Crop Protection Online (CPO)

Transcription

1 Crop Protection Online (CPO) Requirements for implementation of CPO-weeds in a new country January Index 1 Driving forces In the past In the future 2 2 System description Concept idea Main functions Research backbone IT backbone Major obstacles and bottlenecks 3 3 System export Previous experiences Principal conditions Required work Cost 5 4 Contacts 6 5 Selected literature 6 Page 1 Driving forces 1.1 In the past In Denmark, a series of political action plans aiming for reductions in pesticide use, have been launched since The actual plan specifies that the so-called Treatment Frequency Index (TFI) must be reduced to a national level of 1.7, before TFI = 1,0 means one full dose of a registered pesticide product, and TFI can be summarized for treatment programmes on a farm level and national levels throughout a growing season. Page 1 of 6

2 Political action plans have been a driving force behind the development of Crop Protection Online (CPO) (Henriksen et al., 2000; Rydahl et al, 2003; Rydahl, 2004) 1.2 In the future I EU, Directive 2009/128/EC provides specifications for the implementation of Integrated Pest Management (IPM) before This directive includes many principles and instructions, which shall subsequently be transformed into more concrete actions plans on the national level. CPO already complies with many of these requirements: application of herbicides according to economic thresholds application of herbicides which are targeted for the purpose and if possible with a reduced input application of herbicides in compliance with herbicide anti resistance strategies (so far only on the tactical level on biotypes that has gained specific resistance) In the coming years, CPO will be expanded to integrate: control strategies, which do not promote further development of weed biotypes, which are resistant to specific herbicide mode-of-action. New decision algorithms, which integrate historical information of herbicide use on a field level in actual, tactical decisions, is presently being designed non-chemical preventive and curative control measures. According to Directive 2009/128/EC, such control measures must be preferred, when sufficiently effective and not too expensive. Such decision algorithms are presently being designed 2 System description 2.1 Concept idea Often, attacks of weeds, pests and diseases vary considerably between fields and in time. A major concept idea behind CPO is that the total use of pesticides can be significantly reduced without jeopardizing the robustness in the production, if the use of pesticides can be adjusted to topic conditions on a field level. Furthermore, while some weed species may be tolerant to the registered dose of a herbicide, other weed species may be controlled sufficiently by down to 5-10% of a registered herbicide dose rate (TFI = 0,05-0,10) (Rydahl, 2004). CPO can recommend input of herbicides ranging from this low level of input up to tank-mixes of 4 herbicides, each in the registered dose rate (TFI=4,0). In this way CPO recommend herbicide use, which may vary 4,0/0,05=80 times in terms of intensity, and consequently, CPO can find recommendations for weed control for both simple and complex weed infestations, of course the latter being only for emergency cases, where a special treatment is necessary to restore the opportunities for continuing the growing. Compared to Danish best practice weed control strategies, which are often recommended in a regional scale, CPO has a potential for reducing the input of herbicides. In crops that compete strongly with weeds like e.g. cereals and grasses, at least 40% reduction has been demonstrated as compared to best practice recommendations (Rydahl, 2004). In row crops like e.g. maize or peas, about 20% reduction has been demonstrated. Page 2 of 6

3 2.2 Main functions CPO is a so-called decision support system (DSS), which has been developed to support decisions on pesticide use. CPO has been released in Denmark since Based on a field-report which specifies crop name, crop growth stage and actual infestation of weeds, pests and diseases, CPO will match this information with models on economic thresholds for treatments and models on the efficacy of pesticides. If thresholds are exceeded, CPO will present a list of treatment options, which will control the reported weeds, pests and diseases to a satisfactory level, and which has been minimized for costs or, alternatively, for the TFI. This calculation engine also runs other calculation tools, which can provide overviews of efficacy of single herbicides and mixtures in different conditions. 2.3 Research backbone Based on: a) models, which quantify the need for control of weeds, pests and diseases in a particular field and b) measured efficacy of pesticides in various dose rates against various weeds, pests and diseases and field conditions, CPO can quantify the need for control of weeds, pests and diseases in a field an suggest treatment options. Dose/response functions are used to find treatment options of single pesticides, and the so-called Additive Dose Model (ADM) is used to calculate mixes of herbicides that match specific weed compositions and conditions. Dose rates will be minimized for cost, or alternatively, for the TFI. 2.4 IT backbone CPO consists of several interactive tools on the Internet. These tools are driven by a set of inter related data bases. Different versions for prototype version and for released versions can be managed by setting up separate databases. At all times, only one structural version will be used and the integrated source code will run prototypes as well as released versions in different countries. The agronomic content of CPO including user interface language(s) can be customized for national and subnational conditions by editing integrated databases. Presently, the source-code running the applications has programmed in JAVA, ASP and ASP.NET, which integrate MS SQL Server databases. 2.5 Major obstacles and bottlenecks Presently, about 1,000 out of 15,000 professional Danish farmers are subscribing to CPO. Furthermore, practically all consultants, all agrochemical companies and dealers are subscribing too. CPO has also been integrated in the examination criteria in schools for young farmers and in educations for master degrees. In order to fully exploit the potentials in CPO to reduce input of pesticides, it is important that pesticides are used according to registrations from field inspections. As farmer s consultants cannot overcome this task, it is crucial that farm staff will do field inspections. Danish farmers have high confidence in recommendations from CPO, but they do not have time for conducting field inspections. Instead, general recommendations, which are often provided on a regional scale, will often be followed (Jørgensen et al, 2008). In order to customize CPO for national conditions sound data on the efficacy of single herbicides in different dose rates, e.g. 1/4, ½ and 1/1 of the registered dose, are required. Such data are, Page 3 of 6

4 however, often sparse or often with a restricted public access, which may seriously obstruct opportunities for customizing CPO. 3 System export 3.1 Previous experiences CPO has been developed by Aarhus University, Faculty of Agricultural Sciences in collaboration with the Danish Agricultural Advisory Service. In , the CPO system was also adapted for conditions in the Baltic States and Poland (Høstgaard et al. 2003). Since 2003, Aarhus University and BioForsk i Norway have been collaborating to develop a Norwegian version of the weed-tools in CPO (Tørresen et al., 2004). These previous activities show that the principles for decision algorithms and calculations functions contain generic qualities, which make these suitable for customization for arbitrary combinations of geography, crops, weed species, herbicides and conditions. 3.2 Principal conditions In order to implement CPO in a new country, local partners who have a detailed scientific knowledge on chemical control of weeds, pests and diseases, must take responsibility for the customization of CPO for local conditions. AU will support all processes as required. Results from local field- and semifield tests of reduced dose rates must be available to establish continuous dose-response functions. Exchange and pooling of relevant efficacy data between neighbouring countries and regions could be exploited for mutual benefit. CPO-prototypes should be constructed and tested locally for robustness and potentials, and such tests should also enable fine-tuning of model functions. Experiences in different countries show that satisfactory levels of robustness have achieved in all cases, but potentials for reduction of pesticide use strongly depend on the extent and quality of experimental data, which is available for parameterisation and customization. A returning obstacle has been availability of data on the efficacy of reduced dosages. CPO is not an out-of-the-box system. As such, the financial conditions concerning customisation of CPO in a new country will be negotiated individually depending on specific needs for support in the short term and in the long term. A basic fee for maintenance and hosting must be expected. 3.3 Required work To initiate customization of CPO for a new country, the following work steps may be considered: Initially, a 1-2 day workshop should be convened to allow local stakeholders (researchers, advisors, sponsors) to get a deeper insight in principles behind decision algorithms and calculation functions in CPO and underlying research. In case interest is identified a 3-4 year collaboration project may be set up between AU and local partners. A collaboration project may include the following work steps: Page 4 of 6

5 o A local person (or group of persons), which have detailed insight in interactions between local crops and weeds and herbicides should be appointed to take full responsibility of the customization of CPO for local conditions o joint 3-5 day workshops to analyse the system architecture that runs CPO in light of local (national) laws, agricultural practices, availability of local data on herbicide efficacy. In case serious conflicts are identified, activities could be stopped, or specific activities could be designed (and financed) to meet special local requirements o a number of crops, weeds, herbicides and conditions should be selected for construction of initial CPO prototypes (a stepwise or long-term approach may be selected) o existing on herbicide efficacy from historical field and semi-field trials should be collected and organized in ways that are suitable for calculation of estimates of parametners in CPO o if necessacary, supplementary data on herbicide efficacy should be produced o construction of 2-3 prototypes of CPO, which have been parameterized on basis of local data. These prototypes should reflect different levels of target efficacy on the weeds. These prototypes could be in English plus local languages of user-interface as required o local field plot trials should be conducted for at least 2 years to test robustness and potentials of recommendations made by CPO prototypes. Reference tests should be made of local best practice recommendations. Specific adjustments of prototypes could be implemented after test year 1 o based on results from 2 years local field tests, prototypes should be evaluated for robustness and potential, and plans for release and possible future developments could be made. The content in local versions of CPO could be improved by adding: crops weed species herbicides agronomic conditions tools 3.4 Cost Costs include local work and work by AU. In principle, AU will charge cost according to the amount of time used by employees in AU, and exact cost will be charged according to the number of herbicides and crops that are integrated in local customizations of CPO. These costs include: Hosting fee of CPO on servers in AU Access to get locally customized versions of all present and all future tools that are developed in the CPO system architecture Assistance to calculate estimate of parameters in all functions and algorithms on basis of local data Administration of databases that contain all definitions, estimates of parameters construction and test of operational prototypes of CPO Page 5 of 6

6 1-2 annual, 2-4 day local workshops + remote collaboration by internet as required day-by-day maintenance of released versions of CPO 4 Contacts In case additional information is required please contact: Per Rydahl, Aarhus University (agronomic aspects of CPO: per.rydahl@agrsci.dk Phone: / Ole Q Boejer, Aarhus University (IT-aspects of CPO) ole.bojer@agrsci.dk Phone: Per Kudsk, Aarhus University (weed research behind CPO) per.kudsk@agrsci.dk Phone: / Selected literature Henriksen. K.E., Jørgensen, L.N. & Nielsen, G.C PC-Plant Protection - a tool to reduce fungicide input in winter wheat, sinter barley and spring barley in Denmark. Brighton Crop Protection Conference. Pest and diseases Høstgaard, M.B., Hagelskjær, L., Hansen, J.G., Hansen, L.M., Jørgensen, L.N., Lassen, P., Rydahl Nielsen, P., Thysen, I. & Wolffhechel, H., Validation and adaptation of a Danish Decision Support System for crop protection in Lithuania, Estonia, Latvia and Poland. In: Wolffhechel, H. (ed.). Proc. Crop Protection Conf. for the Baltic Sea Region, April Poznan. DIAS report Plant Production 96, Jørgensen LN, Noe E, Nielsen GC, Jensen JE, Ørum JE, Pinnschmidt HO (2008). Problems with disseminating information on disease control in wheat and barley to farmers. Eur J Plant Pathol, 121, Rydahl, P., A Danish decision support system for integrated management of weeds. Aspects of Applied Biology 72, Advances in applied biology: providing new opportunities for consumers and producers in the 21st century, Rydahl, P., Hagelskjær, L., Pedersen, L. & Bøjer, O.Q., User interfaces and system architecture of a web-based decision support system for integrated pest management in cereals. Paper presented at the EPPO Conference on Computer aids for plant protection, York (GB), October 2002, Tørresen, K.S., Netland, J. & Rydahl, P., Norsk utgave av det danske beslutningsstøttesysstemet Plantevern Online for ugrassprøyting i korn. Grønn kunnskap 8(2), Page 6 of 6