Cucumber mosaic virus infection of kava (Piper methysticum) and implications for cultural control of kava dieback disease

Cucumber mosaic virus (CMV) was found by reverse transcription polymerase chain reaction (RT-PCR) to be not fully systemic in naturally infected kava (Piper methysticum) plants in Fiji. Twenty-six of 48 samples (54%) from various tissues of three recently infected plants were CMV-positive compared with 7/51 samples (14%) from three long-term infections (plants affected by dieback for more than 1 year). The virus was also found to have a limited ability to move into newly formed stems. CMV was detected in only 2/23 samples taken from re-growth stems arising from known CMV infected/dieback affected plants. Mechanical inoculation experiments conducted in Fiji indicate that the known kava intercrop plants banana (Musa spp.), pineapple (Ananas comosus), peanut (Arachis hypogaea) and the common weed Mikania micrantha are potential hosts for a dieback-causing strain of CMV It was not possible to transmit the virus mechanically to the common kava intercrop plants taro (Colocasia esculenta), Xanthosoma sp., sweet potato (Ipomoea batatas), yam (Dioscorea alata), papaya (Carica papaya) or the weed Momordica charantia. Implications of the results of this research on a possible integrated disease management strategy are discussed.

A framework for optimising capital investment and operations in livestock logistics

Despite the longevity, scale and importance of northern Australia's beef industry, recent disruptions to external markets have demonstrated a degree of vulnerability to shocks in the supply chain. Matching the industry's long-evident resilience to climatic variability with resilience to changes in markets and supply chains requires careful planning. One component of this is how investments in infrastructure will need to be planned to facilitate adaptive responses to market changes. This paper provides an outline of a modelling framework that links strategic and operational dynamic models of logistics along the supply chain from the property to the abattoir or port. A novelty of the methodology is that it takes into account the high granularity of individual livestock transport vehicle movements and the ability to scale up to an almost complete view of logistics costs across the entire beef industry of northern Australia. The paper illustrates how the methodology could be used to examine the effects of changes in logistics infrastructure on efficiency and costs using examples from the states of Northern Territory, Western Australia and Queensland.