The IPM Decisions platform provides a Decision Support System (DSS) for integrated pest management. The platform includes several integrated DSS  for a variety of crops and offers useful external links as well. The available dashboards of the IPM platform enable users to compare results from various DSS for a given pest or disease or even set the parameters within the DSS to broaden their applicability. Outcomes for Greece: The concept of using DSS platforms is relatively new in Greece and not that common among farmers. However, the introduction of IPM Decisions has significantly added value to the agricultural sector of our country. Over the years,our efforts and activities have provided farmers, advisors, researchers and other stakeholders with the opportunity to become acquainted with this innovative tool. As a result, IPM Decisions has not only filled a gap in knowledge but also empowered them to make informed and effective decisions. Also, there are two significant DSS developed in our country; one for codling moth in pome fruits and another for downy mildew in grapes, both of which are cultivated by Greek farmers.
 

The IPM DECISIONS project has developed a platform that makes a variety of DSSs accessible for the control of plant diseases and parasites. Some DSS are fully usable across the platform; others are connected to it but not directly usable. The platform connects to the meteorological data of the area in which the farm is located and allows users to receive indications for the treatments to be carried out. The project highlighted that in Italy there still remains a certain skepticism about the usefulness and validity of DSS, although signs of increased confidence are emerging. Farmers recognize a lack of skills in using DSS which limits them from taking the first step. It is therefore essential to work on the skills of agricultural entrepreneurs but also of consultants who can act as intermediaries in the use of the IPM DECISIONS platform. It is in this sense that the platform provides a type of access specifically for consultants, who can therefore follow the activities of the companies they assist, recommend their actions based on the results suggested by the DSS performed, and compare the results.
 

The European IPM Decisions project has developed a web-based platform that provides access to the results of a number of Decision Support Systems (DSS) for use in Integrated Pest Management (IPM) in Europe. On the IPM Decisions platform, registered users can access the risk assessment of damage caused by selected pests to selected crops. At the end of the project, more than 25 DSS will be integrated into the IPM Decisions platform. Two DSS have been validated in the IPM Decisions platform for Slovenia for use in IVR, namely for the prediction of the risk of damage caused by the apple weevil (Cydia pomonella L.) on apple and pear. Users can also use models developed or validated in neighbouring countries if they wish, but it is necessary to check the accuracy of the predictions before using them. If the user determines that an adjustment to the DSS is required, they can do so in the 'DSS adaption dashboard' section. Once the user is satisfied with the model result, they can save it for future use. The IPM Decisions platform is available in 12 European languages, including Slovenian, and will continue to be available after the end of the project: www.platform.ipmdecisions.net 
 

www.platform.ipmdecisions.net offers an easy access to a range of Decision Support Systems for pest management in agriculture. In a first step, the platform has been promoted in France through the DEPHY network, a network of farmers demonstrating their efforts to reduce pesticide use, facilitated by advisors (i.e. the French component of the EU IPMWORKS network). The platform was demonstrated in national seminars and webinars. This first promotion had little success, partly because French farmers already benefit from weekly warnings based on both monitoring of a field network and pest dynamics models, partly because the DEPHY network is promoting mostly the re-design of cropping system to reduce weed, disease and pest pressure, rather than the optimisation of decision making. As a second step, the promotion targetted those advisors who are engaged in preparing the warning bulletins, who proved to be very interested in making use of the platform as a complement to strengthen the warnings. This public would be happy to have all the models they are using, and new additional ones, made available through a single platform, and IPM-Decisions could be the solution.
 

IPM Decisions (IPMD) developed a platform for decision support systems (DSS) available across Europe, at www.platform.ipmdecisions.net. Currently (May 2024) the platform includes more than 25 fully integrated DSS and several linked DSS for diseases and pests in numerous crops. After registering and creating a farm, you select relevant DSS. Based on local weather data, the pest and disease risk is recalculated daily, all in the a traffic light color scheme.  For each DSS you get the results, divided into three parts: a) a graphic showing the risk classification for the last few days and for the next 6 days, b) a graphic of the model-specific risk parameters, c) and a standardized recommendation for treatments for each risk level. A summary of the conclusions for Germany: Even though there have been providers of DSS in Germany for many years, the IPMD platform offers numerous new approaches, in addition to some new pathogen crop models that have not yet been established in Germany. These can be tested and easily adapted to regional conditions using a special “adaptation dashboard”.
 

IPM Decisions developed a platform that gives access to a IPM-DSS across Europe. By May 2024 the platform includes more than 25 fully integrated DSS and several linked DSS for pests and diseases. After registration and the creation of a farm location, relevant DSS can be selected. The platform automatically connects to regional weather information. The output of the DSS is continuously updated and can be  accessed through the 'DSS Use Dashboard', also on a smartphone.  A summary of the conclusions for The Netherlands: Commercial DSS for a number of important crop x pest combinations are available on the market for Dutch farmers for several years. The added value of the IPM Decisions platform for Dutch farmers is that the platform gives free access to DSS developed in other countries, but are relevant for Dutch agriculture. To make sure these DSS are useful for Duch growers, testing of these DSS under Dutch conditions is important.  The platform offers the functionality for this testing work through the 'adaptation dashboard'. The project ends in May 2023, but the platform will stay live: www.platform.ipmdecisions.net
 

IPM Decisions developed a platform that gives access to a IPM-DSS across Europe. By May 2024 the platform includes more than 25 fully integrated DSS and several linked DSS for pests and diseases. After registration and the creation of a farm location, relevant DSS can be selected. The platform automatically connects to regional weather information. The output of the DSS is continuously updated and can be  accessed through the 'DSS Use Dashboard', also on a smartphone.  A summary of the conclusions for The UK: There are ~20 DSS available on the platform which have been produced and/or validated for crop x pest risk determination in the UK. These DSS can be used to determine risk of pest and disease in arable and horticultural crops and provide guidelines on appropriate actions. The platform also gives free access to DSS developed in other countries that are relevant for UK agriculture which can be adapted under the adaptation dashboard on the platform. The project ends in May 2023, but the platform will stay live: www.platform.ipmdecisions.net 
 

"In the EU project “IPM Decisions” a platform for decision support systems (DSS) in Europe has been launched. 
In Denmark, DSS have been available to farmers and advisors for many years. Through CropProtectionOnline (CPO), one can get suggestions for the control of weeds, fungal diseases, and pests in cereal species. Additionally, in “Cropmanager,” one can follow the number of hours with leaf wetness to assess the risk of Septoria attacks. Both the CPO-models and the Septoria humidity model are now also available on the IPM Decisions platform. Many consultants and farmers have visited the platform to see what DSS are available and test how the systems work. Farmers and consultants have used the platform for inspiration but have not followed the recommendations, as many of the systems have not yet been validated under Danish conditions. The idea behind the IPM Decisions platform is to gather available DSS on one platform, where one can set up several farms and choose different DSS, which provides a good overview of the decision support systems at the farm level. The platform may also inspire researchers to develop and adapt models for individual pests to other countries."
 

Integrated pest management (IPM), which combines various measures and technological elements is constantly discussed at farmers, advisers and even political level, especially when it comes to the tasks raised by the European Green Deal. In response to the reduction in the use of plant protection products, a lot of attention is paid to the forecasts of diseases and pests, and the targeted use of plant protection products .During the Horizon 2020 project 'IPM Decisions', a platform was created with the possibility of connection throughout Europe. Farmers and advisers are especially appreciating the possibility to be able to use the information provided on the platform in Lithuanian language as well. In order to be an active participant of the platform, the only necessity is to register and provide information about the fields. The DSS automatically connects to regional meteorological data and, in the event of a risk of disease or pest occurrence, immediately provides information about the situation in a specific field.The 'IPM Decision' platform is attractive to the user, as it provides free access to Decision Support Systems (DSS), which are developed in other countries, but are also relevant in Lithuania. www.platform.ipmdecisions.net
 

"IPM Decisions developed a platform that gives access to a IPM-DSS across Europe. By May 2024 the platform includes more than 25 fully integrated DSS and several linked DSS for pests and diseases. After registration and the creation of a farm location, relevant DSS can be selected. The platform automatically connects to regional weather information. The output of the DSS is continuously updated and can be  accessed through the 'DSS Use Dashboard', also on a smartphone.
A summary of the conclusions for Finland: The platform gives Finnish farmers or other actors free access to a set of European crop protection models, and makes it easy to run models with local weather data. Employing DSS models can make crop health monitoring more effective and pest prevention decisions better grounded. Testing of the models under Nordic conditions is important. The project ends in May 2024 but the platform will stay live at http://platform.ipmdecisions.net"
 

A summary of the conclusions for www.platform.ipmdecisions.net for Sweden: DSS for a limited number of important plant diseases are offered to Swedish advisors and farmers by chemical companies. There are a few commercial systems available, some of which are delivered free of charge by the Swedish Board of Agriculture. In addition the Board of Agriculture have their own web service with a few DSS for the most relevant pests and diseases in a limited number of crops. The IPM Decisions platform, with its free access to DSS in several crop x pest/disease combinations, will complement the current supply of decision support in plant diseases and pest management and has the potential to give a more comprehensive and better support for sustainable plant protection in Sweden. To reach larger proportions of the end user community the trust building process is very important. This includes local validation of DSS and to ensure the longevity of the platform.
 

Norway. The IPM Decisions platform (www.platform.ipmdecisions.net) provides access to decision support systems (DSSs) for integrated pest management from multiple DSS providers across Europe. By May 2024 the platform includes more than 25 fully integrated DSS and several linked DSS for pests and diseases. In addition, 3 DSS are presented in risk maps displaying a European overview of risk prediction. After registration and the creation of a farm location, relevant DSS can be selected. The platform automatically connects to regional weather information. The platform provides solutions for direct use of selected DSS, comparisons or adaptations. The added value for Norwegian users, which have access to many of the DSSs through VIPS (www.vips-landbruk.no), will be to recognize, test and evaluate additional DSS of potential interest for Norwegian agriculture. Other benefits from the IPM Decisions platform, is the potential for integration of DSS into external services. This means that both DSSs and weather data from IPM Decisions can be integrated in the VIPS web service to provide direct access to additional features.  
 

"The IPM Decisions platform, https://www.platform.ipmdecisions.net/, contains crop damage risk. These risk maps show the infection risk of plant pests and diseases across Europe. Currently the risk map for Septoria leaf blotch (Zymoseptoria tritici), the risk maps for pollen beetle (Meligethes aeneus) and the risk map for codling moth (Cydia pomonella) are available. The data is updated throughout the risk season for each pest and the user is able to scroll through the maps by date to see how the risk is changing over time. Attention: It is important to note that the information in the maps is only intended to provide a regional overview of risk based on modelled weather data and will not necessarily be an accurate prediction of risk for an individual crop. As the risk maps will show the risk prediction from a number of decision support tools and the meaning of risk varies between the different DSS. There is an information icon included next to the DSS name, which will provide more details about how the DSS produces its risk prediction. In addition to the risk map, maps of additional outputs relevant to the DSS are also provided. 
"
 

Septoria blotch diseases of wheat can be caused by septoria tritici blotch and staganospora nodorum blotch, which are both favored by wet conditions. The Septoria humidity model estimates risk of septoria tritici blotch infections in winter wheat. Risk of attack is assumed after 20 hours with continuous wetness. A wet hour is defined as minimum 0,2 mm precipitation in an hour or minimum 85% relative humidity. Fungicide treatments may need to be applied between stem extension and ear emergence, mainly to protect the upper leaves. Weather data from GS 31 are used. In addition, the dates of occurrence of growth stages 31 and 32 are entered. The model calculates the expected date for the other crop growth stages. This can be adjusted manually. Adding information on fungicide spraying dates is vital for the model. After spraying, the model assumes that the crop is protected for 10 days. The DSS is created by Aarhus University and SEGES and released in Denmark in 2017. Tested in Lithuania, Norway, Sweden, Finland and Denmark in 2018 and 2019. www.platform.ipmdecisions.net
 

Saddle gall midge is a sporadic pest of cereals, which usually persists at low population levels. Yield loss can be caused by constricted vascular supply to the ears. Pupae overwinter in the soil, from which adults emerge in the spring to lay eggs on vulnerable crops. Once larvae have crawled under the leaf sheath, they cannot be controlled using insecticides.The DSS indicates the best time to monitor crops for infestations (start of emergence). If abundance is high treatment needs to be applied before, or soon after oviposition. DSS assumes the earliest date of emergence of saddle gall midge to be after 500 day degrees. User must undertake in field monitoring to assess the abundance of emerging adults. The DSS starts on the date of first rainfall on or after the 1st March and ends at the end of July. The DSS uses accumulative daily temperature (500-degree days above 0 degrees) and rainfall. This DSS was adapted from work carried out in the UK, and is considered applicable, but not yet validated in, Belgium, Luxembourg, Netherlands, France, Germany, and Denmark. The model is available on www.platform.ipmdecisions.ne 
 

Potato late blight is caused by Phytophthora infestans, that causes the most devastating disease of potato. It spreads rapidly in the canopy, and can also infect tubers. Protective fungicide treatments are needed to protect the crop when conditions for infection are favourable.  The Naerstad model predicts if there are favourable conditions for spore production and the following conditions for spread, survival and infection of these spores. The model uses temperature, humidity, precipitation, wind, radiation, leaf wetness and vapor pressure deficit as input parameters, assuming spores of potato late blight are present. A control measure should be considered based on cultivar resistance, time of last application and choice of fungicide. Risk of infection is highest after several consecutive days with warnings, and especially if late blight has been observed in the area. The DSS was developed by NIBIO in Norway. For other countries it is important to first test in practice before using the DSS. Model is available on www.platform.ipmdecisions.ne. 
 

Potato late blight causes severe damage to the foliage and can infect the tubers at harvest. The DSS 'Negativ prognosis' is designed to guide the timing of the first late blight fungicide application. The DSS uses weather data to estimate the ‘epidemic free’ period (‘negative prognosis’) by calculating the accumulated blight risk from the date of crop emergence. Other agronomic factors than weather, such as time of row closure, cultivar susceptibility, the presence or absence of blight inoculum sources, are not included in the risk estimate. The risk is an accumulated value of how the weather affects late blight germination/infection, sporulation and growth. The DSS was first introduced by Schrodter and Ullrich in Germany in the 1970s and has been widely used in Europe since. After the original paper by Ullrich, J. & Schrödter, H. (1966), the negative prognosis model was tested in other countries (e.g. b y Taylor M. C. 2003 in the UK) and was commonly combined with other models to guide subsequent fungicide applications. The model is available on www.platform.ipmdecisions.net
 

"Females pollen beetles bite oilseed rape buds and lay their eggs inside. Adults and larvae attack buds and flowers, resulting in withered buds and reduced pod set. The pollen beetle migration model runs March-April.  Oilseed rape is only vulnerable if large numbers of pollen beetle migrate into the crop during green bud stage. This DSS predicts migration into crops based on air temperature, and so can be used to evaluate risk to crop. Only crops at growth stage 51 – 59 are vulnerable to damage, the period shortly before flowering: GS51: Flower buds visible from above (‘green bud’ stage)
GS52: Flower buds free and level with the youngest leaves
GS53: Flower buds raised above the youngest leaves
GS55: Individual flower buds visible but closed
GS57: Individual flower buds visible but closed
GS59: Flower buds closed with first petals visible (‘yellow bud’ stage)
It is important to update growth stage in the DSS to indicate current crop growth stage. The model uses Daily maximum air temperature.  This DSS was adapted from work carried out in the UK, and is considered applicable, but not yet validated in other countries, see on www.platform.ipmdecisions.net"
 

The Warwick DSS Pollen Beetle simulates the development of cohorts of 500 individuals through spring emergence, egg laying and hatching, larval and pupal development and emergence, followed by dispersal of the new generation of adult beetles. For each stage, the percentage development is calculated each day by integrating the appropriate development rate curve. This percentage is accumulated over days until it reaches 100. At this point the individual moves to the next stage. As multiple cohorts progress simultaneously, adult emergence/dispersal and egg laying can occur at the same time. The DSS requires hourly soil temperatures at a depth of 6 cm and hourly air temperatures. This model requires historic data to provide risk forecasts. This enables users to undertake targeted monitoring and/or mitigating actions to reduce the risk of damage to the crop. The start date for the model is 1st February, as this is often the coldest period in the year. This DSS was adapted from work carried out in the UK. At present, suitable historic data is only available for a limited number of locations. The model is available on www.platform.ipmdecisions.net 
 

This Large Narcissus Fly Model predicts the timing of adult emergence, egg laying and egg hatching, enabling users to undertake targeted monitoring and/or mitigating actions to reduce the risk of damage to the crop. The model simulates the development of cohorts of 500 individuals through adult emergence, egg laying and hatching. The model uses soil temperatures or air temperatures depending on the stage of development. The start date for the model is 1st February, as this is often the coldest period in the year. The DSS shows information about the development of the large Narcissus fly during the growing season. The Large Narcissus Fly forecast requires hourly soil temperatures at a depth of approximately 6 cm and hourly air temperatures. This model requires historic data to provide risk forecasts. At present, suitable historic data is only available for a limited number of locations; please select ‘Edit Parameters’ and select the most appropriate location. The DSS Large Narcissus Fly Model was developed at University of Warwick (Warwick Crop Centre) and was adapted from work carried out in the UK. The model is available on www.platform.ipmdecisions.net 
 

Potato late blight can cause severe damage to potato leaves and tubers. Potato late blight is a disease caused by a fungus-like organism that spreads rapidly in the potato crop canopy and can also infect tubers. This model runs during the potato growing season and relevant as soon as the crop emerges. The model determines when weather conditions create high risk of infection, to guide targeting of fungicide treatment. The model uses daily air temperature and humidity. A high risk ‘Hutton Criteria’ period occurs when two consecutive days have a minimum temperature of 10°C, and at least six hours of relative humidity at or above 90%. Susceptibility of varieties is not taken into account. The risk information can be used for the timing of fungicide applications. Information about properties of fungicides is available through Euroblight, a potato late blight network for Europe: https://agro.au.dk/forskning/internationale-platforme/euroblight/control- strategies/late-blight-fungicide-table This DSS was adapted from work carried out in The UK and is not tested yet in other countries yet. The model is available on www.platform.ipmdecisions.net 
 

Grey field slug is the most important slug pest in oilseed rape. The most damage to oilseed rape occurs during the establishment phase. They thrive in humid conditions. In most cases, they reside in the soil up to 10 cm deep and are 3 to 5 cm in length. Seedbeds with clods  are likely to be damaged. If, on average, there are one or more slugs per trap; the risk of slug populations over threshold is high and management action is needed. In vulnerable crops, continue to monitor slug abundance and consider treatment options where crops require additional protection. Traps should be placed in standing crops or in stubble over a one-night period from May to October when weather conditions such as temperatures between 5 -25 degrees and moist soil surfaces occur. Slugs should be counted before temperatures rise and they leave refuge traps. The trapping should continue until the vulnerable stage of the crop has passed. Crops are considered to be at risk of economic damage where an average of one or more slugs are found per refuge trap. The DSS is developed by ADAS, England. For other countries it is important to first test in practice before using the DSS on www.platform.ipmdecisions.net. 
 

Grey field slug are the most important slug pest in cereals where they causing over 95% of. They thrive in humid conditions. They reside in soil up to 10 cm deep and are 3 to 5 cm in length. Seedbeds with clods are likely to be damaged by slugs most. Slug refuge traps should be placed in standing cereal crops or in stubble over a one-night period from May to October when weather conditions such as temperatures between 5 -25 degrees and moist soil surfaces occur. Slugs should be counted before temperatures rise and they leave refuge traps. The trapping should continue until the vulnerable stage of the crop has passed. Crops are considered to be at risk of economic damage where an average of four or more slugs are found per refuge trap. Number of slugs in the traps need to be monitored. Number of slugs per trap are to be included in the DSS under ‘Parameters’. The DSS is developed by ADAS, England. For other countries it is important to first test in practice before using the DSS. The model is available on www.platform.ipmdecisions.net 
 

"Leaf blotch diseases of wheat can be caused by septoria tritici blotch  and staganospora nodorum blotch, favoured by wet conditions. Fungicide treatments may need to be applied between stem extension and ear emergence. Weather data from GS 31 are used. Risk of attack is assumed after 20 hours with continuous wetness. A wet hour is defined as minimum 0,2 mm precipitation in an hour or minimum 85% relative humidity. The assumption is that septoria tritici blotch is present in the crop and periods with high humidity create risk for a damaging epidemic. Dates of key growth stages must be included for your location. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button, enter the estimated dates. These estimated dates can be updated during the season as growth stages are reached. Adding information on fungicide spray dates is vital for the model. After spraying, the model assumes that the crop is protected for 10 days.
DSS is created by Aarhus University and SEGES and released in Denmark in 2017. Tested in Lithuania, Norway, Sweden, Finland and Denmark in 2018 and 2019. The model is available on www.platform.ipmdecisions.net "
 

"Downy mildew results in severe loss in grapevines. Downy mildew is  caused by the fungus Plasmopara viticola, firstly appear on the grape leaves 7-10 days after infection. Foliar symptoms appear as yellow circular spots with an oily appearance (oil spots). In order to control the pathogen, approved pesticides are used.
The model estimates infection using cardinal temperatures (Tmin, Topt, Tmax) and leaf surface wetness duration requirements for infection. The model is based upon a temperature response function which is scaled to the leaf wetness duration requirement. Hours of interruption to wetness are also important for estimation of infection from hourly weather data so this is also used as an input. 
The DSS is created in Greece and part of the integrated “Gaiasense” smart-farming solution. The prediction model is developed based on literature reviews and adaptations through experiments and observation on local conditions. This means that the model is not yet validated in other countries and results should be treated with caution."
 

Orange wheat blossom midge larvae feed on developing grains. The larvae can cause grains to become small and shrivelled. They can also damage the outer grain layer, this can result in fungal infection and premature sprouting.  The susceptible crops are at highest risk when adult midge emergence coincides with ear emergence, particularly at growth stages between 53 and 59. The model predicts the emergence of adults and associated migration of females into vulnerable crops and when increased monitoring and/or treatment may be appropriate. The model uses daily temperature (degree Celsius) and rainfall (mm) to identify the emergence. It runs between the months May and June, but requires weather data from the 1st of January. Suitable rainfall events have taken place, and/or daily temperatures are suitable for orange wheat blossom midge emergence which is visualised as a red line in the risk status diagram. This means that increased monitoring efforts or treatments may be appropriate. This DSS was adapted from work carried out in Belgium, and is considered to be applicable, but yet to be validated in other countries. The model is available on www.platform.ipmdecisions.net 
 

Cutworms can cause damage to a range of crops. Cutworm are caterpillars of a few species of moth that feed at the base and roots of crops. Eggs are laid in late spring, and the first three instar feed on surface vegetation, before burrowing into roots. Once they’ve moved into the roots, they cannot be controlled using insecticides. This DSS assumes first arrival of adult moths to be 1st June. Significant rainfall events cause high levels of mortality in larvae, which is included in the model. The models ends on the 31st October. Any spray dates can be inputted into the model and are deemed to be 100% effective. The DSS predicts the number of instar 1, 2 or 3 larval batches that could be active in the crop. When 4 or more batches are predicted, treatment is recommended to prevent high numbers of larvae moving into the crop roots. This DSS was adapted from work carried out in the UK, and is considered applicable, but not yet validated in, Belgium, Luxembourg, Netherlands, France, Germany, Rep. Ireland, and Denmark. The model is available on www.platform.ipmdecisions.net.
 

The CPO yellow rust model is recommending treatments in wheat. The risk of attack is based on visual monitoring using frequency of plants attacked. The disease observation is the percentage of plants showing any infection. If treatments are recommended specific fungicides should be chosen. If no action is recommended it is advised to revisit the crop after approximately one week to make a new evaluation of the risk. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar ’s susceptibility. Only two categories are used susceptible and resistant.  The model does not automatically adjust the risk for the effect of previous fungicide sprays. If a fungicide effective against yellow rust has been applied within the previous ten days, the risk can be interpreted as low. Created by Aarhus University and SEGES and released in Denmark in 2000. This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support. The model is available on www.platform.ipmdecisions.net.
 

"The CPO tan spot model is recommending treatments in wheat The risk of attack is based on visual monitoring using frequency of plants attacked. The disease observation is the percentage of plants showing any infection. If treatments are recommended specific fungicides should be chosen. If no action is recommended it is advised to revisit the crop after approximately one week to make a new evaluation of the risk. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar’s susceptibility to tan spot. Only two categories are used susceptible and resistant, if a cultivar is categorized as partly resistant, it is recommended to consider it as susceptible. The model does not automatically adjust risk for the effect of previous fungicide sprays. If a fungicide effective against tan spot has been applied in the last 10 days, the risk can be interpreted as low.
The DSS is created by Aarhus University and SEGES and released in Denmark. This model may be of use in other countries, it is important to first test in practice before using the DSS. This model is available on www.platform.ipmdecisions.net. "
 

"The CPO Septoria model estimates risk of Septoria tritici blotch infections in winter wheat. Weather data from GS 32 to GS 69 are used. Spraying is recommended after minimum 4 days with rain (> 1 mm) in susceptible cultivars counting days between GS 32 and GS 69. In resistant cultivars risk of attack is assumed after 5 days with rain between GS 37 and GS 69. Counting of days with rain goes back a maximum of 30 days. If no action is recommended, it is advised to revisit the crop after approximately one week to make a new evaluation of the risk. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar’s susceptibility to Septoria diseases. The model does not automatically adjust for the effect of previous fungicide sprays. If a fungicide has
been applied in the last 10 days, the risk can be interpreted as low.
The DSS is created by Aarhus University and SEGES and released in Denmark in 2000. This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support. The model is available on www.platform.ipmdecisions.net"
 

The CPO powdery mildew model recommends treatments in wheat. The risk of attack is based on visual monitoring using frequency of plants attacked. The disease observation is the percentage of plants showing any infection. If treatments are recommended specific fungicides should be chosen. If no action is recommended it is advised to revisit the crop after approximately one week to make a new evaluation of the risk. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar’s susceptibility to powdery mildew. The model does not automatically adjust the risk for the effect of previous fungicide sprays. If a fungicide has been applied within the previous 10 days, the risk can be interpreted as low. The DSS is created by Aarhus University and SEGES and released in Denmark in 2000.  This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support. The model is available on www.platform.ipmdecisions.net
 

The CPO powdery mildew model is recommending treatments in barley. The risk of attack is based on visual monitoring using frequency of plants attacked. The disease observation is the percentage of plants showing any infection. If treatments are recommended, specific fungicides should be chosen. If no action is recommended it is advised to revisit the crop after about one week to make a new risk evaluation. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button to enter information on the cultivar ’s susceptibility to powdery mildew. The model does not automatically adjust risk for the effect of previous fungicide sprays. If a fungicide effective against mildew has been applied in the last 10 days, the risk can be interpreted as low. The DSS is created by Aarhus University and SEGES and released in Denmark in 2000. This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support. The DSS is avilable on www.platform.ipmdecisions.net. 
 

The CPO brown rust model in wheat recommends treatments in wheat when thresholds are exceeded. The risk of attack is based on visual monitoring using frequency of plants attacked. The disease observation is the percentage of plants showing any infection. If treatments are recommended specific fungicides should be chosen. If no action is recommended it is advised to revisit the crop after approximately one week to make a new evaluation of the risk. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar’s susceptibility to brown rust. The model does not automatically adjust the risk for the effect of previous fungicide sprays. If a fungicide has been applied within the last 10 days, the risk can be interpreted as low. If a fungicide has been applied in the last 10 days, the risk can be interpreted as low. The DSS is created by Aarhus University and SEGES and released in Denmark in 2000. This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support. THe model is available on www.platform.ipmdecisions.net
 

The CPO brown rust model is recommending treatments in barley when thresholds are exceeded. The risk of attack is based on visual monitoring using frequency of plants attacked. If treatments are recommended, specific fungicides should be chosen. If no action is recommended it is advised to revisit the crop after approximately one week to make a new evaluation of the risk. To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar ’s susceptibility to brown rust. The model does not automatically adjust risk for the effect of previous fungicide sprays. If a fungicide effective against brown rust has been applied in the last 10 days, the risk can be interpreted as low. The DSS is created by Aarhus University and SEGES and released in Denmark in 2000. The whole CPO model has been tested in the Nordic and Baltic countries previously, but this might not have included testing of the specific brown rust part. This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support. The model is available on www.platform.ipmdecisions.net 
 

"The CPO net blotch model is recommending treatments in barley when thresholds are exceeded. The risk of attack is based on visual monitoring using frequency of plants attacked. The disease observation is the percentage of plants showing any infection. For example, if 25 plants out of 100 show even a very small amount of disease and the remaining 75 plants are completely healthy, then the observation is 25%. In susceptible cultivars treatments are recommended at lower incidence levels than in resistant cultivars. If treatments are recommended specific fungicides known to be effective against net blotch should be chosen. When running the net blotch model, the risk for yield losses from other diseases is not considered. If no action is recommended it is advised to revisit the crop after approximately one week to make a new evaluation of the risk.
To obtain accurate risk predictions it is essential to click on the ‘Edit parameters’ button and enter information on the cultivar’s susceptibility to net blotch. The model does not automatically adjust risk for the effect of previous fungicide sprays. If a fungicide effective against net blotch has been applied in the last 10 days, the risk can be interpreted as low.
Created by Aarhus University and SEGES and released in Denmark in 2000. The whole CPO model has been tested in the Nordic and Baltic countries previously, but this might not have included testing of the specific barley net blotch part. This model may be of use in other countries in Northern Europe, it is important to first test in practice before using the DSS for decision support."
 

The larvae emerged from eggs laid by the codling moth fruit cause damage to apples, pears and other pome fruit. The DSS Codling moth flight model on platform.ipmdecisions.net, predicts the start of adult codling moth flight, enabling users to undertake targeted monitoring and/or mitigating actions to reduce the risk of damage to the crop. A 3-parameter non-linear regression model fits cumulative moth captures as a function of accumulated day degrees for all three of the male flights. The model predicts that 1st migration begins after 151 day degrees, 2nd migration begins after 673 day degrees and 3rd migration begins after 1303 day degrees. The start of migration events are reported in the DSS warning to the user. The model uses minimum and maximum temperature from the 1st of January. The DSS output gives information about the risk of codling moth migration. The ‘Cumulative Captures’ chart indicates the predicted accumulative proportion (%) of adult males likely to be caught by these dates. This DSS was adapted from work carried out in Greece, and is considered applicable, but not yet validated in other countries, see on www.platform.ipmdecisions.net 
 

Carrot rust fly can cause damage to carrots and some other crops. The first generation of adult carrot fly emerge from pupae in the soil in the spring, and lay eggs close to the base of vulnerable crops. Larvae initially feed at the surface, then tunnel into the tap root. Adults emerge mid-July and can lead to a second generation. Treatments may need to be applied soon after adults arrive in the crop, before larvae tunnel into the crop roots. The DSS determines the start of the flight period for the 1st generation of carrot rust fly based on accumulated degree-days (260 day-degrees) over a base temperature of 5°C. The model uses daily air temperature; the default starting day is 1 March. The DSS shows accumulated day degrees after 1 March and thresholds for the start of the flight period and the threshold for the peak of the flight period. When the first flight is expected, placing yellow sticky traps in the field is recommended to monitor if the flies indeed are present in the field. The DSS was developed by Luke, Finland, and is considered applicable, but not yet validated in other countries, see on www.platform.ipmdecisions.net
 

The Carrot Fly model simulates the development of cohorts of 500 individuals through adult emergence, egg laying and hatching. For each stage, the percentage development is calculated each day by integrating the appropriate development rate curve. This percentage is accumulated over days until it reaches 100. At this point the individual moves to the next stage. Variability within the insect population is incorporated by assuming that the rates of development of a population held at a constant temperature are normally distributed . The model uses soil temperatures or air temperatures depending on the stage of development. As multiple cohorts progress simultaneously, adult emergence and egg laying can occur at the same time. The DSS requires hourly soil temperatures at a depth of approximately 6 cm and hourly air temperatures. This model requires historic data to provide risk forecasts. Such historic data is only available for a limited number of locations. The start date for the model is 1st February , as this is often the coldest period in the year. This DSS was developed by the University of Warwick, UK. DSS is accessible on www.platform.ipmdecisions.net 
 

"The Cabbage Root Fly model uses soil temperatures or air temperatures depending on the stage of development. Within the model it is possible to specify the proportions of the early and late emerging biotypes in the simulated population. As multiple cohorts progress simultaneously, adult emergence and egg laying can occur at the same time. The Cabbage Root Fly forecast requires hourly soil temperatures at a depth of approximately 6 cm and hourly air temperatures. This model requires historic data to provide risk forecasts. At present, suitable historic data is only available for a limited number of locations; please select ‘Edit Parameters’ and select the most appropriate location. The start date for the model is 1st February , as this is often the coldest period in the year.
The DSS gives information about the risk of adult cabbage root fly flight activity. 
This DSS was developed by the University of Warwick (Warwick Crop Centre), England and adapted from work carried out in the UK. This model requires historic data to provide risk forecasts. At present, suitable historic data is only available for a limited number of locations. DSS is accessible on www.platform.ipmdecisions.net "
 

The model for the warning system for cabbage moth is based on the minimum temperature threshold and the requirement for accumulated day-degrees for the different stages of the cabbage moth. The accumulated degree-day model calculates forecasts for development of the cabbage moth through the summer, generates warnings for the time when eggs and small larvae can be registered in the field and the best time for treatment. The model uses soil temperature at a depth of 10 cm as a parameter. This means that it is not related to the presence or absence of cabbage moth in the field. The DSS gives information about the risk of cabbage eggs and small larvae that can be registered in the field and the best time for treatment. Yellow rectangles indicate that oviposition has begun and the farmer should make observations in the field. Red rectangles indicate the optimal time for treatment. Most larvae are small at this point and easily targeted on the outer leaves.Where can DSS be used. The DSS is created by NIBIO which is based in Norway. In order to work with this DSS, soil temperature at a depth of 10 cm should be available in the country of use. DSS is accessible on www.platform.ipmdecisions.net 
 

The cabbage fly flight model determines the start of egg laying as 160 degree-days based on the soil temperature (10 cm) or based on the standard air temperature (2 m above the soil surface) at the same location. Egg laying starts at 210 degree days. This model should be used in combination with direct observations of eggs in the field. This due to the large variability and to get an idea of the severity of the attack. The model uses daily soil or air temperature as a parameter. In areas with early crops the preceding season, the flight period can start earlier due to higher so il temperature under the covers.The DSS gives information about the risk of adult cabbage root fly flight activity. It can be seen that at 210 degree days (which is the upper threshold value), the risk of flight activity is high and it is likely that egg laying has begun on vulnerable brassica crops. Action should be taken to protect the crop, taking into consideration the observations in your own field.The DSS is created by NIBIO which is based in Norway and accessible on www.platform.ipmdecisions.net 
 

"The DSS Alternaria in potato is a weather-based model, derived from a model originally developed for leaf spot diseases in tomato. Fungicide treatments may be needed to protect the crop when the lower or high threshold value for Aggregated Daily Disease Severity Value (DSV) is reached. When a fungicide is applied and entered into the DSS,, DSV is reset and starts over at 0.
The model uses temperature and leaf wetness as input parameters.  DSV represents the risk of attack of early blight the previous 24 hours. Daily values of DSV are accumulated until a threshold value is reached, and treatment is recommended.
It is important to check and adapt the default DSS parameters to the location where used:
1. Start day of the control period, standard value is the first of March.
2. End day of the control period, depending on the length of the growing season.
3. Fungicide applications against early blight. 
The DSS is tested and adapted to be used against early blight in potato in Denmark and Norway. For other countries it is important to first test in practice before using the DSS for decision support in the control of potato early blight. DSS available on www.platform.ipmdecisions.net"
 

"On platform.ipmdecisions.net you find a DSS for the BYDV. This DSS assumes that the user will update the date of emergence and last insecticide application. When no aphids are found in the field at T-Sum 170 DD, or after insecticide application, a new calculation starts. It is important to set the parameters correctly, as the model uses the parameter settings for the calculation of the risk status: crop emergence date. The T-sum calculation starts from this date. Risk will be under estimated if the input start date is too late. Risk will be overestimated if the input start date is too early. The model provides risk information up to growth stage 31. The DSS gives information about the risk of winged aphids being present in the field and spreading the virus. The DSS display; the T -Sum of the current day, the prediction for the development of the T-Sum over the coming days, and the expected date of reaching the threshold of 170 DD, which is associated with the emergence of winged aphids. The DSS was adapted from research carried out in the UK, and is considered applicable, but not yet validated, in Belgium, Luxembourg, Netherlands, France, Germany, Republic Ireland and Denmark."