Automated detection and monitoring of grain beetles using a “smart” pitfall trap: Poster

A smart, electronic, modified pitfall trap, for automatic detection of adult beetle pests inside the grain mass is presented. The whole system is equipped with optoelectronic sensors to guard the entrance of the trap in order to detect, time-stamp, and GPS tag the incoming insect. Insect counts as well as environmental parameters that correlate with insect’s population development are wirelessly transmitted to a central monitoring agency in real time, are visualized and streamed to statistical methods to assist effective control of grain pests. The prototype trap was put in a large plastic barrel (120lt) with 80kg maize. Adult beetles of various species were collected from laboratory rearings and transferred to the experimental barrel. Caught beetle adults were checked and counted after 24h and were compared with the counts from the electronic system. Results from the evaluation procedure showed that our system is very accurate, reaching 98-99% accuracy on automatic counts compared with real detected numbers of adult beetles inside the trap. In this work we emphasize on how the traps can be selforganized in networks that collectively report data at local, regional, country, continental, and global scales using the emerging technology of the Internet of Things (IoT). We argue that smart traps communicating through IoT to report in real-time the level of the pest population from the grain mass straight to a human controlled agency can, in the very near future, have a profound impact on the decision making process in stored grain protection.A smart, electronic, modified pitfall trap, for automatic detection of adult beetle pests inside the grain mass is presented. The whole system is equipped with optoelectronic sensors to guard the entrance of the trap in order to detect, time-stamp, and GPS tag the incoming insect. Insect counts as well as environmental parameters that correlate with insect’s population development are wirelessly transmitted to a central monitoring agency in real time, are visualized and streamed to statistical methods to assist effective control of grain pests. The prototype trap was put in a large plastic barrel (120lt) with 80kg maize. Adult beetles of various species were collected from laboratory rearings and transferred to the experimental barrel. Caught beetle adults were checked and counted after 24h and were compared with the counts from the electronic system. Results from the evaluation procedure showed that our system is very accurate, reaching 98-99% accuracy on automatic counts compared with real detected numbers of adult beetles inside the trap. In this work we emphasize on how the traps can be selforganized in networks that collectively report data at local, regional, country, continental, and global scales using the emerging technology of the Internet of Things (IoT). We argue that smart traps communicating through IoT to report in real-time the level of the pest population from the grain mass straight to a human controlled agency can, in the very near future, have a profound impact on the decision making process in stored grain protection

Area-wide Integrated Pest Management

Over 98% of sprayed insecticides and 95% of herbicides reach a destination other than their target species, including non-target species, air, water and soil. The extensive reliance on insecticide use reduces biodiversity, contributes to pollinator decline, destroys habitat, and threatens endangered species. This book offers a more effective application of the Integrated Pest Management (IPM) approach, on an area-wide (AW) or population-wide (AW-IPM) basis, which aims at the management of the total population of a pest, involving a coordinated effort over often larger areas. For major livestock pests, vectors of human diseases and pests of high-value crops with low pest tolerance, there are compelling economic reasons for participating in AW-IPM. This new textbook attempts to address various fundamental components of AW-IPM, e.g. the importance of relevant problem-solving research, the need for planning and essential baseline data collection, the significance of integrating adequate tools for appropriate control strategies, and the value of pilot trials, etc. With chapters authored by 184 experts from more than 31 countries, the book includes many technical advances in the areas of genetics, molecular biology, microbiology, resistance management, and social sciences that facilitate the planning and implementing of area-wide strategies. The book is essential reading for the academic and applied research community as well as national and regional government plant and human/animal health authorities with responsibility for protecting plant and human/animal health

Area-wide Integrated Pest Management

Extensive reliance on insecticides reduces biodiversity, contributes to pollinator decline, destroys habitat and threatens endangered species. This book offers a more effective application of the Integrated Pest Management (IPM) approach, on an area-wide (AW) or population-wide (AW-IPM) basis. It addresses the importance of problem-solving research, planning and baseline data collection, integrating tools for appropriate control strategies, and pilot trials. The 48 chapters authored by 184 experts cover advances in genetics, molecular biology, biological control, resistance management, modelling, automated surveillance and unmanned aerial release systems

Inventory and review of quantitative models for spread of plant pests for use in pest risk assessment for the EU territory

This report considers the prospects for increasing the use of quantitative models for plant pest spread and dispersal in EFSA Plant Health risk assessments. The agreed major aims were to provide an overview of current modelling approaches and their strengths and weaknesses for risk assessment, and to develop and test a system for risk assessors to select appropriate models for application. First, we conducted an extensive literature review, based on protocols developed for systematic reviews. The review located 468 models for plant pest spread and dispersal and these were entered into a searchable and secure Electronic Model Inventory database. A cluster analysis on how these models were formulated allowed us to identify eight distinct major modelling strategies that were differentiated by the types of pests they were used for and the ways in which they were parameterised and analysed. These strategies varied in their strengths and weaknesses, meaning that no single approach was the most useful for all elements of risk assessment. Therefore we developed a Decision Support Scheme (DSS) to guide model selection. The DSS identifies the most appropriate strategies by weighing up the goals of risk assessment and constraints imposed by lack of data or expertise. Searching and filtering the Electronic Model Inventory then allows the assessor to locate specific models within those strategies that can be applied. This DSS was tested in seven case studies covering a range of risk assessment scenarios, pest types and dispersal mechanisms. These demonstrate the effectiveness of the DSS for selecting models that can be applied to contribute to EFSA Plant Health risk assessments. Therefore, quantitative spread and dispersal modelling has potential to improve current risk assessment protocols and contribute to reducing the serious impacts of plant pests in Europe

Nondestructive Multivariate Classification of Codling Moth Infested Apples Using Machine Learning and Sensor Fusion

Apple is the number one on the list of the most consumed fruits in the United States. The increasing market demand for high quality apples and the need for fast, and effective quality evaluation techniques have prompted research into the development of nondestructive evaluation methods. Codling moth (CM), Cydia pomonella L. (Lepidoptera: Tortricidae), is the most devastating pest of apples. Therefore, this dissertation is focused on the development of nondestructive methods for the detection and classification of CM-infested apples. The objective one in this study was aimed to identify and characterize the source of detectable vibro-acoustic signals coming from CM-infested apples. A novel approach was developed to correlate the larval activities to low-frequency vibro-acoustic signals, by capturing the larval activities using a digital camera while simultaneously registering the signal patterns observed in the contact piezoelectric sensors on apple surface. While the larva crawling was characterized by the low amplitude and higher frequency (around 4 Hz) signals, the chewing signals had greater amplitude and lower frequency (around 1 Hz). In objective two and three, vibro-acoustic and acoustic impulse methods were developed to classify CM-infested and healthy apples. In the first approach, the identified vibro-acoustic patterns from the infested apples were used for the classification of the CM-infested and healthy signal data. The classification accuracy was as high as 95.94% for 5 s signaling time. For the acoustic impulse method, a knocking test was performed to measure the vibration/acoustic response of the infested apple fruit to a pre-defined impulse in comparison to that of a healthy sample. The classification rate obtained was 99% for a short signaling time of 60-80 ms. In objective four, shortwave near infrared hyperspectral imaging (SWNIR HSI) in the wavelength range of 900-1700 nm was applied to detect CM infestation at the pixel level for the three apple cultivars reaching an accuracy of up to 97.4%. In objective five, the physicochemical characteristics of apples were predicted using HSI method. The results showed the correlation coefficients of prediction (Rp) up to 0.90, 0.93, 0.97, and 0.91 for SSC, firmness, pH and moisture content, respectively. Furthermore, the effect of long-term storage (20 weeks) at three different storage conditions (0 °C, 4 °C, and 10 °C) on CM infestation and the detectability of the infested apples was studied. At a constant storage temperature the detectability of infested samples remained the same for the first three months then improved in the fourth month followed by a decrease until the end of the storage. Finally, a sensor data fusion method was developed which showed an improvement in the classification performance compared to the individual methods. These findings indicated there is a high potential of acoustic and NIR HSI methods for detecting and classifying CM infestation in different apple cultivars

Metapopulation Modelling and Spatial Analysis for HEG Technology in the Control of Malaria

The success of any vector control strategy can be enhanced by onsite analysis and investigation. Combatting malaria, a global disease carried by the vector Anopheles gambiae, has led to the development of novel genetic technologies such as the use of HEG; homing endonuclease genes. This thesis explored the age and stage elements of the vector, building upon current biological understanding and using fitting algorithms with metapopulation matrices to create cohort orientated survival and transition. The environmental forces were analysed alongside this with emphasis on sub-model creation and tool design, employing an array of methods from RBF to satellite classification to couple the local environment and vector. When added, the four potential genetic strategies all demonstrated the ability to suppress a wild type population and even eradicate it, although reinvasion and hotspot population phenomena were reoccurring observations. The movement of the vector was an important factor in control efficiency, which was investigated as a series of different assumptions using wind driven movement and host attraction. Lastly, practical factors such as monitoring and resource distribution within a control project were assessed, which required routing solutions and landscape trapping assessments. This was explored within a framework of Mark-Release-Recapture experiment design that could provide critical information for efficient HEG release strategies.Open Acces

Biological Invasions in South Africa

This open access volume presents a comprehensive account of all aspects of biological invasions in South Africa, where research has been conducted over more than three decades, and where bold initiatives have been implemented in attempts to control invasions and to reduce their ecological, economic and social effects. It covers a broad range of themes, including history, policy development and implementation, the status of invasions of animals and plants in terrestrial, marine and freshwater environments, the development of a robust ecological theory around biological invasions, the effectiveness of management interventions, and scenarios for the future. The South African situation stands out because of the remarkable diversity of the country, and the wide range of problems encountered in its varied ecosystems, which has resulted in a disproportionate investment into both research and management. The South African experience holds many lessons for other parts of the world, and this book should be of immense value to researchers, students, managers, and policy-makers who deal with biological invasions and ecosystem management and conservation in most other regions

Biological Invasions in South Africa

This open access volume presents a comprehensive account of all aspects of biological invasions in South Africa, where research has been conducted over more than three decades, and where bold initiatives have been implemented in attempts to control invasions and to reduce their ecological, economic and social effects. It covers a broad range of themes, including history, policy development and implementation, the status of invasions of animals and plants in terrestrial, marine and freshwater environments, the development of a robust ecological theory around biological invasions, the effectiveness of management interventions, and scenarios for the future. The South African situation stands out because of the remarkable diversity of the country, and the wide range of problems encountered in its varied ecosystems, which has resulted in a disproportionate investment into both research and management. The South African experience holds many lessons for other parts of the world, and this book should be of immense value to researchers, students, managers, and policy-makers who deal with biological invasions and ecosystem management and conservation in most other regions