New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

Integrated pest management and the (un)sustainable use of pesticides

Doutoramento em Engenharia Agronómica - Instituto Superior de Agronomia - UL

Approaches to Aquatic Invasive Species Integrated Pest Management Control and Common ID

This PowerPoint presentation goes over the ways in which aquatics pest and weeds can be controlled.

Influência de fragmentos de cerrado na distribuição de ácaros em seringal

Este estudo teve como objetivo verificar se fragmentos de cerrado influenciam na composição da acarofauna de seringais. Foram estabelecidos cinco transectos, distantes 50 m entre si, em duas áreas de cultivo no sul do Mato Grosso, sendo o primeiro na borda com o limite das áreas nativas e o último a 200 m no interior do seringal. em cada transecto foram marcadas cinco plantas, sendo coletadas sete folhas de cada planta. Durante um ano foram realizadas 25 coletas quantitativas em dois cultivos de seringueiras. O menor número de fitófagos foi registrado no transecto próximo da vegetação nativa e o maior no mais distante. A maior diversidade também foi observada no transecto mais próximo da vegetação nativa. Dez espécies de ácaros predadores também foram registradas nas áreas nativas vizinhas. Os dados sugerem o deslocamento dos ácaros predadores das áreas naturais para o monocultivo. Essas áreas naturais podem fornecer alimento alternativo e hábitat para inimigos naturais de fitófagos no período de escassez de alimento no seringal. A presença de áreas nativas próximo a áreas de cultivo deve ser considerada na elaboração de programas de manejo ecológico de pragas.

Incidência de mosca-minadora e insetos vetores em sistemas de manejo de pragas em tomateiro

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Ecological modeling and pest population management: a possible and necessary connection in a changing world

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Ecological Networks in Stored Grain: Key Postharvest Nodes for Emerging Pests, Pathogens, and Mycotoxins

Wheat is at peak quality soon after harvest. Subsequently, diverse biota use wheat as a resource in storage, including insects and mycotoxin-producing fungi. Transportation networks for stored grain are crucial to food security and provide a model system for an analysis of the population structure, evolution, and dispersal of biota in networks. We evaluated the structure of rail networks for grain transport in the United States and Eastern Australia to identify the shortest paths for the anthropogenic dispersal of pests and mycotoxins, as well as the major sources, sinks, and bridges for movement. We found important differences in the risk profile in these two countries and identified priority control points for sampling, detection, and management. An understanding of these key locations and roles within the network is a new type of basic research result in postharvest science and will provide insights for the integrated pest management of high-risk subpopulations, such as pesticide-resistant insect pests.

Ecological consequences of genetic modifications - an invasion analysis approach

Biological invasions are considered as one of the greatest threats to biodiversity, as they may lead to disruption and homogenization of natural communities, and in the worst case, to native species extinctions. The introduction of gene modified organisms (GMOs) to agricultural, fisheries and forestry practices brings them into contact with natural populations. GMOs may appear as new invasive species if they are able to (1) invade into natural habitats or (2) hybridize with their wild relatives. The benefits of GMOs, such as increased yield or decreased use of insecticides or herbicides in cultivation, may thus be reduced due the potential risks they may cause. A careful ecological risk analysis therefore has to precede any responsible GMO introduction. In this thesis I study ecological invasion in relation to GMOs, and what kind of consequences invasion may have in natural populations. A set of theoretical models that combine life-history evolution, population dynamics, and population genetics were developed for the hazard identification part of ecological risks assessment of GMOs. In addition, the potential benefits of GMOs in management of an invasive pest were analyzed. In the first study I showed that a population that is fluctuating due to scramble-type density dependence (due to, e.g., nutrient competition in plants) may be invaded by a population that is relatively more limited by a resource (e.g., light in plants) that is a cause of contest-type density dependence. This result emphasises the higher risk of invasion in unstable environments. The next two studies focused on escape of a growth hormone (GH) transgenic fish into a natural population. The results showed that previous models may have given too pessimistic a view of the so called Trojan gene -effect, where the invading genotype is harmful for the population as a whole. The previously suggested population extinctions did not occur in my studies, since the changes in mating preferences caused by the GH-fish were be ameliorated by decreased level of competition. The GH-invaders may also have to exceed a threshold density before invasion can be successful. I also showed that the prevalence of mature parr (aka. sneaker) strategy among GH-fish may have clear effect on invasion outcome. The fourth study assessed the risks and developed methods against the invasion of the Colorado Potato Beetle (CPB, Leptinotarsa decemlineata). I showed that the eradication of CPB is most important for the prevention of their establishment, but the cultivation of transgenic Bt-potato could also be effective. In general, my results emphasise that invasion of transgenic species or genotypes to be possible under certain realistic conditions and resulting in competitive exclusion, population decline through outbreeding depression and genotypic displacement of native species. Ecological risk assessment should regard the decline and displacement of the wild genotype by an introduced one as a consequence that is as serious as the population extinction. It will also be crucial to take into account different kinds of behavioural differences among species when assessing the possible hazards that GMOs may cause if escaped. The benefits found of GMO crops effectiveness in pest management may also be too optimistic since CPB may evolve resistance to Bt-toxin. The models in this thesis could be further applied in case specific risk assessment of GMOs by supplementing them with detailed data of the species biology, the effect of the transgene introduced to the species, and also the characteristics of the populations or the environments in the risk of being invaded.