Developing improved supply chains for temperate fruits in transitional Asian economies of Thailand and Vietnam.

Asia's increasing demand for both tropical and temperate fruit is projected to grow significantly. Compared with most developed countries, the production of temperate fruits (peach, nectarine, plum and apple) has expanded rapidly in China over the past 20 years. In contrast, current production of plums and peaches in neighbouring countries (Thailand and Vietnam) is very low but their fruit enters the market earlier. Thailand and Vietnam have enormous potential to satisfy a market window in the northern hemisphere period from March to May inclusive when there is little or no stone fruit on the Asian market. In Vietnam, fruit is harvested in an immature state to avoid disease and fruit fly problems and consequently lacks size and flavour. Approximately 30-40% of locally produced fruit in Vietnam does not reach market due to disease and poor handling during picking and transport. In Thailand, much of the infrastructure needed to transport, store, process and market temperate fruits successfully are now in place. However, there are currently no cool chain management or quality assurance systems to ensure a fresh product reaches the consumer with minimal deterioration. In Vietnam, growing stone fruit under the traditional system with little or minimal inputs, the farmer may receive between AUD3,000-5,000 per ha. In comparison, under higher input systems incorporating fertiliser, irrigation and pest and disease management, net returns can be increased seven-fold. Strengths and weaknesses of the current supply chains in these two countries are discussed.

Processing Tomato Production in the Burdekin: Opportunities and Risks for Growers

The research undertaken here was in response to a decision by a major food producer in about 2009 to consider establishing processing tomato production in northern Australia. This was in response to a lack of water availability in the Goulburn Valley region following the extensive drought that continued until 2011. The high price of water and the uncertainty that went with it was important in making the decision to look at sites within Queensland. This presented an opportunity to develop a tomato production model for the varieties used in the processing industry and to use this as a case study along with rice and cotton production. Following some unsuccessful early trials and difficulties associated with the Global Financial Crisis, large scale studies by the food producer were abandoned. This report uses the data that was collected prior to this decision and contrasts the use of crop modelling with simpler climatic analyses that can be undertaken to investigate the impact of climate change on production systems. Crop modelling can make a significant contribution to our understanding of the impacts of climate variability and climate change because it harnesses the detailed understanding of physiology of the crop in a way that statistical or other analytical approaches cannot do. There is a high overhead, but given that trials are being conducted for a wide range of crops for a variety of purposes, breeding, fertiliser trials etc., it would appear to be profitable to link researchers with modelling expertise with those undertaking field trials. There are few more cost-effective approaches than modelling that can provide a pathway to understanding future climates and their impact on food production.

Biology and Management of Psocids Infesting Stored Products

Previously regarded as minor nuisance pests, psocids belonging to the genus Liposcelis now pose a major problem for the effective protection of stored products worldwide. Here we examine the apparent biological and operational reasons behind this phenomenon and why conventional pest management seems to be failing. We investigate what is known about the biology, behavior, and population dynamics of major pest species to ascertain their strengths, and perhaps find weaknesses, as a basis for a rational pest management strategy. We outline the contribution of molecular techniques to clarifying species identification and understanding genetic diversity. We discuss progress in sampling and trapping and our comprehension of spatial distribution of these pests as a foundation for developing management strategies. The effectiveness of various chemical treatments and the availability and potential of nonchemical control methods are critically examined. Finally, we identify research gaps and suggest future directions for research.

Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.