Growth analysis and biomass partitioning of Cyperus iria in response to rice planting density and nitrogen rate

Cyperus iria is a weed of rice with widespread occurrence throughout the world. Because of concerns about excessive and injudicious use of herbicides, cultural weed management approaches that are safe and economical are needed. Developing such approaches will require a better understanding of weed biology and ecology, as well as of weed response to increases in crop density and nutrition. Knowledge of the effects of nitrogen (N) fertilizer on crop-weed competitive interactions could also help in the development of integrated weed management strategies. The present study was conducted in a screenhouse to determine the effects of rice planting density (0, 5, 10, and 20 plants pot−1) and N rate (0, 50, 100, and 150 kg ha−1) on the growth of C. iria. Tiller number per plant decreased by 73–88%, leaf number by 85–94%, leaf area by 85–98%, leaf biomass by 92–99%, and inflorescence biomass by 96–99% when weed plants were grown at 20 rice plants pot−1 (i.e., 400 plants m−2) compared with weed plants grown alone. All of these parameters increased when N rates were increased. On average, weed biomass increased by 118–389% and rice biomass by 121–275% with application of 50–150 kg N ha−1, compared to control. Addition of N favored weed biomass production relative to rice biomass. Increased N rates reduced the root-to-shoot weight ratio of C. iria. Rice interference reduced weed growth and biomass and completely suppressed C. iria when no N was applied at high planting densities (i.e., 20 plants pot−1). The weed showed phenotypic plasticity in response to N application, and the addition of N increased the competitive ability of the weed over rice at densities of 5 and 10 rice plants pot−1 compared with 20 plants pot−1. The results of the present study suggest that high rice density (i.e., 400 plants m−2) can help suppress C. iria growth even at high N rates (150 kg ha−1).

Transcriptome Analysis of Capsicum Chlorosis Virus-Induced Hypersensitive Resistance Response in Bell Capsicum

Background Capsicum chlorosis virus (CaCV) is an emerging pathogen of capsicum, tomato and peanut crops in Australia and South-East Asia. Commercial capsicum cultivars with CaCV resistance are not yet available, but CaCV resistance identified in Capsicum chinense is being introgressed into commercial Bell capsicum. However, our knowledge of the molecular mechanisms leading to the resistance response to CaCV infection is limited. Therefore, transcriptome and expression profiling data provide an important resource to better understand CaCV resistance mechanisms. Methodology/Principal Findings We assembled capsicum transcriptomes and analysed gene expression using Illumina HiSeq platform combined with a tag-based digital gene expression system. Total RNA extracted from CaCV/mock inoculated CaCV resistant (R) and susceptible (S) capsicum at the time point when R line showed a strong hypersensitive response to CaCV infection was used in transcriptome assembly. Gene expression profiles of R and S capsicum in CaCV- and buffer-inoculated conditions were compared. None of the genes were differentially expressed (DE) between R and S cultivars when mock-inoculated, while 2484 genes were DE when inoculated with CaCV. Functional classification revealed that the most highly up-regulated DE genes in R capsicum included pathogenesis-related genes, cell death-associated genes, genes associated with hormone-mediated signalling pathways and genes encoding enzymes involved in synthesis of defense-related secondary metabolites. We selected 15 genes to confirm DE expression levels by real-time quantitative PCR. Conclusion/Significance DE transcript profiling data provided comprehensive gene expression information to gain an understanding of the underlying CaCV resistance mechanisms. Further, we identified candidate CaCV resistance genes in the CaCV-resistant C. annuum x C. chinense breeding line. This knowledge will be useful in future for fine mapping of the CaCV resistance locus and potential genetic engineering of resistance into CaCV-susceptible crops.

Analysis of recreational fish catches – dealing with highly skewed distributions with many zeros

Data from surveys of recreational anglers fishing on three estuaries in eastern Australia reveal highly skewed distributions of catches with many zeros. Such data may be analysed using a two component approach involving a binary (zero/non-zero catch) response and the non-zero catches. A truncated regression model was effective in analysing the non-zero catches. Covariates were incorporated in the modelling, and their critical assessment has led to improved measures of fishing effort for this recreational fishery.

Antibody response against endogenous stages of an attenuated strain of Eimeria tenella

The application of attenuated vaccines for the prevention of chicken coccidiosis has increased exponentially in recent years. In Eimeria infections, protective immunity is thought to rely on a strong cell mediated response with antibodies supposedly playing a minor role. However, under certain conditions antibodies seem to be significant in protection. Furthermore, antibodies could be useful for monitoring natural exposure of flocks to Eimeria spp. and for monitoring the infectivity of live vaccines. Our objective was to investigate the chicken antibody response to the different parasite lifecycle stages following infection with an attenuated strain of Eimeria tenella. Western blotting analysis of parasite antigens prepared from the lining of caeca infected with the attenuated strain of E. tenella revealed two dominant antigens of 32 and 34 kDa, apparently associated with trophozoites and merozoites that were present at high concentrations between 84 and 132 h post-infection. When cryosections of caeca infected with E. tenella were probed with IgY purified from immune birds the most intense reaction was observed with the asexual stages. Western blotting analysis of proteins of purified sporozoites and third generation merozoites and absorption of stage-specific antibodies from sera suggested that a large proportion of antigens is shared by the two stages. The time-courses of the antibody response to sporozoite and merozoite antigens were similar but varied depending on the inoculation regime and the degree of oocyst recirculation.

Drosophila melanogaster mounts a unique immune response to the rhabdovirus Sigma virus

Rhabdoviruses are important pathogens of humans, livestock, and plants that are often vectored by insects. Rhabdovirus particles have a characteristic bullet shape with a lipid envelope and surface-exposed transmembrane glycoproteins. Sigma virus (SIGMAV) is a member of the Rhabdoviridae and is a naturally occurring disease agent of Drosophila melanogaster. The infection is maintained in Drosophila populations through vertical transmission via germ cells. We report here the nature of the Drosophila innate immune response to SIGMAV infection as revealed by quantitative reverse transcription-PCR analysis of differentially expressed genes identified by microarray analysis. We have also compared and contrasted the immune response of the host with respect to two nonenveloped viruses, Drosophila C virus (DCV) and Drosophila X virus (DXV). We determined that SIGMAV infection upregulates expression of the peptidoglycan receptor protein genes PGRP-SB1 and PGRP-SD and the antimicrobial peptide (AMP) genes Diptericin-A, Attacin-A, Attacin-B, Cecropin-A1, and Drosocin. SIGMAV infection did not induce PGRP-SA and the AMP genes Drosomycin-B, Metchnikowin, and Defensin that are upregulated in DCV and/or DXV infections. Expression levels of the Toll and Imd signaling cascade genes are not significantly altered by SIGMAV infection. These results highlight shared and unique aspects of the Drosophila immune response to the three viruses and may shed light on the nature of the interaction with the host and the evolution of these associations.

Scenario analysis of alternative vegetation management options on the greenhouse gas budget of two grazing businesses in north-eastern Australia

The emerging carbon economy will have a major impact on grazing businesses because of significant livestock methane and land-use change emissions. Livestock methane emissions alone account for similar to 11% of Australia's reported greenhouse gas emissions. Grazing businesses need to develop an understanding of their greenhouse gas impact and be able to assess the impact of alternative management options. This paper attempts to generate a greenhouse gas budget for two scenarios using a spread sheet model. The first scenario was based on one land-type '20-year-old brigalow regrowth' in the brigalow bioregion of southern-central Queensland. The 50 year analysis demonstrated the substantially different greenhouse gas outcomes and livestock carrying capacity for three alternative regrowth management options: retain regrowth (sequester 71.5 t carbon dioxide equivalents per hectare, CO2-e/ha), clear all regrowth (emit 42.8 t CO2-e/ha) and clear regrowth strips (emit 5.8 t CO2-e/ha). The second scenario was based on a 'remnant eucalypt savanna-woodland' land type in the Einasleigh Uplands bioregion of north Queensland. The four alternative vegetation management options were: retain current woodland structure (emit 7.4 t CO2-e/ha), allow woodland to thicken increasing tree basal area (sequester 20.7 t CO2-e/ha), thin trees less than 10 cm diameter (emit 8.9 t CO2-e/ha), and thin trees <20 cm diameter (emit 12.4 t CO2-e/ha). Significant assumptions were required to complete the budgets due to gaps in current knowledge on the response of woody vegetation, soil carbon and non-CO2 soil emissions to management options and land-type at the property scale. The analyses indicate that there is scope for grazing businesses to choose alternative management options to influence their greenhouse gas budget. However, a key assumption is that accumulation of carbon or avoidance of emissions somewhere on a grazing business (e.g. in woody vegetation or soil) will be recognised as an offset for emissions elsewhere in the business (e.g. livestock methane). This issue will be a challenge for livestock industries and policy makers to work through in the coming years.

Refined Global Analysis of Bemisia tabaci (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae) Mitochondrial Cytochrome Oxidase 1 to Identify Species Level Genetic Boundaries.

Identifying species boundaries within morphologically indistinguishable cryptic species complexes is often contentious. For the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae), the lack of a clear understanding about the genetic limits of the numerous genetic groups and biotypes so far identified has resulted in a lack of consistency in the application of the terms, the approaches use to apply them and in our understanding of what genetic structure within B. tabaci means. Our response has been to use mitochondrial gene cytochrome oxidase one to consider how to clearly and consistently define genetic separation. Using Bayesian phylogenetic analysis and analysis of sequence pairwise divergence we found a considerably higher to number of genetic groups than had been previously determined with two breaks in the distribution, one at 11% and another at 3.5%. At >11% divergence, 11 distinct groups were resolved, whereas at >3.5% divergence 24 groups were identified. Consensus sequences for each of these groups were determined and were shown to be useful in the correct assignment of sequences of unknown origin. The 3.5% divergence bound is consistent with species level separations in other insect taxa and Suggests that B. tabaci is it cryptic species composed of at least 24 distinct species. We further show that the placement of Bemesia atriplex (Froggatt) within the B. tabaci in, group adds further weight to the argument for species level separation within B. tabaci. This new analysis, which constructs consensus sequences and uses these its a standard against which unknown sequences call be compared, provides for the first time it consistent means of identifying the genetic hounds of each species with it high degree of certainty.

Analysis and Modelling of the Effects of Water Stress on Maize Growth and Yield in Dryland Conditions.

It is essential to provide experimental evidence and reliable predictions of the effects of water stress on crop production in the drier, less predictable environments. A field experiment undertaken in southeast Queensland, Australia with three water regimes (fully irrigated, rainfed and irrigated until late canopy expansion followed by rainfed) was used to compare effects of water stress on crop production in two maize (Zea mays L.) cultivars (Pioneer 34N43 and Pioneer 31H50). Water stress affected growth and yield more in Pioneer 34N43 than in Pioneer 31H50. A crop model APSIM-Maize, after having been calibrated for the two cultivars, was used to simulate maize growth and development under water stress. The predictions on leaf area index (LAI) dynamics, biomass growth and grain yield under rain fed and irrigated followed by rain fed treatments was reasonable, indicating that stress indices used by APSIM-Maize produced appropriate adjustments to crop growth and development in response to water stress. This study shows that Pioneer 31H50 is less sensitive to water stress and thus a preferred cultivar in dryland conditions, and that it is feasible to provide sound predictions and risk assessment for crop production in drier, more variable conditions using the APSIM-Maize model.

Are high-impact species predictable? An analysis of naturalised grasses in northern Australia

Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species.

Soil nitrogen—crop response calibration relationships and criteria for winter cereal crops grown in Australia

More than 1200 wheat and 120 barley experiments conducted in Australia to examine yield responses to applied nitrogen (N) fertiliser are contained in a national database of field crops nutrient research (BFDC National Database). The yield responses are accompanied by various pre-plant soil test data to quantify plant-available N and other indicators of soil fertility status or mineralisable N. A web application (BFDC Interrogator), developed to access the database, enables construction of calibrations between relative crop yield ((Y0/Ymax) × 100) and N soil test value. In this paper we report the critical soil test values for 90% RY (CV90) and the associated critical ranges (CR90, defined as the 70% confidence interval around that CV90) derived from analysis of various subsets of these winter cereal experiments. Experimental programs were conducted throughout Australia’s main grain-production regions in different eras, starting from the 1960s in Queensland through to Victoria during 2000s. Improved management practices adopted during the period were reflected in increasing potential yields with research era, increasing from an average Ymax of 2.2 t/ha in Queensland in the 1960s and 1970s, to 3.4 t/ha in South Australia (SA) in the 1980s, to 4.3 t/ha in New South Wales (NSW) in the 1990s, and 4.2 t/ha in Victoria in the 2000s. Various sampling depths (0.1–1.2 m) and methods of quantifying available N (nitrate-N or mineral-N) from pre-planting soil samples were used and provided useful guides to the need for supplementary N. The most regionally consistent relationships were established using nitrate-N (kg/ha) in the top 0.6 m of the soil profile, with regional and seasonal variation in CV90 largely accounted for through impacts on experimental Ymax. The CV90 for nitrate-N within the top 0.6 m of the soil profile for wheat crops increased from 36 to 110 kg nitrate-N/ha as Ymax increased over the range 1 to >5 t/ha. Apparent variation in CV90 with seasonal moisture availability was entirely consistent with impacts on experimental Ymax. Further analyses of wheat trials with available grain protein (~45% of all experiments) established that grain yield and not grain N content was the major driver of crop N demand and CV90. Subsets of data explored the impact of crop management practices such as crop rotation or fallow length on both pre-planting profile mineral-N and CV90. Analyses showed that while management practices influenced profile mineral-N at planting and the likelihood and size of yield response to applied N fertiliser, they had no significant impact on CV90. A level of risk is involved with the use of pre-plant testing to determine the need for supplementary N application in all Australian dryland systems. In southern and western regions, where crop performance is based almost entirely on in-crop rainfall, this risk is offset by the management opportunity to split N applications during crop growth in response to changing crop yield potential. In northern cropping systems, where stored soil moisture at sowing is indicative of minimum yield potential, erratic winter rainfall increases uncertainty about actual yield potential as well as reducing the opportunity for effective in-season applications.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

Genetic differentiation analysis for the identification of complementary parental pools for sorghum hybrid breeding in Ethiopia

Key message The potential for exploiting heterosis for sorghum hybrid production in Ethiopia with improved local adaptation and farmers preferences has been investigated and populations suitable for initial hybrid development have been identified. Abstract Hybrids in sorghum have demonstrated increased productivity and stability of performance in the developed world. In Ethiopia, the uptake of hybrid sorghum has been limited to date, primarily due to poor adaptation and absence of farmer’s preferred traits in existing hybrids. This study aimed to identify complementary parental pools to develop locally adapted hybrids, through an analysis of whole genome variability of 184 locally adapted genotypes and introduced hybrid parents (R and B). Genetic variability was assessed using genetic distance, model-based STRUCTURE analysis and pair-wise comparison of groups. We observed a high degree of genetic similarity between the Ethiopian improved inbred genotypes and a subset of landraces adapted to lowland agro-ecology with the introduced R lines. This coupled with the genetic differentiation from existing B lines, indicated that these locally adapted genotype groups are expected to have similar patterns of heterotic expression as observed between introduced R and B line pools. Additionally, the hybrids derived from these locally adapted genotypes will have the benefit of containing farmers preferred traits. The groups most divergent from introduced B lines were the Ethiopian landraces adapted to highland and intermediate agro-ecologies and a subset of lowland-adapted genotypes, indicating the potential for increased heterotic response of their hybrids. However, these groups were also differentiated from the R lines, and hence are different from the existing complementary heterotic pools. This suggests that although these groups could provide highly divergent parental pools, further research is required to investigate the extent of heterosis and their hybrid performance.

Genome-wide association analysis and differential expression analysis of resistance to Sclerotinia stem rot in Brassica napus

Brassica napus is one of the most important oil crops in the world, and stem rot caused by the fungus Sclerotinia sclerotiorum results in major losses in yield and quality. To elucidate resistance genes and pathogenesis-related genes, genome-wide association analysis of 347 accessions was performed using the Illumina 60K Brassica SNP (single nucleotide polymorphism) array. In addition, the detached stem inoculation assay was used to select five highly resistant (R) and susceptible (S) B. napus lines, 48 h postinoculation with S. sclerotiorum for transcriptome sequencing. We identified 17 significant associations for stem resistance on chromosomes A8 and C6, five of which were on A8 and 12 on C6. The SNPs identified on A8 were located in a 409-kb haplotype block, and those on C6 were consistent with previous QTL mapping efforts. Transcriptome analysis suggested that S. sclerotiorum infection activates the immune system, sulphur metabolism, especially glutathione (GSH) and glucosinolates in both R and S genotypes. Genes found to be specific to the R genotype related to the jasmonic acid pathway, lignin biosynthesis, defence response, signal transduction and encoding transcription factors. Twenty-four genes were identified in both the SNP-trait association and transcriptome sequencing analyses, including a tau class glutathione S-transferase (GSTU) gene cluster. This study provides useful insight into the molecular mechanisms underlying the plant's response to S. sclerotiorum.