring Barley Cultivars Combining High Quality and Disease Resistance, Current Winter Barley Varieties Combining High Yield and Malting Quality,Broad ‐ Based Virus ‐ Resistant Winter Barley Cultivars, Biotechnology ‐ Based and Marker ‐ Assisted Approaches: Evolution of Breeding Methods, Conclusions and Perspectives, Barley Production in Canada, Barley Production in the United States, Breeding Programs in Canada, Breeding Programs in the United States, Selecting Sources of Resistance to Abiotic and Biotic Stresses in Canada and the United States, Breeding Methods and Techniques in Canada and the United States, Collaboration between Breeding Programs in the United States and AMBA for Developing Malting Barley Cultivars, Cultivar Release in Canada, Cultivar Release and Intellectual Property Issues in the United States, History ‐ Barley Production in Australia, History ‐ Barley Improvement in Australia, Recent Progress in Australian Barley Improvement Programs, PBA, Australian Barley Breeding Objectives, Integration of Technologies in Australia, Near East, North Africa, East Africa, Latin America

Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930-932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30-40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping.

Grain samples from a combined intermediate and advanced stage barley breeding trial series, grown at two sites in two consecutive years were assessed for detailed grain quality and ruminant feed quality. The results indicated that there were significant genetic and environmental effects for “feed” traits as measured using grain hardness, acid detergent fibre (ADF), starch and in-sacco dry matter digestibility (ISDMD) assays. In addition, there was strong genotypic discrimination for the regressed feed performance traits, namely Net Energy (NE) and Average Daily Gain (ADG). There was considerable variation in genetic correlations for all traits based on variance from the cultivars used, sites or laboratory processing effects. There was a high level of heritability ranging from 89% to 88% for retention, 60% to 80% for protein and 56% to 68% for ADF. However, there were only low to moderate levels of heritability for the feed traits, with starch 30–39%, ISDMD 55–63%, ADF 56–68%, particle size 47–73%, 31–48% NE and ADG 44–51%. These results suggest that there were real differences in the feed performance of barleys and that selection for cattle feed quality is potentially a viable option for breeding programs.

In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS-Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding

In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding

The aim of the pedigree-based genome mapping project is to investigate and develop systems for implementing marker assisted selection to improve the efficiency of selection and increase the rate of genetic gain in breeding programs. Pedigree-based whole genome marker application provides a vehicle for incorporating marker technologies into applied breeding programs by bridging the gap between marker-trait association and marker implementation. We report on the development of protocols for implementation of pedigree-based whole genome marker analysis in breeding programs within the Australian northern winter cereals region. Examples of applications from the Queensland DPI&F wheat and barley breeding programs are provided, commenting on the use of microsatellites and other types of molecular markers for routine genomic analysis, the integration of genotypic, phenotypic and pedigree information for targeted wheat and barley lines, the genomic impacts of strong selection pressure in case study pedigrees, and directions for future pedigree-based marker development and analysis.

Net form of net blotch (NFNB), caused by Pyrenophora teres Drechs. f. teres Smedeg., is a serious disease problem for the barley industry in Australia and other parts of the world. Three doubled haploid barley populations, Alexis/Sloop, WI2875-1/Alexis, and Arapiles/Franklin, were used to identify genes conferring adult plant resistance to NFNB in field trials. Quantitative trait loci (QTLs) identified were specific for adult plant resistance because seedlings of the parental lines were susceptible to the NFNB isolates used in this study. QTLs were identified on chromosomes 2H, 3H, 4H, and 7H in both the Alexis/Sloop and WI2875-1/Alexis populations and on chromosomes 1H, 2H, and 7H in the Arapiles/Franklin population. Using QTLNetwork, epistatic interactions were identified between loci on chromosomes 3H and 6H in the Alexis/Sloop population, between 2H and 4H in the WI2875-1/Alexis population, and between 5H and 7H in the Arapiles/Franklin population. Comparisons with earlier studies of NFNB resistance indicate the pathotype-dependent nature of many resistance QTLs and the importance of establishing an international system of pathotype nomenclature and differential testing.

Barley (Hordeum vulgare) genotypes were sequenced for polymorphism in the hardness genes, these being the three hordoindoline (hin a, hin b1 and hin b2) genes. The variation in haplotype was determined by sequencing for single nucleotide polymorphisms (SNPs). Polymorphism between each gene was then compared to grain hardness (three methods), malt quality characteristics (hot water extract and friability) and cattle feed quality. Two haplotypes were found in a set of forty barley genotypes. For hin a, two alleles were present, namely hin a1 and hin a2. However, there was no specific hin a allele that was associated with grain hardness, malt and feed quality. Barley has two hin b genes, namely hin b1 and hin b2, and the genotypes tested here had one of two alleles for each gene. However, there were no obvious effects on hardness or quality from either of these hin b alleles. Unlike wheat, where a clear relationship has been demonstrated between a number of SNPs in the wheat hardness genes and quality (soft or hard wheat), there was no such relationship for barley. Despite the wide range in hardness, malt and feed quality, there were only two haplotypes for each of the hin a, hin b1 and hin b2 genes and there was no clear relationship between grain hardness, malt or feed quality. The genotypes used in this study demonstrated that there was a low level of polymorphism in hardness genes in current commercial varieties as well as breeding lines and these polymorphisms had no impact on quality.

Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in. component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding sch

In this study, 120–144 commercial varieties and breeding lines were assessed for grain size attributes including plump grain (>2.8 mm) and retention (>2.5 mm+>2.8 mm). Grain samples were produced from replicated trials at 25 sites across four years. Climatic conditions varied between years as well as between sites. Several of the trial sites were irrigated while the remaining were produced under dryland conditions. A number of the dryland sites suffered severe drought stress. The grain size data was analysed for genetic (G), environmental (E) and genotype by environment (G×E) interactions. All analyses included maturity as a covariate. The genetic effect on grain size was greater than environmental or maturity effects despite some sites suffering terminal moisture stress. The model was used to calculate heritability values for each site used in the study. These values ranged from 89 to 98% for plump grain and 88 to 96% for retention. The results demonstrated that removing the sources of non-heritable variation, such as maturity and field effects, can improve genetic estimates of the retention and plump grain fractions. By partitioning all variance components, and thereby having more robust estimates of genetic differences, plant breeders can have greater confidence in selecting barley genotypes which maintain large, stable grain size across a range of environments.

Objective: We have tested the relapse-preventive effect of citalopram when compared with placebo in 282 patients with Seasonal Affective Disorder (SAD) responding to 1 week of light therapy. Method: The response rate to 1-week light therapy and relapse during the continuation phase of 15 weeks were assessed by use of the Hamilton Depression Rating Scale (HAM-D17), the six-item subscale (HAM-D6), the Melancholia Scale (MES), and the combined HAM-D/ SIGH-SAD. Results: The response rate to light therapy was 62.5% on the HAM-D17 and the HAM-D6, 56.1% on the HAM-D/SIGH-SAD, 52.8% on the MES. In the continuation phase, citalopram was found superior to placebo on all scales, but the difference was only of statistical significance on the HAM-D6 and the MES. Mean citalopram dose was 26.3 mg. Conclusion: Light therapy was found to have and early onset of action. On the HAM-D6 and the MES citalopram significantly reduced the relapse rate in the continuation phase.

Six doubled haploid barley populations (Alexis × Sloop, Chebec × Harrington, Arapiles × Franklin, Patty × Tallon, Tallon × Kaputar, and Sloop × Halcyon) and a recombinant inbred population (WI2875-1 × Alexis) were assessed for response to selected pathotypes of the barley leaf rust pathogen, Puccinia hordei, at the seedling growth stage. Resistance genes were postulated for the parents of each population based on their reaction to selected pathotypes. In most cases, the resistance genes postulated in the cultivars were validated by QTL mapping analyses of the progeny populations. The resistance genes detected and mapped were Rph2, Rph3, Rph4, Rph12, and Rph19. The chromosomal locations of these 5 genes were consistent with previous reports, with Rph2 mapping near to the centromere on the short arm of chromosome 5H, Rph4 mapping to chromosome 1H, Rph12 mapping to the long arm of chromosome 5H, and Rph3 and Rph19 mapping ~30 cM apart on the long arm of chromosome 7H.

A doubled haploid population of 120 individuals was produced from the parents Chebec, an Australian 2-row barley of feed quality with resistance to the cereal cyst nematode, and Harrington, a 2-rowed, Canadian variety of premium malting quality. This paper describes 18 field and laboratory experiments conducted with the population and summarises the traits mapped and analysed. The genomic location of 25 traits and genes is described and marker–trait associations for 5 traits (malt extract, diastatic power, resistance to cereal cyst nematode, early flowering, resistance to pre-harvest sprouting) important to Australian efforts to improve malting barley varieties have been used in practical breeding programs. Detailed maps for these populations are shown in this paper, while a consensus map incorporating these maps and further experiments on the populations are described elsewhere in this issue.

Barley stripe rust (BSR), caused by Puccinia striiformis f. sp. hordei, has been a major disease problem to the barley industry worldwide that has not, to date, been detected in Australia. This paper describes the mapping of stripe rust resistance genes in Tallon/Kaputar (TK) and Arapiles/Franklin (AF) populations. The paper also reports on the usefulness of markers associated with alternative sources of resistance previously identified in the varieties Orca and Shyri in the USA. Stripe rust screening was conducted at the adult plant stage in Toluca, Mexico, for 2 years. Two major quantitative trait loci (QTLs) were found on chromosomes 2H and 5H in both populations. One region on chromosome 5H was highly significantly associated with resistance to stripe rust (R2 = 68% and 34% in TK and AF, respectively). The QTL on chromosome 2H accounted for 36% of the variation in TK and 10% of the variation in the AF population. These associations were consistent over both years. Further work will involve screening for additional markers in the target regions to identify polymorphism that can be used to select for multiple resistances in the absence of the pathogen.

A genetic map of barley with 224 AFLP and 39 simple sequence repeat (SSR) markers was constructed using a doubled haploid (DH) mapping population from a cross between the varieties Tallon and Kaputar. Linkage groups were assigned to individual barley chromosomes using the published map locations of the SSR markers as reference points. This genetic map was used to identify markers with linkage to agronomic, disease, and quality traits in barley. The population, which comprised 65 lines, was tested in a range of environments across Australia. Quantitative trait loci (QTLs) analyses were performed using software packages MapMaker, MapManager, and Qgene. Significant associations with markers were found for several traits. Grain yield showed significant association with regions on chromosomes 2H, 3H, and 5H over a range of sites throughout Australia. Regions on chromosomes 2H and 3H explained 30% and 26% of variation in lodging, respectively. Among quality traits, diastatic power was associated with regions on chromosomes 1H, 2H, and 5H (R2 = 37%). Hot water extract was associated with a region on chromosome 6H and a marker not assigned to a chromosome (R2 = 45%). There were also environment-specific QTLs for the traits analysed. The markers identified here present an opportunity for marker assisted selection of lines for these traits in barley breeding programs.

Identification and deployment of disease resistance genes are key objectives of Australian barley breeding programs. Two doubled haploid (DH) populations derived from Tallon × Kaputar (TK) and VB9524 × ND11231 (VN) crosses were used to identify markers for net type net blotch (NTNB) (Pyrenophora teres f. teres). The maps included 263 and 250 markers for TK and VN populations, respectively. The TK population was screened with 5 pathotypes and the VN population with 1 pathotype of NTNB as seedlings in the glasshouse. In addition, the TK population was subjected to natural infection in the field at Hermitage Research Station, Qld. Analyses of the markers were performed using the software packages MapManager and Qgene. One region on chromosome 6H was strongly associated with resistance to NTNB in both populations (R2 = 83% for TK and 66% for VN). In the TK population, 2 more quantitative trait loci (QTLs) were identified on chromosomes 2H and 3H, with R2 values of 30% and 31%, respectively. These associations were consistent over all pathotypes studied during the seedling stage. The same QTL on chromosome 6H was also found to be highly significantly associated (R2 = 65%) with the adult plant (field) response in the TK population. There are several very closely linked markers showing strong associations in these regions. Association of the 4 markers on chromosome 6H QTL with resistance to the NTNB has been validated in 2 other DH populations derived from barley crosses Pompadour × Stirling and WPG8412 × Stirling. These markers present an opportunity for marker assisted selection of lines resistant to NTNB in barley breeding programs.

A doubled haploid population of 120 individuals was produced from the parents Chebec, an Australian 2-row barley of feed quality with resistance to the cereal cyst nematode, and Harrington, a 2-rowed, Canadian variety of premium malting quality. This paper describes 18 field and laboratory experiments conducted with the population and summarises the traits mapped and analysed. The genomic location of 25 traits and genes is described and marker–trait associations for 5 traits (malt extract, diastatic power, resistance to cereal cyst nematode, early flowering, resistance to pre-harvest sprouting) important to Australian efforts to improve malting barley varieties have been used in practical breeding programs. Detailed maps for these populations are shown in this paper, while a consensus map incorporating these maps and further experiments on the populations are described elsewhere in this issue.

Two populations between the German malting variety Alexis and the Australian malting variety Sloop were constructed, mapped, phenotyped, and subjected to quantitative trait loci analysis. One population consisted of 153 F4-derived recombinant inbred lines and the other of 111 doubled haploid lines. This paper describes 18 field and laboratory experiments conducted with the populations and summarises the traits mapped and analysed. The genetic basis of 5 traits (malt extract, resistance to leaf rust, resistance to powdery mildew, early flowering, plant stature) important to Australian efforts to improve malting barley varieties was elucidated. Detailed maps for these populations are shown in this paper, while a consensus map incorporating these maps and further experiments on the populations are described elsewhere in this issue.

A dihaploid (DH) mapping population was developed between Tallon and Kaputar varieties and used to construct a genetic linkage map of barley. Map construction is described in an accompanying paper (Cakir et al. these proceedings). This genetic map with 195 amplified fragment length polymorphism (AFLP) and 25 simple sequence repeat (SSR) markers was used to identify markers that are linked to agronomic, disease and quality traits in barley. The population, which included 65 lines, were tested across Australia in different environments and a number of traits were measured. The marker data set and phenotypic data were used to identify quantitative trait loci (QTLs) associated with the traits. Significant associations were found for a number of traits. Notably grain yield and net blotch resistance showed significant associations on chromosomes 5H and 6H, respectively. Markers located on these regions present an opportunity for marker assisted selection (MAS) for these traits in barley breeding programs.

Genetic map construction is an important step towards identifying genes that are responsible for the expression of traits. To achieve this goal a dihaploid mapping population was constructed between the barley parents Tallon and Kaputar. Parents were first screened with amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers. A total of 211 AFLP markers and 33 SSR markers were identified as polymorphic between the parents. Then all of the polymorphic AFLP markers and 24 of the SSR markers were assayed for the whole population. Linkage analysis of the markers revealed seven large and thirteen smaller linkage groups. The seven large linkage groups are assigned to individual barley chromosomes with reference to the published map locations of the SSR markers. The total map covered 1300 cM, which is about the expected size of the barley genome.

The use of molecular markers in plant breeding is well underway. Though they are expensive to develop, molecular markers open the possibility of reliable and rapid selection for a wide range of traits. In many cases marker-based selection will eventually be more efficient and cost-effective than evaluation of plants in the field. Marker-based selection has particular potential for the genetic improvement of traits that must be painstakingly evaluated after harvest, such as malting quality in barley. The objective of this study is to generate and identify molecular markers to be used in marker-assisted breeding for disease resistance, quality, and agronomic traits in barley. Molecular markers such as RFLPs (Restriction Fragment Length Polymorphisms), AFLPs (Amplified Fragment Length Polymorphisms), and SSRs (Simple Sequence Repeats) are being used. Major traits of interest are scald resistance, net blotch, stripe rust, basic vegetative period, plant height, time to maturity, grain size, malt extract, alpha amylase activity and grain yield. This process requires the construction of a mapping population with the parents that differ for the desired traits and fingerprinting of the progeny lines with the markers. Depending on the size of the population and the genetics of a trait a full population analysis or a bulk segregant analysis will be used, with the DNA markers, to identify significant chromosomal regions so called 'Quantitative Trait Loci'.