Location: Subtropical Plant Pathology Research2012 Annual Report
1a. Objectives (from AD-416):
1. Develop spatial and temporal models and assessment of disease control/mitigation strategies via incorporation of variable meteorological conditions. 2. Utilize these models to test alternative disease control strategies and to conduct scenario testing.
1b. Approach (from AD-416):
1. Collect, analyze, and interpret initial HLB epidemic data. 2. Conduct field trials to determine the efficacy of rouging, insect control, and treatment combinations. 3. Conduct field trials to determine the efficacy of Murraya paniculata as a trap plant. 4. Develop preliminary spatial and temporal models and preliminary assessment of disease control/mitigation strategies. 5. Initiate development of stochastic models to estimate the temporal increase and spatial spread of HLB that are plastic and adaptable to other pest and pathogen systems. 6. Incorporate model parameters that allow the use of variable meteorological conditions, for instance in local conditions in citrus growing regions in various citrus producing states. 7. Utilize these models and statistical methods to test alternative disease control strategies via stochastic simulation and select those strategies which maximize the probability of success prior to test/deployment of control methods in the field. 8. Conduct scenario testing and the ability to estimate citriculture economic parameters such as estimates of fiscal and manpower requirements for yearly planning and budgetary requirements.
3. Progress Report:
This research is related to inhouse project objective 3. Develop or improve comprehensive integrated disease management strategies. The objectives of this study are: 1) To develop a series of flexible stochastic models to predict the temporal increase and spatial spread of citrus disease. The models were initially designed for citrus canker but have subsequently been extended to huanglongbing (HLB). They can be used in a number of ways: to predict spread and to analyze the effectiveness of control strategies both in plantations and State-wide. 2) Test various control methods under field conditions to evaluate effects and collect data to parameterize models. An Susceptible Exposed Infected Diseased Removal (SEIDR) model was developed that uses Markov-chain Monte Carlo methods, and extensive data from South Florida. This model portrays successive snapshots of the occurrence of symptomatic detected trees in known populations of susceptible trees. To date we have been able to estimate the transmission rates and dispersal kernel for HLB by interrogating this prior data center. Currently we are working on differential effects of host age on epidemiological parameters and variability across the plantation. This allows us to explore the uncertainty how the predictions which is then incorporated in models to predict spread and to allow for uncertainty in the efficiency and comparison of control methods. A web based version of the model is in the final stages of development. This web-based model is for non-researcher users you can utilize it as a tool to understand how the disease will increase and spread both residential and commercial situations. It can also be used to test a wide variety of epidemiological and climate/weather variables and their effects on an HLB epidemic as well as various disease control/mitigation parameters to see the effect of these various control strategies. The team has been using the data from southern gardens citrus that includes both young and mature trees, since host age is likely to be an important consideration for HLB. The model continues to be improved upon to capture more and more of the true features of the data and the disease. The model is being extended to estimate spread in diverse situations, should HLB be introduced into new areas such as Texas, California or Arizona. Field plots were established at the USDA, ARS Picos Farm to examine the effects of insecticide control and roguing in various combinations, both to evaluate treatment effects and to collect epidemiological data for model development. These field studies are underway as well however, at the time of this writing there are no detectable statistical differences among various control strategies.