Article

A web‐based decision support system for integrated management of weeds in cereals and sugarbeet*

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Abstract

A Danish decision support system (DSS) named Crop Protection Online (CPO) for integrated management of weeds in cereals and beet has been developed during the past 20 years. CPO is based on a model that runs in three main steps: model step 1 quantifies the level of weed control needed on a field level, model step 2 selects candidate herbicides and calculates dose rates to meet the need, and model step 3 calculates tank mixtures of herbicides with two to four mixing components, if advantageous. CPO has been developed in cereals and beet, and various prototype versions have been validated in 1679 field tests. CPO secured yield potentials, and the level of residual weeds was not increased when compared with reference treatments. The potential of CPO to reduce herbicide use has been observed in all model crops, but the potential was greatest in cereals. In spring cereal field trials highly infested with weeds, the present version of CPO suggested 35% of one full herbicide dose on average and in winter cereals CPO suggested 44% on average of one full dose. The results from validation trials demonstrate that CPO is capable of suggesting robust treatment options with a low input of herbicides. The system architecture of CPO has been exported to Poland and the Baltic countries, and the system is expected to be suitable for export to other countries too.

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... • In Denmark, at least 40% in cereal crops and 20% in crops sown in a wide row distance like sugar beet and maize (Rydahl 2003;Sønderskov et al. 2014). • In Norway, about 30% mainly in spring cereal crops (Netland 2005). ...
... A general challenge, in order to achieve a more rational use of herbicides, is the estimation in a simple and quick way of both the need for weed control and the expected efficacy of control measures. To achieve this goal, since the 1980s, scientists from Aarhus University began to develop what is now the most widely used DSS for IWM in Europe, the Crop Protection Online-Weeds (Rydahl 2003). It was initially designed only for spring cereals, such as spring barley (Rydahl and Pedersen 2003) and it was first released in 1989 and further commercialised since 1991 (Rydahl 2003;Kudsk 2008a, b). ...
... To achieve this goal, since the 1980s, scientists from Aarhus University began to develop what is now the most widely used DSS for IWM in Europe, the Crop Protection Online-Weeds (Rydahl 2003). It was initially designed only for spring cereals, such as spring barley (Rydahl and Pedersen 2003) and it was first released in 1989 and further commercialised since 1991 (Rydahl 2003;Kudsk 2008a, b). ...
Chapter
Integrated weed control is mandatory in the current legislative framework for sustainable plant protection programmes. The advent of synthetic pesticides in the 1950s allowed farmers to simplify cropping systems and forego more complicated crop protection strategies, especially in cereal production. Moreover, the awareness of the necessity to decrease pesticide use has been raised considerably since the mid-1980s in Europe. In this work, a Danish Decision Support System (DSS) for Field-Specific Crop Management is presented. This DSS, known as Crop Protection Online (CPO) and later IPMwise, optimizes herbicide weed control by providing recommendations of specific herbicide solutions to achieve a required control level. It has been developed since the 1980s, and the actual version (IPMwise) has recently been adapted to the edaphic and climatic conditions of Spain.
... In Denmark, more than 30 crops and 100 weed species were investigated by means of the DSS "IPMwise" and suggestions for herbicide applications along with recommendations for non-chemical weed control were made [23]. There is clear evidence that herbicide inputs can be decreased in major crops by applying herbicides according to the suggestion of such DSSs [24,25]. Both farmers and advisors can significantly benefit from the use of a DSS for weed control. ...
... For instance, DSS methodologies have been reported to have achieved comparisons of the densities of all weed species into a common basis and consequently predict possible yield losses for the crop due to weed competition [18]. A functional DSS can also quantify the level of the weed control needed on a field level, select the appropriate herbicides and the required rates for a satisfactory weed control, and also estimate the proportion of the individual herbicides in tank mixtures [24]. Synergistic and antagonistic effects between the mixture components can also be detected [32] and this is among the most important information for farmers. ...
... The impact of the DSS technology on reducing herbicide use by approximately 40%, as compared to reference herbicide treatments, has been well established [25]. Efficient weed control has been recorded at over a 30% decreased herbicide use in cereals by applying herbicides according to the suggestion of a DSS, whereas in sugar beet, the advice from a DSS decreased the herbicide input up to 20% [24]. Moreover, herbicide inputs can be decreased up to 60% in cereals if spraying is carried out according to the collection of site-specific data [37]. ...
Article
Full-text available
Decision support systems (DSS) have the potential to support farmers to make the right decisions in weed management. DSSs can select the appropriate herbicides for a given field and suggest the minimum dose rates for an herbicide application that can result in optimum weed control. Given that the adoption of DSSs may lead to decreased herbicide inputs in crop production, their potential for creating eco-friendly and profitable weed management strategies is obvious and desirable for the re-designing of farming systems on a more sustainable basis. Nevertheless, it is difficult to stimulate farmers to use DSSs as it has been noticed that farmers have different expectations of decision-making tools depending on their farming styles and usual practices. The function of DSSs requires accurate assessments of weeds within a field as input data; however, capturing the data can be problematic. The development of future DSSs should target to enhance weed management tactics which are less reliant on herbicides. DSSs should also provide information regarding weed seedbank dynamics in the soil in order to suggest management options not only within a single period but also in a rotational view. More aspects ought to be taken into account and further research is needed in order to optimize the practical use of DSSs for supporting farmers regarding weed management issues in various crops and under various soil and climatic conditions.
... Crop Protection Online (CPO) is a DSS developed and managed by Aarhus University, which was commercialised in 1991 (Rydahl, 2003(Rydahl, , 2004Kudsk, 2008a). CPOWeeds optimises herbicide combinations and dosages in relation to the actual crop and weed infestation either by lowest dose or lowest price. ...
... The aim of this work was to examine locally generated parameters and adjustments for the doseeresponse function described in (Rydahl, 2003) with regard to herbicides and weeds present in winter cereal fields in the North-east of Spain. The prototype was developed under the name CPOWeeds. ...
... This was done by shifting the doseeresponse curve to the right. (Kudsk, 2008b) (Rydahl, 2004) (Rydahl, 2003) Some non-parameterized species were regarded equally susceptible to an herbicide as another species by local experts and similar doseeresponse curves were adopted in the system for those species. ...
Article
The Danish decision support system Crop Protection Online (CPO) optimises herbicide weed control. CPO recommends specific herbicide solutions to achieve a required level of control. The aim is to apply herbicides as little as possible but as much as necessary. CPOWeeds is a version of CPO adjusted to conditions in North-eastern Spain. The predicted efficacies and the yield obtained with CPOWeeds were validated in winter cereal field trials from 2010 to 2013. All CPOWeeds treatments were related to the efficacies obtained with standard herbicide treatments decided upon by local advisors. The predictions from CPOWeeds were compared to the actually achieved efficacies in the field trials for the nine weed species at different developmental stages and for 84.2% of the comparisons the obtained efficacies were equal to or higher than predicted. The average difference between predicted and observed efficacies was 2.35 percentage points. Yield was measured in three trials and the recommendations from CPOWeeds were maintaining yield. There were two situations where CPOWeeds were performing suboptimal. One is in the early weed growth stages, as the model is not yet prepared to account for water stress on root action herbicides applied at 10-11 BBCH. The second situation was in fields with a prior unidentified population of resistant Alopecurus myosuroides. For key species in winter cereals in Spain, such as Avena sterilis, Lolium rigidum and Papaver rhoeas, CPOWeeds achieved a satisfactory control level. It was concluded that the use of CPOWeeds allowed optimisation of the herbicide application with a very high robustness. The recommendations were satisfactorily for the conditions of the Northeast of Spain and have the potential to decrease the amount of applied herbicides by at least 30%. Therefore, it can be an important tool in Integrated Weed Management.
... crop growth stage, weed species, weather conditions, herbicide spectrum, their economic and ecological properties and implications) is too large for intuitive decision-making (Mir & Quadri, 2009). For uniform field herbicide applications, many DSSs have been presented in research journals and several are also implemented and available as web-based, desktop and/or pocket (on-site usage) solution ( Bennett et al., 2003;Rydahl, 2003). Frequently required inputs for DSSs are the grown crop, its competitive ability (e.g. ...
... Online (Rydahl, 2003). In addition, population-based DSS incorporate information about weed biology, ecology and management through deterministic models ( Christensen et al., 2009;Wiles et al., 1996). ...
... An integral part of these DSS are databases storing information about herbicide performance under various conditions (crop, weed species, growth stage etc.), as reported by Christensen et al. (2009). Examples of this type of DSSs are SELOMA (Stigliani & Cosimo, 1993) or Crop Protection Online (Rydahl, 2003). In addition, population-based DSS incorporate information about weed biology, ecology and management through deterministic models (Christensen et al., 2009; Wiles et al., 1996). ...
... Another approach is based upon herbicide dose models, as in the Danish system, Crop protection Online (CPO). CPO focuses on optimizing the applied dose through detailed information on the expected herbicide efficacy for the individual weed species (Kudsk 2008;Rydahl 2003;Rydahl et al. 2003). CPO has been tested for practical purposes in a range of crops and has been found to provide robust advice and ensure yield. ...
... The standard curves were obtained in previously conducted field experiments by spraying at the zero-to two-leaf stage at 8 to 14 C and no soil moisture stress. The magnitude of the parallel displacement is specific for each herbicide and based on experimental data (Rydahl 2003). The youngest growth stages of most annual weed species are generally more susceptible to herbicides than more developed plants (Kudsk 1989). ...
Article
Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO for herbicide application in spring barley in Denmark were validated through field experiments targeting three levels of weed control requirement. Satisfactory weed control levels at harvest were achieved by a medium control level requirement generating substantial herbicide reductions (~ 60% measured as the Treatment Frequency Index (TFI)) compared to a high level of required weed control. The observations indicated that the current level of weed control required is robust for a range of weed scenarios. Weed plant numbers 3 wk after spraying indicated that the growth of the weed species were inhibited by the applied doses, but not necessarily killed, and that an adequate level of control was reached later in the season through crop competition.
... crop growth stage, weed species, weather conditions, herbicide spectrum, their economic and ecological properties and implications) is too large for intuitive decision-making (Mir & Quadri, 2009). For uniform field herbicide applications, many DSSs have been presented in research journals and several are also implemented and available as web-based, desktop and/or pocket (on-site usage) solution (Bennett et al., 2003;Rydahl, 2003). Frequently required inputs for DSSs are the grown crop, its competitive ability (e.g. ...
... Online (Rydahl, 2003). In addition, population-based DSS incorporate information about weed biology, ecology and management through deterministic models Wiles et al., 1996). ...
... Among the systems that have been on the market for the longest time are Pro_Plant and Crop Protection Online (CPO); both systems are today Internet-based (Rydahl et al. 2003; Volk et al. 2003). More specifically, the Danish DSS CPO is a threshold-based system that determines economically viable strategies for control of diseases, pests and weeds using low pesticide input (Secher et al. 1995; Rydahl 2003). The system is designed to support advisors and farmers when they make decisions about crop protection in arable crops. ...
Article
Full-text available
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 20years 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 10years (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.
... Doyle (1997) stressed that models for weed management had hardly ever addressed the central issues of how to promote a more selective use of herbicides and minimise their environmental impacts. The Danish system PC-Plant Protection (Rydahl, 2003) aims to limit the environmental impact of herbicide treatments by reducing the level of weed control needed, assessed using algorithms based on expert knowledge. However, the eco-toxicological properties of herbicides are not included in the decision-making process. ...
Article
The aim of this research was to improve the advice given by extension institutions to French farmers and to develop a Decision Support System (DSS) for weed control that would match the practical approach adopted by farmers. Farmers running 15 farms with different farming systems in different regions completed comprehensive interviews which allowed them to explain how they deal with weeds. We built temporal diagrams for crop management sequences and decision making. This paper describes the basic framework common to all the farmers interviewed. Each farmer employed pre-established weed control programmes. When designing these programmes, farmers integrated different time scales: the current year, the rotation, and the long term. In the short term, they considered the risks of yield losses and/or lower harvest quality plus harvesting difficulties. In the medium term, they anticipated the risk of finding a weed species in another crop of the rotation where control would be difficult or costly, weighing the risks of yield loss against the cost and effectiveness of solutions, not only in the current crop but also in subsequent crops, so that once again, the rotation was the central focus of weed control. In the long term, their main aim was to limit the soil seed bank to an acceptable level. The farmers interviewed stated that they would continue to implement a weed control programme that they deemed satisfactory as long as no new problem appeared, and until they could learn about more effective technical solutions. When designing a DSS that will ensure successful, more sustainable weed management practices, it is crucial to take account of both the complexity of the decision-making process and the multicriteria nature of decision making.
... Several other systems have been developed since and new systems are still entering the field today (Röhrig, 2006). Among the systems that have been on the market for the longest time are Pro_Plant and Crop Protection Online (CPO); both systems are today Internet-based (Rydahl, 2003;Volk et al., 2003). Pest management and crop protection includes a large number of techniques using varied knowledge in entomology, plant pathology, nematology, weeds and vertebrate pests. ...
Chapter
Full-text available
Information of the required quality always has the potential of improving efficiency in all spheres of agriculture. The personnel, who work as the welfare of Indian farmers, such as plant protectionists, extension workers, do not have access to latest information which hinders their ability to serve the farming community effectively. Rapid developments in scientific techniques, ideas and information, such as those in the field of molecular biology, have made electronic systems of storage essential to the laboratory scientist. The Internet is becoming increasingly important as a source of plant protection information. The range of information available on the web is increasing, with more organizations moving their databases and publications to the web. Plant protectionists now have a vast array of tools to manage information and access to a wide range of sources of information. Decision support Systems (DSS), Expert systems are now being widely used in various sectors of agriculture. Expert systems and DSS for pest control and crop protection comprises one of the most important and commonly used types of agricultural systems for plant protection. The scale and diversity of this information can seem quite daunting. This chapter attempts to provide a brief overview of the main uses of IT in relation to plant protection and some of the future prospects for developments in this field.
... The importance of addressing differences in herbicide sensitivity of weed populations increases with the reduction of doses. Reduction of herbicide doses using a dose-response model is a key concept of Crop Protection Online, a Danish decision support system for weed control (Rydahl, 2003;Kudsk, 2008;Sønderskov et al., 2014). Based on the principles of Crop Protection Online, decision support systems have been developed for winter wheat in northern regions of Poland and Germany under the acronym DSSHerbicide. ...
Article
The question on intraregional versus inter-regional variability in herbicide sensitivity for weed populations is of major importance, both in extrapolation of model parameters and in herbicide zonal approval procedures. We hypothesised that inter-regional variability in herbicide sensitivity for field populations would be the same as intraregional variability for regions with similar climatic conditions. Seeds of field weed populations were collected in a Danish, German and Polish region. Herbicide sensitivity was tested in dose–response experiments in the glasshouse with flufenacet and iodosulfuron (Apera spica-venti), florasulam and tribenuron (Tripleurospermum inodorum), diflufenican, diflufenican + flurtamone and pendimethalin (Viola arvensis). ED50 values and variance components of the ED50 values were estimated to describe the influence of region, year and population. The regions accounted for a maximum of 26% of the variance and always less than the variance accounted for by individual populations. Sensitivity indices (SI50) were calculated as the ratio between ED50 of the test population and a reference population. There was considerable intraregional variability in SI50 values and SI50 values from a single region did not consistently differ from other regions. The large intraregional variability in herbicide sensitivity between populations, with no evidence of resistance, is of interest both for zonal evaluation of herbicides and resistance research. For practical weed management, we conclude that dose–response functions can be transferred between the study regions, for example for the common use in decision support systems with proper insurance for the control of less sensitive populations.
... A slightly different approach is employed by Crop Protection Online (CPO), which is a DSS for optimal herbicide use developed in Denmark (Kudsk, 2008;Rydahl, 2003Rydahl, , 2004Sønderskov et al., 2014). CPO can aid the farmer in decision making concerning the need for weed control and the optimal herbicide combination and dose. ...
... Das heißt, dass weder die Restverunkrautung höher als bei Expertenentscheidungen lag, noch Ertragsdepressionen aufgrund der Computerentscheidung zu verzeichnen waren. Die Robustheit des Systems, das nach denselben Algorithmen auch in Dänemark läuft, wurde auch dort in Herbizidversuchen bestätigt(RYDAHL, 2003). Die Standorte unterscheiden sich in der Höhe der Verunkrautung sehr, jedoch sind alle Standorte durch eine dikotyle Mischverunkrautung gekennzeichnet. ...
Article
Full-text available
To choose herbicides and their optimal dosages is a great challenge in chemical weed control in arable crops, because the choice of possible herbicide mixtures is big and economic consequences are hardly estimated. DSSHerbicide is a computer aided decision support system calculating cost-saving weed control measures. It is adapted to German conditions from the Danish Crop Protection Online system with German herbicide and weed data. To test the prototype of the system, fourteen herbicide trials were installed at conventional winter weed fields with differing weed densities in 2011 and 2012. Apart from the herbicide selection of DSSHerbicide recommendations from private advisers, official advisory service and farmers were implemented as test variables. The different ways of decision-making were investigated with the parameters chosen herbicides, herbicide costs, treatment frequency index, weeds left after treatments and wheat yield. Neither in herbicide costs, nor in treatment frequency index nor in yield significant differences between the decision support system on the one side and the expert advices on the other side were found. Biomass of weeds after treatments was significantly higher in the DSSHerbicide plots than in the plots of the official advisory service. In tendency, but not significantly, this led to higher yields in the plots of the official advisory service. Variation in herbicide costs and treatment frequency indices between the field trials was highest in the DSSHerbicide plots. A higher correlation of weed density before control and herbicide costs in the DSSHerbicide plots than in the expert plots indicates a field specific herbicide advice by the DSSHerbicide. The prototype worked with a limited number of implemented herbicides. Since herbicide advices of the decision support system were robust over the fourteen field trials, it will be worth implementing more herbicides in the system.
... The database forms the backbone of the Danish web-based decision support system 'Crop Protection Online -Weeds' (CPO-Weeds). The data have been used to generate the doseresponse curves simulating more than 50,000 combinations of herbicides, weed species, crops and seasons (10,11). We believe that the data available to farmers in Denmark can serve to illustrate that the term 'the recommended dose' makes good sense when considering the spectrum of weed species that can be controlled, but makes little sense when it comes to determining what is a 'low' and a 'high' dose. ...
Chapter
In the wake of the steadily increasing number of cases of non-target site resistance (NTSR) in recent years, the discussion of low versus high herbicide doses (‘the dose discussion’) has attracted renewed attention. Several studies have concluded that low doses can select for NTSR phenotypes and this has led to a general recommendation to farmers not to apply doses lower than the recommended dose. The objective of this paper is to discuss whether this simple, and easy to convey, recommendation is justified. It is concluded that the term ‘low dose’ is misleadingly over-simplistic as it makes no reference to herbicide efficacy. Lower doses often provide the same, or very similar, level of control as the recommended dose and therefore can be applied without jeopardizing the sustainability of cropping systems. Some herbicides (e.g. ACCase and ALS inhibitors), some weeds (e.g. Lolium spp.) and some agronomic practices (e.g. repeated application of herbicides with the same site of action) pose a much greater resistance risk than others. Compared to these risk factors, herbicide dose is relatively insignificant. It is recommended 1) that more focus is devoted to generating information on herbicide dose response relationships, 2) that terms like ‘low’ or ‘reduced’ doses are omitted and there is more focus on efficacy levels and 3) that diversity in management and avoidance of ‘high risk’ practices becomes the key points in the advice to farmers, rather than herbicide dose.
... The Abs. CountDiff shows that on average, the model is off by 0.51 leaves, and for 70% of the samples, it is off by zero. Therefore, according to the results obtained, it can be concluded that the developed model can be implemented with 70% accuracy on variable field machines, including machine weed control; because in these systems, the amount of toxic material applied to the weed in the classes of close ranges (e.g., 2:3 or 7:8) does not differ greatly [31]. Figure 9 shows image samples that were hard to classify with the trained models, which is shown by the distribution of the predictions. ...
Article
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This study outlines a new method of automatically estimating weed species and growth stages (from cotyledon until eight leaves are visible) of in situ images covering 18 weed species or families. Images of weeds growing within a variety of crops were gathered across variable environmental conditions with regards to soil types, resolution and light settings. Then, 9649 of these images were used for training the computer, which automatically divided the weeds into nine growth classes. The performance of this proposed convolutional neural network approach was evaluated on a further set of 2516 images, which also varied in term of crop, soil type, image resolution and light conditions. The overall performance of this approach achieved a maximum accuracy of 78% for identifying Polygonum spp. and a minimum accuracy of 46% for blackgrass. In addition, it achieved an average 70% accuracy rate in estimating the number of leaves and 96% accuracy when accepting a deviation of two leaves. These results show that this new method of using deep convolutional neural networks has a relatively high ability to estimate early growth stages across a wide variety of weed species.
... Plant Protection Online has facilities for seasonal planning, weed, disease and pest identification, problem solving, pesticide database look-up, and formulation of mixtures of pesticides. For further information about Plant Protection Online, see Rydahl (2003) and Rydahl et al. (2003). ...
... Decision support systems have been developed to assist farmers in optimising the use of herbicides. In Denmark, a computer-based decision support system ÔCrop Protection OnlineÕ has been available as a software program since 1986 and as a web-based program since 2001 (Kudsk, 1999;Rydahl, 2003). Based on information on weed flora, density of each weed species, weed growth stage, climatic conditions and crop cultivar, the program will list all effective herbicide solutions adjusting the dose to the prevalent conditions in the field. ...
Article
Dose-splitting or reduced dose repeat application, i.e. the application of a herbicide twice to the same plant, is likely to become a more common scenario in future, if farmers adopt the use of novel techniques for prediction of herbicide efficacy shortly after application. Fourteen pot experiments were conducted to study whether graminicides applied to annual grass weeds as dose-splitting treatments were as effective as single applications. The influence of time interval between applications and the ratio of the doses of the two applications were studied. Two statistical approaches were applied: comparison of the ED90 of the single treatments and a joint action model. The study revealed that flupyrsulfuron, iodosulfuron, sulfosulfuron, clodinafop and glyphosate could be applied as repeat treatments with up to 14 days’ interval between the two applications without loss of activity. In some experiments, particularly with iodosulfuron, dose-splitting enhanced herbicide performance. By contrast, prosulfocarb responded adversely, most likely due to the pronounced impact of weed growth stage on the activity of this herbicide. The ratio of the doses and the timing between the two applications had no significant influence on herbicide responses. The results of the present studies showed that even if a reduced dose of a graminicide results in an unsatisfactory control and it is necessary to re-spray, the overall use of herbicide will not increase, if methods are available that can predict the efficacy of a herbicide application within the first 1–2 weeks after application.
Article
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.
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On the basis of one 12-year lasting experiment in Germany and one 4-year lasting experiment in Denmark, different crop rotations, soil tillage intensities, and strategies of pesticide use were investigated with regard to yield, humus replacement, nitrogen (N) balance, energy use efficiency as well as acute and chronic risk potentials for aquatic and terrestrial organisms due to pesticide application. The investigation of the Danish experiment concerned two crop rotations (continuous winter wheat cropping, ‘FR 1’; winter oilseed rape–winter wheat–winter wheat–winter barley, ‘FR 2’), three intensities of soil tillage (ploughing, ‘P’; tine tillage ‘H8–10’; direct drilling, ‘D’) and three target control levels against Apera spica-venti (untreated, ‘AU’; 70% control, ‘A 70%’; and 90% control, ‘A 90%’), whilst the German experiment comprised one arable crop rotation (winter oilseed rape–winter wheat–winter rye–peas–winter wheat–winter barley, ‘DR 1’) and one fodder crop rotation (winter oilseed rape–winter barley–alfalfa/clover/grass-mixture–winter rye–silage maize–winter wheat, ‘DR 2’) each crop with situation-related pesticide use (100% HF) or application rates reduced by 50% (50% HF). At both sites, rotations and treatments were located on the same plots in each year. The study comprises the harvest years 2003–2006.
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A survey has been conducted of decisions support systems (DSS's) for weed control in Europe. 9 DSS's representing 7 countries were studied. These were all targeted at farmers, but they differed in decisions supported, in number of crops covered and in demonstrated impact. At a workshop in Denmark in March 2008, a set of 'best parts' / 'building blocks' from these DSS's suitable for unification of a European level was identified. These could form the basis for building and validating DSS's on a European level that meets requirements for robustness in production lines and which hold some potential for reducing dependency and / or use of herbicides. When some robust and potent DSS concepts have been identified, the production and exchange of data that support integrated decision algorithms and calculation models of such DSS should be co-ordinated on a European level.
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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.
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A Danish decision support system (DSS) on integrated pest management (including pathogens and weeds) has been developed during the past 20 years. This DSS is distributed as an integrated part of the ‘Danish Integrated Farm Management System’, which is a PC program, of which the plant protection module presently has about 2500 subscribers in Denmark. This program has been designed to propose relevant options for treatment with plant protection products according to observations from a field inspection. The new object-oriented web-based system architecture of this DSS was developed in 2001. This allows local (national) adaptation of the DSS in terms of language, crops, pests, products and features. Model complexity and DSS algorithms can also be adjusted to local conditions. The system has been implemented in a relational database structure (Microsoft SQL Server) and a dynamic web application (Java and Jscript in Active Server Pages on an Internet Information Server). The system architecture has been designed with emphasis on a high level of flexibility for future adjustments due to agronomic and legal requirements. The DSS models have been linked to a pest identification module and to a comprehensive database on label information on plant protection products.
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The present major agricultural issues are to feed the world and reduce negative environmental impacts. To this end, organic farming appears as a promising solution. However organic farming has several drawbacks such as difficult weed management. Indeed weeds can reduce crop yields. Therefore there is a need for improved decision support tools for weed management in organic farming. An existing weed competition model actually predicts the effect of early multispecies weed density, both on organic wheat yield loss and on the weed density at flowering stage. However main existing models do not take into account the activity of end-users, e.g. farmers, during model design. Therefore we analysed weed information acquisition by farmers using the dynamic environment theory to design a decision support system that takes into account end-users. We interviewed eight French organic farmers. We analysed interview data using a coding scheme inspired by dynamic environment theory. Our results show that weed quantity was the information most frequently collected by organic farmers both for short- and long-term crop management. This information was compatible with early weed density, the main input of the previously developed models. Findings also show that procedures for gathering information and processing depended on farmer profiles. We also show that a conceptual model based on dynamic situations and a coding structure were appropriate for taking into account the information elaborated by end-users. Finally we propose further design of a decision support system for tactical organic weed management using a participatory approach.
Article
Weeds cause crop yield loss due to competition, interfere with agricultural activities and reduce grain quality due to seed contamination. Among the numerous methods for weed control, the use of herbicides is the most common practice. Nowadays, the optimization of herbicide application is pursued to reduce the environmental impact, delay the appearance of herbicide-resistant weed populations, and improve the cost/benefit ratio of the agronomic business. This work proposes an operational planning model, aimed at calculating the optimal application times of herbicides in no-tillage systems within a growing season in order to maximize the economic benefit of the activity while rationalizing the intensity of the applications with respect to expert-knowledge-based recommendations. The model can decide on herbicide applications on a daily basis, consistent with timing of agricultural activities, and provides an explicit quantification of the environmental impact as an external cost. The proposed approach was tested on a winter wheat (Triticum aestivum)–wild oat (Avena fatua) system, typical of the semiarid region of Argentina. In all the studied scenarios at least two pre-sowing applications of non-selective herbicides were required to effectively control early emerging weed seedlings. Additional pre-sowing and post-emergence applications were also advised in cases when competitive pressure was significant.
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In wheat the incidence and severity of diseases may vary with season, region, variety, weather, inoculum load and resistance level of the host cultivars. This variation leads to the varied yield losses even up to 100 percent under most severe conditions. Thus effective disease management strategy is to be followed for timely and successful management of wheat diseases. This may involve chemical control, Host plant resistance, cultural and biological control etc. Out of all these, methods chemical control gave a quick response with maximum benefits. But this method is not a preferable choice for sustainable agriculture. Hence to avoid/minimize the dependency on fungicides, we can look for the option of use of epidemiological models to predict the time and place of occurrence or development of the disease. So, prediction of disease appearance in advance in space and time would help a lot to the farmers to have maximum cost benefit ratio by timely managing the diseases with minimum expenditure. Keeping this in view several models has been developed for the almost all the important wheat diseases namely rusts, Fusarium head blight, Septoria blight, Karnal Bunt, Powdery mildew and Blast etc. in different groups in different countries with varied accuracy like PROCULTURE a mechanistic model, developed in Belgium could accurately predicted epidemics of septoria blight with probability of detection (POD) of more than 0.90 Based on the predictions. Likewise weather based mechanistic model developed in Italy for predicting DON worked with 90 per cent accuracy in Netherlands and 60 per cent in Egypt, U. K., Mexico, Hungary and Russia. For the prediction of Karnal Bunt a multiregression Models has been also developed on the basis of maximum temperature (Tmax), sunshine duration (SSD), evening relative humidity (RHe) and rainy days (RD) and the equations derived from them are explained up to 89 percent of the disease variation. Similarly in rusts and other diseases there are successful examples of disease prediction models. Some of them have been used for developing the Decision support systems for the benefit of the farmers e.g. granoduro.net® in Italy, FusaProg in Switzerland and Fusarium Risk Tool in USA, SeptoriaSim in Denmark, PUCREC/PUCTRI, Superconsultant etc. are some. Despite of so many models in use still there is a need to develop by following the interdisciplinary approach which can be practically more feasible globally.
In 1986 Denmark adopted, as the first country in Europe, a pesticide action plan calling for 50% reduction in pesticide use. The first pesticide action plan was later followed by three other pesticide action plans and recently the Danish government announced the fifth pesticide action plan covering the period 2013 to 2015. As a result of the long-standing public pressure to reduce pesticide use numerous research and advisory activities have been initiated to provide farmers with the knowledge and tools required to meet the goals. This chapter: (1) provides an overview of the content of the pesticide action plans; (2) presents the research and advisory activities supported by the pesticide action plans; (3) gives examples of the IPM tools that are available to Danish farmers; and (4) describes the most recent political initiatives including the new Pesticide Load Indicator that will replace the Treatment Frequency Index. © 2014 Springer Science+Business Media Dordrecht. All rights reserved.
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The introduction of Decision Support Systems (DSSs) in weed management poses an attractive option for creating improved and more environmentally friendly control strategies. The aim of the current study was to present key factors affecting decision-making process that need to be taken into account before developing a DSS in terms of weed management. First, attention should be paid to the effects of environmental factors and agronomic practices on weed emergence and the composition of the weed flora in an agricultural field. If weed emergence and timing of weed emergence could be predicted, then a DSS could make accurate suggestions for weed control. Secondly, to develop any weed management program, it is essential to have a deep understanding of weed biology and ecology. The biological traits of weeds, weed growth, the impact of weed competition during crucial growth stages for the crop should be estimated in order to optimize decision-making process. Moreover, a better understanding of seed production and weed seedbank dynamics into the soil would help experts develop DSSs able to provide management strategies also in the long-term period. However, these objectives are quite complex and need to be addressed in the near future. Furthermore, carrying out field surveys, hosting workshops, and group meetings in order to communicate with farmers and help them familiarize with the adoption of DSS methodologies. This is a vital step for persuading farmers to trust the use DSSs for the management of weeds in their fields. Further research and extended experimentation are needed in order to develop effective DSSs in terms of weed management under different soil and climatic conditions, always according to the special needs of each farmer.
Conference Paper
Referred to a process based model, with Web development tool and advanced object-oriented approach, a universal Web-based simulation system for greenhouse crops was developed, it can be accessed by users in different places by Internet exploring, which provides much convenient way to simulate the growth of greenhouse crops such as tomato, cucumber, etc. With the Web-based model, optimal environmental parameters in greenhouse can be estimated through the simulating system, and countermeasures of environment control and management for the greenhouse can be made more precisely according to these calculation.
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The assessment of mixture effects is usually done with isoboles which illustrate whether mixture effects are greater or smaller than would be expected on the basis of the individual activities of the herbicides. Under the assumption of similarity of response curves and by incorporating a function that can model the shape of isoboles, we can statistically test whether divergence from the Additive Dose Model (ADM) is significant. Two dose-response experiments with mixtures of either salt or ester formulations of MCPA and mecoprop-P and one experiment with tribenuron-methyl and mecoprop-P were analysed. Mixtures of tribenuron-methyl and a salt formulation of mecoprop-P showed antagonism. Mixtures of salt formulations of MCPA and mecoprop-P followed ADM, whilst ester formulations of the same compounds showed synergism. To get reliable estimates, the model requires mixture ratios covering the whole isobole © 1998 SCI
Article
A Danish decision support system (DSS) on integrated pest management (including pathogens and weeds) has been developed during the past 20 years. This DSS is distributed as an integrated part of the ‘Danish Integrated Farm Management System’, which is a PC program, of which the plant protection module presently has about 2500 subscribers in Denmark. This program has been designed to propose relevant options for treatment with plant protection products according to observations from a field inspection. The new object-oriented web-based system architecture of this DSS was developed in 2001. This allows local (national) adaptation of the DSS in terms of language, crops, pests, products and features. Model complexity and DSS algorithms can also be adjusted to local conditions. The system has been implemented in a relational database structure (Microsoft SQL Server) and a dynamic web application (Java and Jscript in Active Server Pages on an Internet Information Server). The system architecture has been designed with emphasis on a high level of flexibility for future adjustments due to agronomic and legal requirements. The DSS models have been linked to a pest identification module and to a comprehensive database on label information on plant protection products.
Will weed seed production become a problem by use of reduced doses of herbicides in cereal crops?
  • I Rasmussen
[Model in PC-Plant Protection for weed control in sugar beets - 3 years of evaluation.]
  • Rydahl
[PC-Plant Protection - optimized herbicide mixtures in sugar beet.]
  • Rydahl
Joint action of tribenuron and other broadleaf herbicides
  • Kudsk