Clayton Robert Forknall

Context: Many wheat producers are increasing the biomass of cereal stubble retained after harvest through the adoption of stripper front harvesters, which result in taller standing stubble. Aims: We investigated whether taller stubble affects the survival and dispersal of Fusarium pseudograminearum (Fp), the causative agent of Fusarium crown rot (FCR). Methods: Field experiments at two sites in northern New South Wales were run for 3 years to investigate whether taller cereal stubble in Year 1 facilitated additional Fp colonisation, and subsequent effects on dispersal of Fp inoculum from chickpea harvest in Year 2 and FCR infection and expression in cereal crops in Year 3. Culturing and quantitative polymerase chain reaction (qPCR) methods assessed Fp colonisation and future disease risks. Key results: In taller cereal stubble, Fp colonised an additional 91–92% of the stubble length in the 6 months post-harvest and persisted at higher levels for at least 1 year than did the shorter cereal stubble. Cutting cereal stubble short (in Year 1) therefore successfully restricted further colonisation by Fp. Significant displacement of Fp in the crown 6 months post-harvest resulted in significant decreases in Fp DNA overall; however, long-term survival of Fp was observed 10–20 cm above the crown. Conclusions: Different residue management scenarios did not increase FCR risk for Year 3, likely owing to high inoculum levels across all treatments and unseasonably wet conditions in Years 2–3. Implications: We provide important field-validation of Fp colonisation in standing cereal stubble and discuss implications for FCR management across regions and seasons.

The size and complexity of datasets resulting from comparative research experiments in the agricultural domain is constantly increasing. Often the number of variables measured in an experiment exceeds the number of experimental units composing the experiment. When there is a necessity to model the covariance relationships that exist between variables in these experiments, estimation difficulties can arise due to the resulting covariance structure being of reduced rank. A statistical method, based in a linear mixed model framework, is presented for the analysis of designed experiments where datasets are characterised by a greater number of variables than experimental units, and for which the modelling of complex covariance structures between variables is desired. Aided by a clustering algorithm, the method enables the estimation of covariance through the introduction of covariance clusters as random effects into the modelling framework, providing an extension of the traditional variance components model for building covariance structures. The method was applied to a multi-phase mass spectrometry-based proteomics experiment, with the aim of exploring changes in the proteome of barley grain over time during the malting process. The modelling approach provides a new linear mixed model-based method for the estimation of covariance structures between variables measured from designed experiments, when there are a small number of experimental units, or observations, informing covariance parameter estimates.

The root lesion nematode (RLN) species Pratylenchus thornei and P. neglectus are widely distributed within cropping regions of Australia and have been shown to limit grain production. Field experiments conducted to compare the performance of cultivars in the presence of RLNs investigate management options for growers by identifying cultivars with resistance, by limiting nematode reproduction, and tolerance, by yielding well in the presence of nematodes. A novel experimental design approach for RLN experiments is proposed where the observed RLN density, measured prior to sowing, is used to condition the randomization of cultivars to field plots. This approach ensured that all cultivars were exposed to consistent ranges of RLN in order to derive valid assessments of relative cultivar tolerance and resistance. Using data from a field experiment designed using the conditioned randomization approach and conducted in Formartin, Australia, the analysis of tolerance and resistance was undertaken in a linear mixed model framework. Yield response curves were derived using a random regression approach and curves modeling change in RLN densities between sowing and harvest were derived using splines to account for nonlinearity. Groups of cultivars sharing similar resistance levels could be identified. A comparison of slopes of yield response curves of cultivars belonging to the same resistance class identified differing tolerance levels for cultivars with equivalent exposures to both presowing and postharvest RLN densities. As such, the proposed design and analysis approach allowed tolerance to be assessed independently of resistance.

The root lesion nematode Pratylenchus thornei causes economic losses in wheat and barley internationally through both reduced grain yield and grain quality. This study investigated the relationships between the presowing P. thornei density and grain yield and the postharvest nematode densities. Four field experiments were conducted at the same site between 2010 and 2014. A range of presowing P. thornei densities was established in the first year by growing three cereal cultivars that ranged from resistant to susceptible. In the following year, plots were sown with the five same cereal cultivars. A linear relationship was observed between the natural log of the presowing P. thornei density and grain yield across all seasons. The results showed that grain yield losses varied between cultivars and seasons. The importance of season was significant, with this study conducted over several seasons, and it highlighted the variability in yield losses between seasons, which will need further investigation. The greatest yield losses observed were 25 to 28% when the maximum presowing P. thornei densities ranged between 150 and 250 P. thornei g of soil⁻¹. An analysis of the relationship between the presowing and postharvest nematode densities revealed that increased presowing nematode densities resulted in decreased multiplication rates in all seasons and in all cultivars. Nematode multiplication rates also varied between seasons. These results explain why it is difficult to predict nematode levels based on cropping history, and additionally, they highlight the importance of growing resistant cultivars to maintain low levels of P. thornei to minimize risk of yield losses.

The disease crown rot, caused predominantly by the fungal pathogen Fusarium pseudograminearum, is a major disease of winter cereals in many regions of the world, including Australia. A methodology is proposed, using response curves, to robustly estimate the relationship between grain yield and increasing crown rot pathogen burdens. Using data from a field experiment conducted in northern New South Wales, Australia in 2016, response curves were derived for five commercial wheat cultivars exposed to six increasing rates of crown rot inoculum, where the rates served to establish a range of crown rot pathogen burdens. In this way, the response curve methodology is fundamentally different from alternate approaches that rely on genetic or environmental variation to establish a range in pathogen burdens over which yield loss relationships are estimated. By manipulating only the rates of crown rot inoculum and, thus, pathogen burden directly, the number of additional confounding factors and interactions are minimized, enabling the robust estimation of the rate of change in yield due to increasing crown rot pathogen burdens for each cultivar. The methodology revealed variation in the rate of change in yield between cultivars, along with the extent of crown rot symptoms expressed by the cultivars. Variation in the rate of change in yield between cultivars provides definitive evidence of differences in the tolerance of commercial Australian wheat cultivars to crown rot caused by F. pseudograminearum, while variation in the extent of crown rot symptoms signifies differences in the resistance of the cultivars to this disease. The response curve methodology also revealed variation in how the different mechanisms of tolerance and resistance act to limit yield losses due to crown rot for different cultivars.