Genetic variability of Tomato spotted wilt virus in Australia and validation of real time RT-PCR for its detection in single and bulked leaf samples

The potential for large-scale use of a sensitive real time reverse transcription polymerase chain reaction (RT-PCR) assay was evaluated for the detection of Tomato spotted wilt virus (TSWV) in single and bulked leaf samples by comparing its sensitivity with that of DAS-ELISA. Using total RNA extracted with RNeasy® or leaf soak methods, real time RT-PCR detected TSWV in all infected samples collected from 16 horticultural crop species (including flowers, herbs and vegetables), two arable crop species, and four weed species by both assays. In samples in which DAS-ELISA had previously detected TSWV, real time RT-PCR was effective at detecting it in leaf tissues of all 22 plant species tested at a wide range of concentrations. Bulk samples required more robust and extensive extraction methods with real time RT-PCR, but it generally detected one infected sample in 1000 uninfected ones. By contrast, ELISA was less sensitive when used to test bulked samples, once detecting up to 1 infected in 800 samples with pepper but never detecting more than 1 infected in 200 samples in tomato and lettuce. It was also less reliable than real time RT-PCR when used to test samples from parts of the leaf where the virus concentration was low. The genetic variability among Australian isolates of TSWV was small. Direct sequencing of a 587 bp region of the nucleoprotein gene (S RNA) of 29 isolates from diverse crops and geographical locations yielded a maximum of only 4.3% nucleotide sequence difference. Phylogenetic analysis revealed no obvious groupings of isolates according to geographic origin or host species. TSWV isolates, that break TSWV resistance genes in tomato or pepper did not differ significantly in the N gene region studied, indicating that a different region of the virus genome is responsible for this trait.

Genetic diversity, aggressiveness and metalaxyl sensitivity of Pythium aphanidermatum populations infecting cucumber in Oman

Seventy three isolates of Pythium aphanidermatum obtained from cucumber from four different regions of Oman and 16 isolates of muskmelon from the Batinah region in Oman were characterized for aggressiveness, sensitivity to metalaxyl and genetic diversity using AFLP fingerprinting. Twenty isolates of P. aphanidermatum from diverse hosts from different countries were also included in the study. Most isolates from Oman were found to be aggressive on cucumber seedlings and all were highly sensitive to metalaxyl (EC50 < 0•80 µg mL−1). Isolates from cucumber and muskmelon were as aggressive as each other on both hosts (P > 0.05), which implies a lack of host specialization in P. aphanidermatum on these two hosts in Oman. AFLP analysis of all isolates using four primer-pair combinations resolved 152 bands, of which 61 (~40%) were polymorphic. Isolates of P. aphanidermatum from Oman and other countries exhibited high genetic similarity (mean = 94.1%) and produced 59 different AFLP profiles. Analysis of molecular variance indicated that most AFLP variation among populations of P. aphanidermatum in Oman was associated with geographical regions (FST = 0.118; P < 0.0001), not hosts (FST = -0.004; P = 0.4323). These data were supported by the high rate of recovery (24%) of identical phenotypes between cucumber and muskmelon fields in the same region as compared to the low recovery (10%) across regions in Oman, which suggests more frequent movement of Pythium inoculum among muskmelon and cucumber fields in the same region compared to movement across geographically separated regions. However, recovering clones among regions and different countries may imply circulation of Pythium inoculum via common sources in Oman and also intercontinental spread of isolates.

Genetic diversity, aggressiveness and metalaxyl sensitivity of Pythium spinosum infecting cucumber in Oman

A total of 24 isolates of Pythium spinosum from cucumber obtained from five regions in Oman were characterized for genetic diversity using amplified fragment length polymorphism (AFLP) fingerprinting and three isolates from the Netherlands, South Africa and Japan were included for comparison. Isolates from Oman were also characterized for aggressiveness on cucumber seedlings and sensitivity to metalaxyl. Identity of all isolates was confirmed using sequences of the internal transcribed spacer (ITS) region of the ribosomal DNA (rDNA), which showed more than 99% nucleotide similarity among all isolates. Using six primer-pair combinations, AFLP fingerprinting resolved 295 AFLP markers of which 193 were polymorphic among isolates from other countries and only six were polymorphic among isolates of P. spinosum from Oman. Seven different AFLP phenotypes of P. spinosum were recovered in Oman; two of them were found to contain over 79% of isolates and one was recovered from all regions in Oman. Phenotypes from Oman showed very high (?99%) levels of genetic similarity to each other compared to moderate (mean =53%) levels of genetic similarity with phenotypes from other countries. In addition, all isolates from Oman were found to be highly sensitive to metalaxyl and all were aggressive on cucumber seedlings at 25°C. The high genetic similarity among phenotypes of P. spinosum in Oman as well as recovering two major clones across regions may suggest that P. spinosum has been recently introduced in Oman via a common source.

Assessing the relationship between shire winter crop yield and seasonal variability of the MODIS NDVI and EVI images

Australian researchers have been developing robust yield estimation models, based mainly on the crop growth response to water availability during the crop season. However, knowledge of spatial distribution of yields within and across the production regions can be improved by the use of remote sensing techniques. Images of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, available since 1999, have the potential to contribute to crop yield estimation. The objective of this study was to analyse the relationship between winter crop yields and the spectral information available in MODIS vegetation index images at the shire level. The study was carried out in the Jondaryan and Pittsworth shires, Queensland , Australia . Five years (2000 to 2004) of 250m resolution, 16-day composite of MODIS Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images were used during the winter crop season (April to November). Seasonal variability of the profiles of the vegetation index images for each crop season using different regions of interest (cropping mask) were displayed and analysed. Correlation analysis between wheat and barley yield data and MODIS image values were also conducted. The results showed high seasonal variability in the NDVI and EVI profiles, and the EVI values were consistently lower than those of the NDVI. The highest image values were observed in 2003 (in contrast to 2004), and were associated with rainfall amount and distribution. The seasonal variability of the profiles was similar in both shires, with minimum values in June and maximum values at the end of August. NDVI and EVI images showed sensitivity to seasonal variability of the vegetation and exhibited good association (e.g. r = 0.84, r = 0.77) with winter crop yields.

The sensitivity of updated NIR PLS models for fruit sorting to initial parameter settings

Partial least squares regression models on NIR spectra are often optimised (for wavelength range, mathematical pretreatment and outlier elimination) in terms of calibration terms of validation performance with reference to totally independent populations.

Molecular characterisation, pathogenesis and fungicide sensitivity of Pythium spp. from table beet (Beta vulgaris var. vulgaris) grown in the Lockyer Valley, Queensland

Table beet production in the Lockyer Valley of south-eastern Queensland is known to be adversely affected by soilborne root disease from infection by Pythium spp. However, little is known regarding the species or genotypes that are the causal agents of both pre- and post-emergence damping off. Based on RFLP analysis with HhaI, HinfI and MboI of the PCR amplified ITS region DNA from soil and diseased plant samples, the majority of 130 Pythium isolates could be grouped into three genotypes, designated LVP A, LVP B and LVP C. These groups comprised 43, 41 and 7% of all isolates, respectively. Deoxyribonucleic acid sequence analysis of the ITS region indicated that LVP A was a strain of Pythium aphanidermatum, with greater than 99% similarity to the corresponding P. aphanidermatum sequences from the publicly accessible databases. The DNA sequences from LVP B and LVP C were most closely related to P. ultimum and P. dissotocum, respectively. Lower frequencies of other distinct isolates with unique RFLP patterns were also obtained with high levels of similarity (>97%) to P. heterothallicum, P. periplocum and genotypes of P. ultimum other than LVP B. Inoculation trials of 1- and 4-week-old beet seedlings indicated that compared with isolates of the LVP B genotype, a higher frequency of LVP A isolates caused disease. Isolates with the LVP A, LVP B and LVP C genotypes were highly sensitive to the fungicide Ridomil MZ, which suppressed radial growth on V8 agar between approximately four and thirty fold at 5 μg/mL metalaxyl and 40 μg/mL mancozeb, a concentration far lower than the recommended field application rate.

Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme.

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting tor energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.

Antibiotic Sensitivity Testing

Respiratory bacterial pathogens in pigs are currently treated with antibiotics. Intervet - Schering Plough markets an antibiotic called Nurflor (Florfenicol) targeting respiratory pathogens. This project tests the effectiveness of this antibiotic against a series of respiratory pathogens. 6 isolates will be tested per serovar/strain and the isolates will be from 4 different farms using MIC testing. The sensitivity of Florfenicol will be compared to sensitivity of the organisms to Tilmicosin and Amoxicillin. Development of resistance to certain antibiotics have been reported, so it is important to have alternative antibiotics available to treat the respiratory pathogens on farms.

The intrinsic plasticity of farm businesses and their resilience to change. An Australian example.

This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.

Interacting effects of vegetation, soils and management on the sensitivity of Australian savanna rangelands to climate change

There is an increasing need to understand what makes vegetation at some locations more sensitive to climate change than others. For savanna rangelands, this requires building knowledge of how forage production in different land types will respond to climate change, and identifying how location-specific land type characteristics, climate and land management control the magnitude and direction of its responses to change. Here, a simulation analysis is used to explore how forage production in 14 land types of the north-eastern Australian rangelands responds to three climate change scenarios of +3A degrees C, +17% rainfall; +2A degrees C, -7% rainfall; and +3A degrees C, -46% rainfall. Our results demonstrate that the controls on forage production responses are complex, with functional characteristics of land types interacting to determine the magnitude and direction of change. Forage production may increase by up to 60% or decrease by up to 90% in response to the extreme scenarios of change. The magnitude of these responses is dependent on whether forage production is water or nitrogen (N) limited, and how climate changes influence these limiting conditions. Forage production responds most to changes in temperature and moisture availability in land types that are water-limited, and shows the least amount of change when growth is restricted by N availability. The fertilisation effects of doubled atmospheric CO2 were found to offset declines in forage production under 2A degrees C warming and a 7% reduction in rainfall. However, rising tree densities and declining land condition are shown to reduce potential opportunities from increases in forage production and raise the sensitivity of pastures to climate-induced water stress. Knowledge of these interactions can be applied in engaging with stakeholders to identify adaptation options.

Implications of geometric plasticity for maximizing photosynthesis in branching corals

Reef-building corals are an example of plastic photosynthetic organisms that occupy environments of high spatiotemporal variations in incident irradiance. Many phototrophs use a range of photoacclimatory mechanisms to optimize light levels reaching the photosynthetic units within the cells. In this study, we set out to determine whether phenotypic plasticity in branching corals across light habitats optimizes potential light utilization and photosynthesis. In order to do this, we mapped incident light levels across coral surfaces in branching corals and measured the photosynthetic capacity across various within-colony surfaces. Based on the field data and modelled frequency distribution of within-colony surface light levels, our results show that branching corals are substantially self-shaded at both 5 and 18 m, and the modal light level for the within-colony surface is 50 mu mol photons m(-2) s(-1). Light profiles across different locations showed that the lowest attenuation at both depths was found on the inner surface of the outermost branches, while the most self-shading surface was on the bottom side of these branches. In contrast, vertically extended branches in the central part of the colony showed no differences between the sides of branches. The photosynthetic activity at these coral surfaces confirmed that the outermost branches had the greatest change in sun- and shade-adapted surfaces; the inner surfaces had a 50 % greater relative maximum electron transport rate compared to the outer side of the outermost branches. This was further confirmed by sensitivity analysis, showing that branch position was the most influential parameter in estimating whole-colony relative electron transport rate (rETR). As a whole, shallow colonies have double the photosynthetic capacity compared to deep colonies. In terms of phenotypic plasticity potentially optimizing photosynthetic capacity, we found that at 18 m, the present coral colony morphology increased the whole-colony rETR, while at 5 m, the colony morphology decreased potential light utilization and photosynthetic output. This result of potential energy acquisition being underutilized in shallow, highly lit waters due to the shallow type morphology present may represent a trade-off between optimizing light capture and reducing light damage, as this type morphology can perhaps decrease long-term costs of and effect of photoinhibition. This may be an important strategy as opposed to adopting a type morphology, which results in an overall higher energetic acquisition. Conversely, it could also be that maximizing light utilization and potential photosynthetic output is more important in low-light habitats for Acropora humilis.