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.

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.

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.