Use of geographic information systems in warning services for late blight*

One of the important aims of the German Crop Protection Services (GCPS) is to reduce spraying intensity as part of an environmentally friendly crop protection strategy. ZEPP is the central institution in Germany responsible for the development of methods with the goal of improving the control of plant diseases and, to this end, more than 20 meteorological data‐based models have been developed and introduced into practice. This study shows that it is possible to improve the accuracy of the results given by the models by using Geographic Information Systems (GIS). The influence of elevation, slope and aspect on meteorological data was interpolated with GIS and the results were used as input for forecasting models. The results will be presented as spatial risk maps on which areas of maximum disease risk are displayed. The modern presentation methods of GIS enable the results to be displayed in a more user‐friendly way.     

The Dutch approach: a combination of meteo‐based decision‐support systems*

Reduction in the amount of active substance and reduced dependence on chemical plant production products are the main items in the Dutch Government Multiyear Crop Protection Plan. There are problems in reaching this goal, as weather conditions in The Netherlands are very beneficial to all kinds of fungal diseases. Such diseases have to be controlled by applications of preventive fungicides, and it is quite regular to use a spray interval of 6–7 days. Another problem is application at the wrong time. With the help of decision‐support systems (DSSs), it is possible to calculate the period of protection by a product, the danger of an infection period and the moment of highest efficacy. DLV‐Meteo offers advice based on five DSSs for individual pests (Prophy, onion leaf spot disease, Botrypré, Mycos and Contapré) and on a general DSS for application at the time of day that ensures highest efficacy (Gewis).     

Development and implementation of cost‐effective plant protection technology using decision‐support systems in Lithuania*

In many European countries, factors important for decision‐making in plant protection, such as biology, weather and environmental conditions, crop management level and their relationships, have been incorporated into decision‐support systems (DSSs). In 1996, a project was jointly elaborated, and research was started by the Danish Institute of Plant and Soil Science, the Lithuanian Institute of Agriculture and the Lithuanian and Danish Agricultural Advisory Services. This research was focused on the testing, development and adaptation of a Danish computer‐based decision‐support and information system (PC‐Plant Protection) for plant protection under Lithuanian conditions. Trials were carried out by the Lithuanian Institute of Agriculture in 1996/1998 to investigate the potential for reducing fungicide inputs in cereal production in different regions of Lithuania representing typical local agrometeorological conditions. On the basis of the trials, the following conclusions were drawn: the reduced doses and fungicide combinations recommended by the DSS gave rather good control of diseases; spraying according to the recommendations of the DSS increased yield significantly in all experiments and allowed saving in fungicides; some models, e.g. for Leptosphaeria nodorum, were not fully suitable for Lithuanian conditions and need to be developed further.     

Computer aids for plant protection,historical perspective and future developments*

Initiatives such as Videotext and forecasting models resulted in a relatively fast introduction of computer technology on to farms at the end of the 1980s. In several countries there were developments to create models for supervised control and data exchange became digital. Most models were developed for diseases that could expand very rapidly, or diseases that should be controlled regularly. In the 1990s, development of weather‐related Decision Support Systems (DSSs) began. It is important to use the optimal way to disseminate information to the target group; which can differ between or even within countries. The use of DSSs results in a lower risk of crop damage by diseases and pests, and a lower input of active substances, from the use of adjusted dosages. Future developments may include the possibility of implementing a number of DSS‐models into a Geographical Information System, which will support precision agriculture by providing adjusted spraying advice based on plot‐specific characteristics. The success of DSSs is despite its development occurring independently in a number of countries. The speed of development of these systems would have been substantially faster had there been real cooperation between countries or groups of researchers. In order to withstand funding reductions, it is necessary for the development of new DSSs that collaboration between researchers and research groups internationally increases significantly in the near future.     

Decision aids for multiple-decision disease management as affected by weather input errors

Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.     

Structure and organization of warning services in Rheinland‐Pfalz (Germany)*

Rheinland‐Pfalz, a federal state in the south‐western part of Germany, is an agricultural region with high crop diversity. For each branch of agriculture (arable, fruits, vegetables and ornamental plants), specific warning and information services have been installed. Advisory work, including warning services, is done by a central (LPP) and eight regional state institutions (SL V As). LPP provides the infrastructure for information dissemination, organizes data acquisition and supplies the farmers with general information on crop protection (availability of plant protection products, control strategies, etc.), SL V As collect data on current pest development and elaborate regional recommendations on field assessments and control measures to be taken by the farmers. Warning service information is transmitted to the farmers by info post (periodic letters), telephone‐answering machines, fax services and, lately, via the Internet. Farmers are mainly interested in current disease and pest severity data, preferably on a local basis, to aid their decision‐making in crop protection. The forecasting models and computer‐aided decision‐support systems run by the state crop protection service have become essential tools during the last four years. Their results, supplemented by field‐monitoring data, serve as the main input for the warning services. The Internet, in conjunction with computerized decision‐support systems, provides the means of ensuring an adequate supply of warning service information at a time when crop protection services are undergoing severe staff reductions.     

Intranet in Baden‐Württemberg (Germany) – using the technology of the Internet for internal information interchange within a State Plant Protection Service*

This article describes the new possibilities of an intranet for internal interchange of information within the plant protection service of a German federal state. In Baden‐Württemberg, the precondition is a closed internal network with central information servers and workstations at the local offices of agriculture. The intranet with information servers is based on the technology of the Internet and is a modern and user‐friendly tool for supplying advisers highly efficiently and economically with current comments, relevant notices, files, weather data and evalutions of computer aids for decision‐making. In the last 2 years, significant progress has been made in the automation of procedures for data request, transmission and evaluation of weather data for the warning service. In the plant protection service of Baden‐Württemberg, the most important data‐processing routines and evaluations of computer aids for decision‐making are running automatically as batch files. In order to save time in the preparation of regional warnings, the relevant information is available to the advisers via intranet at the beginning of their work. Compared with traditional procedures, the intranet with information servers is advantageous to the information supplier (Central Institute of Plant Protection) as well as to the user (advisers at the local offices of agriculture).     

Decision support systems: barriers and farmers’ need for support*

The highly complex knowledge of scientific disciplines makes nuanced analysis and modelling possible. However, the information produced often does not reach farmers because it is presented in a way that does not correspond to the way their work is carried out in practice. The decision support system Crop Protection Online is widely used by advisors and as a learning tool for students. Although the system has been validated in many field trials over the years and has shown reliable results, the number of end‐users among farmers has been relatively low during the last 10 years (approximately 1000 farmers). A sociological investigation of farmers’ decision‐making styles in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) system‐orientated farmers, (b) experience‐based farmers and (c) advisory‐orientated farmers. The information required by these three groups to make their decisions varies and therefore different ways of using decision support systems need to be provided. Decision support systems need to be developed in close dialogue and collaboration with user groups.     

Instruments of the warning service for plant protection in Bayern (Germany)*

The warning service for plant protection in Bayern (Germany) obtains its information mainly from its own observations. The appearance of pests (including diseases and weeds) is investigated in cultivated areas and field trials. Weather data complementary to the pest enquiries can be made available from a measuring network of 116 field weather stations and is used to estimate the development of pests in relation to weather requirements. For several fungi and animal pests, computer‐based decision support systems (DSSs) and forecasting models are being used. The results are processed and passed on to farmers via circulars, branch reviews, public notices, telephonic announcement services, telefax services and the Internet.     

Computer aids for plant protection in Latvia*

The main agricultural crops where decision support systems (DSS) can be used via the Internet in Latvia are winter and spring cereals and potato. Two PC‐based models, forming part of a Danish DSS, were tested under the agroecological conditions of Latvia in 1999/2002: PC‐Plant Protection to control diseases in cereals and several modifications of the NegFry model for prediction of potato late blight. The results of 4 years of trials suggest that models that satisfy the needs of one pest may not fit another. The main reasons for failure to adapt PC models are differences in cultivar susceptibility, differences in pathogenicity, simultaneous action of other organisms and spatial placement of crops (forests, rivers and fallow land). For example, it is well known that, with the recent global migration of more aggressive strains and populations of Phytophthora infestans, late blight epidemics have become less predictable and, at the same time, less controllable in potato‐growing areas. For cereals, there is a different spectrum of prevailing pathogens, causing different levels of damage, requiring incorporation into models of thresholds corresponding to local conditions. Data from weekly monitoring of local fields, warnings about the local situation and meteorological information via the Internet are the most important computer‐aided elements for experts in plant protection.     

A decision algorithm for patch spraying

It has been established that weeds are spatially aggregated with a spatially varying composition of weed species within agricultural fields. Site‐specific spraying therefore requires a decision method that includes the spatial variation of the weed composition and density. A computerized decision method that estimates an economic optimal herbicide dose according to site‐specific weed composition and density is presented in this paper. The method was termed a ‘decision algorithm for patch spraying’ (DAPS) and was evaluated in a 5‐year experiment, in Denmark. DAPS consists of a competition model, a herbicide dose–response model and an algorithm that estimates the economically optimal doses. The experiment was designed to compare herbicide treatments with DAPS recommendations and the Danish decision support system PC‐Plant Protection. The results did not show any significant grain yield difference between DAPS and PC‐Plant Protection; however, the recommended herbicide doses were significantly lower when using DAPS than PC‐Plant Protection in all years. The main difference between the two decision models is that DAPS integrates crop–weed competition and estimates the net return as a continuous function of herbicide dose. The hypothesis tested is that the benefit of using lower herbicide doses recommended by DAPS would disappear after a few years because weed density will increase and thus require higher doses. However, the results of weed counting every year did not confirm this hypothesis.     

AgmedaWin – a tool for easy and flexible management of meteorological data*

Decision support systems in plant protection need plausible and complete meteorological data as the main input. While meteorological data are provided by the German meteorological service, several states in Germany have built up their own meteorological networks. These states use the software AgmedaWin to import, manage, present, evaluate and export the measured data. At the core of the program is a flexible import module which facilitates the import of files in different formats from all types of meteorological stations by using import profiles to describe the structure of the files. Several algorithms are integrated in AgmedaWin to ensure plausibility and completeness of the data. The program also includes a module to compare the data of neighbouring stations. AgmedaWin is being used so far in seven states of Germany since 2005. With an XML–based export interface the data are transferred from AgmedaWin to the Internet system ISIP ( http://www.isip.de ) in which all data are stored and used as input for decision support systems. Furthermore the unprocessed meteorological data can be evaluated in ISIP or downloaded as files in different formats by external users.     

PRATIQUE: a research project to enhance pest risk analysis techniques in the European Union

PRATIQUE is an EC-funded 7th Framework research project designed to address the major challenges for pest risk analysis (PRA) in Europe. It has three principal objectives: (a) to assemble the datasets required to construct PRAs valid for the whole of the EU, (b) to conduct multi-disciplinary research that enhances the techniques used in PRA and (c) to provide a decision support scheme for PRA that is efficient and user-friendly. The research will be undertaken by scientists from 13 institutes in the EU and one each from Australia and New Zealand with subcontractors from institutes in China and Russia. They will produce a structured inventory of PRA datasets for the EU and undertake targeted research to improve existing procedures and develop new methods for (a) the assessment of economic, environmental and social impacts, (b) summarising risk while taking account of uncertainty, (c) mapping endangered areas (d) pathway risk analysis and systems approaches and (e) guiding actions during emergencies caused by outbreaks of harmful organisms. The results will be tested and provided as protocols, decision support systems and computer programs with examples of best practice linked to a computerised European and Mediterranean Plant Protection Organization (EPPO) PRA scheme.     

http://www.isip.de– online plant protection information in Germany*

The demand for information from agricultural professionals is increasing steadily but can be met with the use of modern communications technologies. Consequently, governmental extension services in Germany have introduced the Information System for Integrated Plant Production (ISIP). ISIP, an Internet‐based information system, gives rapid and convenient access to all data necessary for integrated plant production. Target groups are farmers as well as extension workers. The system focuses on problem‐specific decision support modules for a range of agronomical and horticultural crops. In ISIP, such a module does not only comprise a model for decision support. Due to the fact that a model is only a simplified representation of reality, simulation results are supplemented by monitoring data (if available) and a comment of a regional extension worker. This ‘threefold decision support’ is one of the unique features of ISIP. The framework of ISIP integrating independent models for decision support is built in an open and readily extensible architecture. To incorporate new simulation approaches, the concept of a ‘master component’ frees the developer from technical details and provides a comparatively simple integration. This speeds up model development and ensures a fast knowledge transfer.     

Tree fruit IPM programs in the western United States: the challenge of enhancing biological control through intensive management

The seminal work of Stern and his coauthors on integrated control has had a profound and long‐lasting effect on the development of IPM programs in western orchard systems. Management systems based solely on pesticides have proven to be unstable, and the success of IPM systems in western orchards has been driven by conservation of natural enemies to control secondary pests, combined with pesticides and mating disruption to suppress the key lepidopteran pests. However, the legislatively mandated changes in pesticide use patterns prompted by the Food Quality Protection Act of 1996 have resulted in an increased instability of pest populations in orchards because of natural enemy destruction. The management system changes have made it necessary to focus efforts on enhancing biological control not only of secondary pests but also of primary lepidopteran pests to help augment new pesticides and mating disruption tactics. The new management programs envisioned will be information extensive as well as time sensitive and will require redesign of educational and outreach programs to be successful. The developing programs will continue to use the core principles of Stern and his co‐authors, but go beyond them to incorporate changes in society, technology and information transfer, as needed. Copyright © 2009 Society of Chemical Industry     

Collection,processing and transfer of weather data in the Agrometeorological Measuring Net of Rheinland‐Pfalz: a prior condition for using weather‐based forecasting systems*

The fundamental and most important condition for running forecasting systems successfully is the input of correct meteorological data. Rheinland‐Pfalz owns more then 30 agrometeorological measuring stations, which automatically collect data 24 h a day. This article describes how the data is managed (collection by modem, plausibility tests, filling blanks in the weather files), how the data flow from the Agrometeorological Measuring Net Rheinland‐Pfalz (AMN RP) to the adviser in the plant protection office is organized, how administration of data, sensors and service routines works and, finally, the conclusions and improvements that are made based on the results. This leads to meteorological data of high quality, which are necessary for weather‐based forecasting systems to guarantee a high standard of certainty when using the results of simulation in agricultural practice.     

Problems with disseminating information on disease control in wheat and barley to farmers

Plant pathologists have traditionally worked in the area of clarifying and understanding the disease cycles of specific diseases, factors influencing epidemiology, yield loss potential and host-pathogen interactions in order to be able to minimise the disease risk, build warning systems or recommend specific control thresholds in relation to the application of fungicides. The decision support system Crop Protection Online (CPO) is an example of a threshold-based system that determines economically viable fungicide strategies. The system is based on using appropriate doses aimed at minimising the overall pesticide input. CPO is used widely by advisors and many of the thresholds are generally accepted and disseminated through newsletters. The national figures for the use of fungicides in cereals have shown a major reduction during the last 20 years and their use today is much in line with the level that can be achieved from using CPO as indicated from validation trials. The number of end-users among farmers has been stable at around 3% during the last 10 years (800–1,000 farmers). Major hurdles in increasing the number of users are believed to be: (1) the requirements for carrying out assessments in the field, (2) farm sizes getting larger, leaving less time for decision making for individual fields, (3) lack of economic incentives to change from standard treatments, (4) the failure of decision support systems to interact with other computer-based programmes on the farm, (5) the lack of compatibility of decision support systems with farmers’ ways of making decisions on crop protection in general, (6) the need for direct interactions with advisors. A sociological investigation into the farmers’ way of making decisions in the area of crop protection has shown that arable farmers can be divided into three major groups: (a) systems-orientated farmers, (b) experienced-based farmers and (c) advisory-orientated farmers. The information required by these three groups is different and has to be looked at individually from the end-user’s perspective rather than from the scientist’s perspective. New ways of entering the decision support system where specific field inspections are omitted and where regional disease data are relied on, have been investigated and tested in field trials. The results show possibilities for further developments in that direction, which might be one way of gaining more end-users.     

An international campaign coordinated by EPPO to control Colorado Beetle in the Channel Islands

Collaboration between the Plant Protection Services of France and the Channel Islands has helped to keep Jersey and Guernsey free of Colorado Beetle (Leptinotarsa decemlineata) for over 60 years. The Channel Islands lie close to the coast of the Cotentin peninsula where potato fields are still infested with Colorado Beetle. Joint surveys of the coastal potato fields of Cotentin provide valuable information on beetle populations. Beetle flight records together with local weather data provide the necessary information to issue Colorado Beetle alerts to the Channel Islands during the months of May–July. High risk alerts issued by French Plant Protection colleagues are acted on and inspectors are mobilised to search beaches in Jersey and Guernsey for adult beetles. Farmers are not obliged to control Colorado Beetle in France. However, there has been an agreement negotiated in the Cotentin that farmers will treat their fields if beetles are found, with monitoring carried out by staff from a local co‐operative. This co‐operation has proved essential in the Colorado Beetle campaign.     

Development of an interactive decision‐support system on a Web site for control of Mycosphaerella graminicola in winter wheat*

A decision‐support system (DSS) has been developed in Belgium to help farmers and advisers to manage Mycosphaerella graminicola in winter wheat during stem elongation. The system calculates in real time the interactions between winter wheat and M. graminicola development to simulate disease progression in the canopy in order to guide field observations on the different leaf layers and determine the risks for the crop. It has been structured to run with individual field input and local hourly meteorological data. An interactive Internet version of the system has been developed to facilitate the delivery of information. It allows users to base their decisions on advice tailored to conditions in their own fields, as well as to recent and validated hourly local meteorological data that is regularly updated on the server computer.     

Decision support systems used in the Netherlands for reduction in the input of active substances in agriculture

Since the middle of the 1980s, Dutch farmers have been using decision support systems (DSS) as an aid in the control of pests. This started with EPIPRE, then weather-related potato blight warning systems were developed (Prophy and Plant-Plus). In the 1990s, many weather-based DSS were developed against pests of orchards, flower bulbs, arable crops and field-produced vegetables. Also, a DSS was developed to predict and check the effect of meteorological conditions on the effectiveness of application timing of plant protection products (GEWIS). The use of these systems resulted in more sustainable crop protection: sustainable because the use of DSS led to a lower risk of crop damage and, in many cases, to a lower input of active substances, by optimization of the product and dose to actual phytosanitary and meteorological conditions. The use of GEWIS to ensure application at the right time of day further reduced the input of active substances and increased efficacy.