A General Model for the Effect of Crop Management on Plant Disease Epidemics at Different Scales of Complexity

A general and flexible model was developed to simulate progress over time of the epidemics caused by a generic polycyclic pathogen on aerial plant parts. The model includes all of the epidemiological parameters involved in the pathogen life cycle: between-season survival, production of primary inoculum, occurrence of primary infections, production and dispersal of secondary inoculum both inside and outside the crop, and concatenation of secondary infection cycles during the host's growing season. The model was designed to include the effect of the main crop management actions that affect disease levels in the crop. Policy-oriented, strategic, and tactical actions were considered at the different levels of complexity (from the agro-ecosystem to the farming and cropping system). All effects due to disease management actions were translated into variations in the epidemiological components of the model, and the model quantitatively simulates the effect of these actions on epidemic development, expressed as changes in final disease and in the area under the disease progress curve. The model can help researchers, students and policy makers understand how management decisions (especially those commonly recommended as part of Integrated Pest Management programs) will affect plant disease epidemics at different scales of complexity

Helping farmers face the increasing complexity of decision-making for crop protection

The European Community Directive 128/2009 on the Sustainable Use of Pesticides establishes a strategy for the use of plant protection products (PPPs) in the European Community so as to reduce risks to human health and the environment. Integrated Pest Management (IPM) is a key component of this strategy, which will become mandatory in 2014. IPM is based on dynamic processes and requires decision-making at strategic, tactical, and operational levels. Relative to decision makers in conventional agricultural systems, decision makers in IPM systems require more knowledge and must deal with greater complexity. Different tools have been developed for supporting decision-making in plant disease control and include warning services, on-site devices, and decision support systems (DSSs). These decision-support tools operate at different spatial and time scales, are provided to users both by public and private sources, focus on different communication modes, and can support multiple options for delivering information to farmers. Characteristics, weaknesses, and strengths of these tools are described in this review. Also described are recently developed DSSs, which are characterised by: i) holistic treatment of crop management problems (including pests, diseases, fertilisation, canopy management and irrigation); ii) conversion of complex decision processes into simple and easy-to-understand ‘decision supports’; iii) easy and rapid access through the Internet; and iv) two-way communication between users and providers that make it possible to consider context-specific information. These DSSs are easy-to-use tools that perform complex tasks efficiently and effectively. The delivery of these DSSs via the Internet increases user accessibility, allows the DSSs to be updated easily and continuously (so that new knowledge can be rapidly and efficiently provided to farmers), and allows users to maintain close contact with providers

Toward domotic appliances control through a self-paced P300-based BCI

During recent years there has been a growing interest in Brain Computer Interface (BCI) systems as an alternative means of interaction with the external world for people with severe motor disabilities. The use of the P300 event-related potentials as control feature allows users to choose between various options (letters or icons) requiring a very short calibration phase. The aim of this work is to improve performances and flexibility of P300 based BCIs. An efficient BCI system should be able to understand user's intentions from the ongoing EEG, abstaining from doing a selection when the user is engaged in a different activity, and changing its speed of selection depending on current user's attention level. Our self-paced system addresses all these issues representing an important step beyond the classical synchronous P300 BCI that forces the user in a continuous control task. Experimentation has been performed on 10 healthy volunteers acting on a BCI-controlled domestic environment in order to demonstrate the potential usability of BCI systems in everyday life. Results show that the self-paced BCI increases information transfer rate with respect to the synchronous one, being very robust, at the same time, in avoiding false negatives when the user is not engaged in a control task

Technological developments for ultra-lightweight, large aperture, deployable mirror for space telescopes

The increasing interest on space telescopes for scientific applications leads to implement the manufacturing technology of the most critical element, i.e. the primary mirror: being more suitable a large aperture, it must be lightweight and deployable. The presented topic was originally addressed to a spaceborne DIAL (Differential Absorption LIDAR) mission operating at 935.5 nm for the measurement of water vapour profile in atmosphere, whose results were presented at ICSO 2006 and 2008. Aim of this paper is to present the latest developments on the main issues related to the fabrication of a breadboard, covering two project critical areas identified during the preliminary studies: the design and performances of the long-stroke actuators used to implement the mirror active control and the mirror survivability to launch via Electrostatic Locking (EL) between mirror and backplane. The described work is developed under the ESA/ESTEC contract No. 22321/09/NL/RA. The lightweight mirror is structured as a central sector surrounded by petals, all of them actively controlled to reach the specified shape after initial deployment and then maintained within specs for the entire mission duration. The presented study concerns: a) testing the Carbon Fiber Reinforced Plastic (CFRP) backplane manufacturing and EL techniques, with production of suitable specimens; b) actuator design optimisation; c) design of the deployment mechanism including a high precision latch; d) the fabrication of thin mirrors mock-ups to validate the fabrication procedure for the large shells. The current activity aims to the construction of an optical breadboard capable of demonstrating the achievement of all these coupled critical aspects: optical quality of the thin shell mirror surface, actuators performances and back-plane - EL subsystem functionality

A General Model for the Effect of Crop Management on Plant Disease Epidemics at Different Scales of Complexity

A general and flexible model was developed to simulate progress over time of the epidemics caused by a generic polycyclic pathogen on aerial plant parts. The model includes all of the epidemiological parameters involved in the pathogen life cycle: between-season survival, production of primary inoculum, occurrence of primary infections, production and dispersal of secondary inoculum both inside and outside the crop, and concatenation of secondary infection cycles during the host’s growing season. The model was designed to include the effect of the main crop management actions that affect disease levels in the crop. Policy-oriented, strategic, and tactical actions were considered at the different levels of complexity (from the agro-ecosystem to the farming and cropping system). All effects due to disease management actions were translated into variations in the epidemiological components of the model, and the model quantitatively simulates the effect of these actions on epidemic development, expressed as changes in final disease and in the area under the disease progress curve. The model can help researchers, students and policy makers understand how management decisions (especially those commonly recommended as part of Integrated Pest Management programs) will affect plant disease epidemics at different scales of complexity

Sviluppo di un modello flessibile per le malattie fungine

A mechanistic model was developed for the simulations of epidemics caused by air-borne fungal pathogens on any crops. Components of the infection process are simulated by specific sub-models which use metereological variables as driving variables and pathogen-related parameters. Model parameters are estimated from literature data by using original procedures. The main output of the model is the disease progress expressed as proportion of host tissue affected. The model is flexible because it can be easly adapted to a wide range of host-pathogen couples