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DSSHerbicide: Weed control in winter wheat with a decision support system in three South Baltic regions – Field experimental results

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... The tools sort and present the available herbicide solutions in different way as a response to the questions asked by the user. Several names for the system have been used in the English literature, including PC Plant Protection (Denmark), Plant Protection Online (Denmark), VIPS-Ugras (Norway), CPOWeeds (Spain) and DSSHerbicide (Poland, Germany) [11,12,18]. In each country, the CPO-versions are adjusted according to the herbicide availability in the specific country and parameterised accordingly, whereas the algorithms and calculations follow the same concept. ...
... This led to average required control levels of around 70 % including the scenarios that were below the economic threshold and did not call for any herbicide application. The validations of this version showed that CPO-Weeds maintained its robustness, and larger herbicide reductions were achieved [14,18,19]. Some additions/changes to CPO-Weeds have improved the DSS, while others have been found merely to increase complexity for the users without adding any real benefits. ...
... The experiences hitherto have shown that CPO-Weeds has potential for substantial reductions in herbicide use, if used as intended. Practical experiments in various countries have estimated reduction potentials between 20 and 40 % compared to labelled rates or standard recommendations [11,14,18]. ...
Chapter
Crop Protection Online—Weeds (CPO-Weeds) is a decision support system for weed control developed in Denmark and later adjusted to conditions in several other countries. In Denmark, the DSS includes all major crops and available herbicides. The background for developing CPO-Weeds was a political motivation for reducing pesticide use and the concept of factor-adjusted doses. It was never the intention to build a sophisticated scientific model, but rather to design a simple user-friendly system. It is a knowledge-driven DSS, which offers herbicide dose suggestions based on a large database of the existing knowledge of herbicides and herbicide efficacies. The required weed control level in CPO-Weeds is based on expert evaluations, a herbicides dose-response model and an additive dose model to calculate possible mixtures of herbicides targeted a specific weed population. The herbicide dose model is a two parameter dose-response model, which is modified to include the effects of temperature, weed growth stage and influence of drought. The development has been driven by an ambition of offering a robust system with relatively low amounts of input variables and limited need for experimental parameter generation. CPO-Weeds offers overview and guidance for field specific spraying solutions, and the system has proved able to recommend herbicide doses with considerable reductions compared to label rates. Furthermore, CPO-Weeds offers a variety of tools that summarises knowledge of herbicides for a wide range of questions asked by practical weed managers, e.g. efficacy profiles of each herbicide, efficacy of users own herbicide mixtures, weed identification key and guidance for spraying strategy. The experiences have shown that even though CPO-Weeds are considered robust and trustworthy by both farmers and advisors there is a relatively low number of farmers subscribing to the system. A survey revealed that the DSS falls in between the strategies of many farmers; either the farmers relies completely on own experiences or advisory services or they considers the full crop rotation in their weed management. The latter is not supported by CPO-Weeds, which focus on a single season. The long term consequences of herbicide recommendations is only included in the need to limit input to soil seed bank. Another limiting factor for an increased practical use of CPO-Weeds is the need for field monitoring of weed populations, which can be a time consuming task and requires extensive weed recognising abilities of the farmer at the very early growth stages of weeds. The intention of CPO-Weeds was to provide recommendations for the full spraying season of a field, but experiences have shown that the system has several uses. Many farmers spray with a standard solution in the autumn in winter crops and then use the DSS for spring sprayings. The relatively simple input requirements also make the DSS suitable for teaching purposes and for farmers starting to grow new crops in their rotation as a learning tool.
... Successful tools were also developed and tested in other areas of crop production. One example is DSSHerbicide [13], which is used to optimize herbicide use. All these DSSs were evaluated in practice or in field trials to show their utility for potential users. ...
... In contrast, numerous other studies mainly deal with the optimal intensity of fertilization and provide valuable knowledge in this area: For example, Wu and Ma [34], who state in their review that integrated nutrient management is of great importance for global crop productivity, or Rajsic and Weersink [28], and Mandrini et al. [14], focusing on economically optimal nitrogen supply. More broadly, some field-tested DSSs that simulate or recommend the use of inputs in crop production were studied and found to be useful in enabling agronomic performance [10][11][12][13]. These studies are based on crop-growth models, or apply ex ante versus ex post analysis. ...
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Decision-support system (DSS) IoFarm was developed to identify economically optimal fertilizer strategies on the farm level. The average cost savings are 66 EUR ha−1. This study aimed to determine whether this approach impacts yield, protein content, and market performance in crop production compared to usual farm-fertilization strategies. Few DSSs for fertilizer optimization consider multiple nutrients. DSSs with a clear focus on both fertilizer intensity and the least-cost combination of fertilizers are even rarer. To the best of our knowledge, there is no information in the literature on the impact of such DSSs on yield, protein content, and market performance for cereal–maize crop rotation. This study determines for the first time whether the financial benefits of using such an optimization tool are in conflict with important agronomic goals. In a three-year field trial, IoFarm was compared to standard farm-fertilization strategies. Results were evaluated with an analysis of variance followed by post hoc tests. No significant differences in yield, protein content, and market performance were found for comparable fertilization variants (with or without organic fertilization). However, differences exist in the selection of fertilizers and the timing of fertilization. Results show the agronomic comparability of IoFarm and usual farm-fertilizer strategies.
... DSS can assist farmers in making decisions about 'if' and 'how' to treat, and field surveys can provide the information needed to run the DSS (Berti et al., 2003). Most of the existing DSS for weed control in maize and other crops are aiming at optimizing herbicide use (Swinton et al., 2002;Bennett et al., 2003;Berti et al., 2003;Sønderskov et al., 2014Sønderskov et al., , 2015; nevertheless, few models have been developed to aid in a range of management practice decisions within the cropping system (Monjardino et al., 2003;Benjamin et al., 2009). DSS for optimizing herbicide use are estimating the need for weed control, where the necessary efficacy depends on field-specific weed population with each weed species causing a certain magnitude of yield loss (Sønderskov et al., 2015), with recommendations often being optimized on the basis of net return (Bennett et al., 2003;Berti et al., 2003). ...
... Most of the existing DSS for weed control in maize and other crops are aiming at optimizing herbicide use (Swinton et al., 2002;Bennett et al., 2003;Berti et al., 2003;Sønderskov et al., 2014Sønderskov et al., , 2015; nevertheless, few models have been developed to aid in a range of management practice decisions within the cropping system (Monjardino et al., 2003;Benjamin et al., 2009). DSS for optimizing herbicide use are estimating the need for weed control, where the necessary efficacy depends on field-specific weed population with each weed species causing a certain magnitude of yield loss (Sønderskov et al., 2015), with recommendations often being optimized on the basis of net return (Bennett et al., 2003;Berti et al., 2003). However, DSS are still not broadly adopted and used by farmers (Berti et al., 2003;Swanton et al., 2008), even though some DSS could reduce herbicide inputs significantly (Rydahl et al., 2009). ...
... An effective way to reduce the side effects of the herbicides, according to the Integrated Weed Management 2 weed species" combinations (Dogan & Boz, 2005;Kudsk 2008;Pannacci et al., 2010). Furthermore, the knowledge of MDRE is one of the main factors in the implementation of the Decision Support Systems for Integrated Weed Management (Rydahl, 2004;Sønderskov et al., 2015), with the aim to decrease the dependence on herbicides that has become a distinct objective within the EU with the directive 2009/128/EC. The determination of MDRE requires dose-response studies for each "herbicide-weed species" under various environmental conditions (Kudsk & Kristensen, 1992;Pannacci & Covarelli, 2009). ...
Article
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Four field experiments were carried out from 2011 to 2014 in order to evaluate the effects of foramsulfuron, applied at the recommended (60.8 g a.i./ha) and reduced doses (1/3 and 2/3), on the efficacy against several of the most important weeds in maize. For each “year-weed” combination, dose-response curves were applied to estimate the dose of foramsulfuron required to obtain 90% and 95% weed control (ED90 and ED95). Foramsulfuron phytotoxicity on maize and crop yield were assessed. Foramsulfuron at 1/3 of the recommended dose (20.3 g a.i./ha) provided 95% efficacy against redroot pigweed (Amaranthus retroflexus L.), green foxtail (Setaria viridis (L.) Beauv.), wild mustard (Sinapis arvensis L.) and black nightshade (Solanum nigrum L.). Velvetleaf (Abutilon theophrasti Medik.), common lambsquarters (Chenopodium album L.) and barnyardgrass (Echinochloa crus-galli (L.) Beauv.) were satisfactorily controlled (95% weed efficacy) with ED95 ranged from 20 to 50 g/ha of foramsulfuron (about from 1/3 to 5/6 of the recommended dose) depending on growth stage. The recommended dose was effective against pale smartweed (Polygonum lapathifolium L.) at 2-4 true leaves (12-14 BBCH scale), but this dose did not kill plants larger than 2-4 true leaves. The ranking among weed species based on their susceptibility to foramsulfuron was: redroot pigweed = green foxtail = wild mustard = black nightshade > velvetleaf = common lambsquarters = barnyardgrass > pale smartweed. Dose of foramsulfuron can be reduced below recommended dose depending on weed species and growth stage. Foramsulfuron showed a good crop selectivity and had no negative effect on maize yield.
... The total of 66 species which were identified over the three years of pre-harvest surveying is consistent with results from an on-farm winter wheat monitoring which was conducted in Northwest Germany (Ulber et al., 2009). The major surveyed weeds V. arvensis, F. convolvulus, P. aviculare, E. arvense, B. napus, P. annua, M. chamomilla, G. aparine, E. repens and C. arvense are typical for conventional managed winter wheat grown on loamy soils in Germany (Gruber et al., 2012;Sønderskov et al., 2015). We supposed that frequent glyphosate applications lead to a shift in which glyphosate-tolerant weed species gain dominance in the weed community. ...
Article
In the discussion about glyphosate-based herbicides, the question of how repeated applications affect biodiversity has become prominent. However, approaches are lacking to assess direct glyphosate effects under real, on-farm field conditions. This paper focuses the effect of post-harvest and / or pre-sowing glyphosate use on weed density, richness, diversity and composition in arable cropping systems. An on-farm monitoring was conducted in Northeast Germany over the period 2014–2016. The pre-harvest weed survey took place on a total of 97 winter wheat fields. Farmers´ records of field management were obtained for the surveyed fields for the year in which a field was visited and also the nine previous years. A total of 66 species over the three survey years were identified shortly before harvest. Overall, the highest number of specimens were found for the species Viola arvensis Murray, Fallopia convolvulus (L.) Á. Löve and Polygonum aviculare L. This study provided evidence that intensive glyphosate use in the recent past significantly sinks species richness by 31% and the true diversity by 40%. In contrast, weed density and weed community composition were not affected by past glyphosate use intensity. Indeed, we found that glyphosate-based or inversion tillage-based cropping systems induce different weed community patterns. The results of this study provide one more piece in the puzzle for the assessment of the impact of glyphosate use on the environment.
... Due to generic qualities in agro-biological modelling and IT basis, IPMW is currently being customized for professional use also in countries abroad, mainly Norway, Germany and Spain, and start-up activities are in progress in additional EU countries. In all countries involved so far, DSS has demonstrated sufficiently robust IWM, and potentials for reducing the use of herbicides in the range of 20-40% as compared to local 'best practice' programs Reduction (Rydahl, 2004;Tørresen et al., 2004;Sønderskov et al., 2014;Sønderskov et al., 2015;Montull, 2016). However, in all countries involved, a common recognized major bottleneck for a wider exploitation of reduction potentials has been identified in terms of reluctance among farmers to conduct manual field inspections (Jørgensen et al., 2007). ...
Article
In order to exploit potentials of 20–40% reduction of herbicide use, as documented by use of Decision Support Systems (DSS), where requirements for manual field inspection constitute a major obstacle, large numbers of digital pictures of weed infestations have been collected and analysed manually by crop advisors. Results were transferred to: 1) DSS, which determined needs for control and connected, optimized options for control returned options for control and 2) convolutional, neural networks, which in this way were trained to enable automatic analysis of future pictures, which support both field- and site-specific integrated weed management.
... There is no systematic published analysis of the distribution of the relative slopes around the ED 50 . However, there is some research in the differences among relative slopes in the Danish Crop Protection Online (CPO) (22,23). The relative slopes in CPO range between 1 and 3. ...
Chapter
This chapter deals with dose-response models to describe the relationship between a dose and its effect on target and non-target organisms, often after the dose has been diluted by drift. We define pesticide drift and describe the endeavor to link effects to an arbitrary point outside the field. Lastly, we analyze data from published papers on non-target plants to determine how they contribute to understand the biological effect of herbicide drift. The research bottleneck is in the drift model and the way non-target plants are affected. The variation in determining EDx (Effective Dose at a response level x) among species is often so large that sensitivity of species cannot be unraveled. In particular, when herbicides with large potency differences are included in a study, the effect of herbicides usually stands out, while other factors are not significant. An aspect currently in the news is the novel use of auxin herbicides on genetically modified auxin herbicide-tolerant crops and the problems that can occur when large areas are sprayed nearby very sensitive non-target plants. One additional aspect is that when using “wild species” as test plants, EDx levels will vary much more than when using crops and weed species that are genetically more uniform.
... Towards decision-making processes in weed control, Parsons et al. (2009) developed a model-based decision support system to assist arable farmers and consultants. Montull et al. (2014) validated the Danish decision support system Crop Protection Online (CPO) and found that its herbicide recommendations were satisfactory for the conditions of Northeast of Spain and had the potential to decrease the amount of applied herbicides by at least 30%, while Sønderskov et al. (2015) compared the results of two herbicide decision support systems with CPO's outputs after field experimental trials in winter wheat. ...
Article
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Site-specific weed management presupposes the careful monitoring and mapping of weed infestation areas. Cut-edge sensor technologies coupled with geographical information systems (GIS) provide the means for reliable decision-making concerning weed management even in sub-field level. In present research, two different spectral sensing systems were engaged in order to digitally map weed patches as grown in four different cotton fields in Central Greece. The systems used were a set of two Crop Circle multispectral sensors ACS-430 and a digital camera Nikon D300S. The spaces between cotton rows were scanned and photographed with the two systems accordingly. Raw recorded data were stored and analyzed in GIS environment producing spatially interpolated maps of red-edge normalized difference vegetation index (NDVI) and weed cover percentage values. Both mapping approaches were satisfactorily related to weed distribution as occurred in the fields; however, the photographic method tended to underestimate weed populations. Correlation of red-edge NDVI and weed cover values, at the points where photographs were taken, as revealed by Pearson’s correlation coefficient was high (r > 0.83) and statistically significant at the 0.01 level. A first-degree linear equation adequately modeled (R² > 0.7) the between value pair relations, strengthening the validity of the two methodologies in spatially monitoring weed patches. The methodologies and the technologies used in the study can be used for yearly mapping weed flora in cotton cultivation and potentially constitute a means of rationalizing herbicide application in terms of doses and spatio-temporal decision-making.
... The pest, crop, and environment data are randomly generated within a reasonable interval. For example, the attribute of crop planting density is generated from 180-525 seeds/m 2 [68]. Since TSM is developed within a European project, entitled Aggregate Farming in the Cloud (AFarCloud), we expect to receive data from real fields as soon as the sensor deployment is complete. ...
Article
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Case-based reasoning has been a widely-used approach to assist humans in making decisions through four steps: retrieve, reuse, revise, and retain. Among these steps, case retrieval plays a significant role because the rest of processes cannot proceed without successfully identifying the most similar past case beforehand. Some popular methods such as angle-based and distance-based similarity measures have been well explored for case retrieval. However, these methods may match inaccurate cases under certain extreme circumstances. Thus, a triangular similarity measure is proposed to identify commonalities between cases, overcoming the drawbacks of angle-based and distance-based measures. For verifying the effectiveness and performance of the proposed measure, case-based reasoning was applied to an agricultural decision support system for pest management and 300 new cases were used for testing purposes. Once a new pest problem is reported, its attributes are compared with historical data by the proposed triangular similarity measure. Farmers can obtain quick decision support on managing pest problems by learning from the retrieved solution of the most similar past case. The experimental result shows that the proposed measure can retrieve the most similar case with an average accuracy of 91.99% and it outperforms the other measures in the aspects of accuracy and robustness.
... In scientific experiments, this response variable 'herbicide use' must result from a standardized, reproducible decision procedure. Decision support systems adapted to German conditions and available for winter wheat included selected herbicides only (Sønderskov et al., 2015). We developed a new approach compiling decision rules for herbicide use based on major weed species and their densities to objectively perform herbicide decisions for different weed control targets. ...
Article
Herbicide use simplified cropping systems, which lead to short rotations and sowing dates rather focusing on yield than on weed management. Re-diversifying these cropping systems should reduce the vast use of herbicides. We hypothesize that herbicide use decreases with more diverse cropping systems even with few common crops. Cropping system experiments raise methodological questions connected with herbicide use. So far, herbicide use in field experiments is a-priori fixed and not adapted to changing situations. To overcome this, we developed a heuristic decision rule to employ herbicide intensities as response variable in statistical models. Field trials were set up at two locations in Germany as split plot design with cropping systems as main factor and weed control targets as sub-factor. The cropping systems contained maize, winter wheat and winter oilseed rape, and differed in length and sowing date of winter wheat. Weed control targeted a high, medium and low multi-year level. The outcome ‘herbicide intensity’ was described as treatment frequency index (TFI) and as number of active ingredients (NAI). Finally, crops were harvested and yields measured. The heuristic decision rule enabled reproducible, objective herbicide decisions to adapt herbicide intensities to various weed infestations. Herbicide intensities sorted themselves according to the multi-year control target. All crops required a lower herbicide intensity when grown in longer rotations: on average TFI decreased by 19% and 11% resp. depending on the location, and NAI decreased by 0.3 on average per year. Highest yields were harvested with a medium to high weed control target. The heuristic approach opens up new opportunities to collect data on herbicide use as a dependent variable. More diversity in cropping systems reduced herbicide intensity, nevertheless, could not completely compensate the use of herbicides. Thus, we consider them as a useful tool in integrated weed management.
... The accuracy considers the average precision [56] of retrieved top three similar cases. The formula of the average precision is defined in Equation (1). ...
Article
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As an artificial intelligence technique, case-based reasoning has considerable potential to build intelligent systems for smart agriculture, providing farmers with advice about farming operation management. A proper case representation method plays a crucial role in case-based reasoning systems. Some methods like textual, attribute-value pair, and ontological representations have been well explored by researchers. However, these methods may lead to inefficient case retrieval when a large volume of data is stored in the case base. Thus, an associated representation method is proposed in this paper for fast case retrieval. Each case is interconnected with several similar and dissimilar ones. Once a new case is reported, its features are compared with historical data by similarity measurements for identifying a relative similar past case. The similarity of associated cases is measured preferentially, instead of comparing all the cases in the case base. Experiments on case retrieval were performed between the associated case representation and traditional methods, following two criteria: the number of visited cases and retrieval accuracy. The result demonstrates that our proposal enables fast case retrieval with promising accuracy by visiting fewer past cases. In conclusion, the associated case representation method outperforms traditional methods in the aspect of retrieval efficiency.
... Focusing on crop protection, these DST can play a major role in identifying diseases (Hallau et al. 2018), simulating disease development (Damos 2015) and optimizing pesticide applications (Nansen et al. 2015). They have been shown, for instance, to reduce herbicide applications while maintaining the same yield levels as the standard recommended applications (Sønderskov et al. 2015). These DST consequently have the potential to increase sustainability of agricultural production by reducing negative external effects and costs for agro-chemicals. ...
Article
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There is a steady increase in smartphone apps available to improve farmers’ decision making with respect to crop protection. While current studies have focused on smartphone adoption in general and farmers’ general willingness to pay for crop protection smartphone apps in particular, none have focused on the initial adoption decision. Furthermore, it has not been studied yet which app functions are perceived as useful and which are actually used by farmers. Based on an online survey conducted in 2019 with 207 German farmers, this study investigated latent factors affecting farmers’ adoption decision for crop protection smartphone apps based on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework applying partial least squares equation modelling and a binary logit model. Descriptive results show that 95% of the surveyed farmers use a smartphone, but only 71% use a crop protection smartphone app. Apps providing information about weather, pest scouting and infestations forecasts are perceived as most useful by the majority of farmers. However, reported use fell short of reported usefulness. With respect to the model for the UTAUT, 73% of the variation in the behavioral intention to use a crop protection smartphone app is explained by the model. The results are of interest for policy makers in the field of digitization in agriculture as well as providers and developers of crop protection smartphone apps since the results could be used for further development of apps and policies regarding digitization.
... Proximal sensing systems can also be mounted directly on the farming equipment, which is a highly desired property, due to an increasing focus on automation (e.g., agricultural robots) of the agricultural practices [3,13,15]. Detailed plant population maps can, for instance, be used in decision support systems for weed management, to optimize control strategies according to the observed weed species and composition, which can provide significant reductions in herbicide usages [3,12,16,17]. Proximal sensing and visual recognition can also be applied for other applications, such as phenotyping, diseases and pests detection, grain quality and plant fitness estimation, etc. [2,18]. ...
Article
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For decades, significant effort has been put into the development of plant detection and classification algorithms. However, it has been difficult to compare the performance of the different algorithms, due to the lack of a common testbed, such as a public available annotated reference dataset. In this paper, we present the Open Plant Phenotype Database (OPPD), a public dataset for plant detection and plant classification. The dataset contains 7590 RGB images of 47 plant species. Each species is cultivated under three different growth conditions, to provide a high degree of diversity in terms of visual appearance. The images are collected at the semifield area at Aarhus University, Research Centre Flakkebjerg, Denmark, using a customized data acquisition platform that provides well-illuminated images with a ground resolution of ∼6.6 px mm − 1 . All images are annotated with plant species using the EPPO encoding system, bounding box annotations for detection and extraction of individual plants, applied growth conditions and time passed since seeding. Additionally, the individual plants have been tracked temporally and given unique IDs. The dataset is accompanied by two experiments for: (1) plant instance detection and (2) plant species classification. The experiments introduce evaluation metrics and methods for the two tasks and provide baselines for future work on the data.
... In addition, it is implemented to varying degrees in Norway, Estonia, Poland and Germany in one or more crops. In these countries, the validation tests have showed that the recommendations were robust (Sønderskov et al. 2015). However, the potential of herbicide reductions varies between countries and depends on the weed species present in the fields and also on management decisions (Been et al. 2010). ...
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.
... Therefore, simulated data are used currently and they are generated within a given range. For instance, judging from the current literature [50], the planting density of rice is generated from 180 to 525 seeds/m 2 . The life cycle of rice can be categorized by "embryogenesis," "vegetative," "ripening" and "reproductive" stages [51], encoded by integers "1," "2," "3" and "4." ...
Article
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Case-based reasoning has considerable potential to model decision support systems for smart agriculture, assisting farmers in managing farming operations. However, with the explosive amount of sensing data, these systems may achieve poor performance in knowledge management like case retrieval and case base maintenance. Typical approaches of case retrieval have to traverse all past cases for matching similar ones, leading to low efficiency. Thus, a new case retrieval algorithm for agricultural case-based reasoning systems is proposed in this paper. At the initial stage, an association table is constructed, containing the relationships between all past cases. Afterwards, attributes of a new case are compared with an entry case. According to the similarity measurement, associated similar or dissimilar cases are then compared preferentially, instead of traversing the whole case base. The association of the new case is generated through case retrieval and added in the association table at the step of case retention. The association table is also updated when a closer relationship is detected. The experiment result demonstrates that our proposal enables rapid case retrieval with promising accuracy by comparing a fewer number of past cases. Thus, the retrieval efficiency of our proposal outperforms typical approaches.
... When the desired level of weed control focuses on long-term crop productivity rather than 100% weed control, then decision support systems (DSS) are ideally designed to select optimum herbicide levels for each treatment area. A decision support system designed to suit European farming systems has resulted in herbicide savings of 20-40% (Sønderskov et al., 2015). By further refining this DSS analysis and applying it to individual areas of the field, an additional 40% reduction in herbicide use can be achieved (Somerville et al., 2019). ...
Article
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The targeted treatment of weeds is an expanding part of precision farming in many countries. Targeted weed treatments, using precision spray maps, reduce herbicide consumption, whilst still maintaining long term weed control. Assembling accurate spray maps is a vital part of this process. However, acceptable accuracy in spray maps is difficult to quantify, due in part to rapid technological advances in cameras, weed recognition software, and herbicide decision support systems (DSS). This research applied a DSS to repeated samples from field gathered weed data. Variability in the herbicide recommendations when different numbers of images were used for the same areas (polygons) within a field were examined. Type 2 errors (not recommending herbicide where it was needed), were analysed separately to type 1 errors (recommending herbicide where it was not needed). Type 2 errors were more common than type 1 errors in diagnosing herbicides to control Viola arvensis in Field 1, and Poaceae species in Field 2, and were also more common with systematically dispersed images compared to randomly dispersed images. In contrast, type 2 errors were less common than type 1 errors for Poaceae species in Field 1. Variability in herbicide recommendations differed for herbicides but was generally reduced (1) with greater numbers of images per polygon; (2) by using regularly arranged images; and (3) for datasets with greater ratios of ‘empty’ (not needing spray) polygons. Targeted treatments reduced herbicide use to 3–11% of the rate recommended for blanket spraying of the same weeds. High numbers of ‘empty’ polygons gave better results with lower relative percentages of type 1 errors. These results highlight the need to focus on reducing type 2 errors in spatial herbicide recommendations.
... A reduction in herbicide doses has been reported to be feasible in wheat [124]. Field trials in Germany and Poland with recommendations for weed control in winter wheat based on the DSS "DSSHerbicide", an adjusted DSS based on CPO, resulted in a 20-40% reduction in the treatment frequency index and, hence, a reduction in herbicide use in autumn sprayings as compared to standard recommendations, without adverse effects on the yield [125]. AVENA-PC, a DSS for the control of Avena sterilis ssp. ...
Article
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Agricultural systems in the EU have become more vulnerable and less sustainable due to an overreliance on herbicides and the tremendous increase in herbicide-resistant weeds. The EU Green Deal aims to reduce the use and risk of chemical pesticides by 50% by 2030, although it is still undefined whether a reduction in herbicide use could be feasible in different farming systems and situations. This review aims to provide a holistic framework for sustainable crop and weed management to reduce the herbicide input and ensure crop protection. Current and future dilemmas and policies that need to be handled to ensure the agroecological transition of the EU's agricultural systems are also discussed. The integration of non-chemical alternatives for integrated weed management is feasible and includes novel cultivation techniques (e.g., intercropping, false seedbed, reduced tillage, crop rotation and diversification, adjustments on sowing densities and dates), non-chemical tools (e.g., flaming, seed coating, beneficial microorganisms, mechanical weeding, biocon-trol agents and natural herbicides), competitive plant material (hybrids and cultivars, cover crops, service crops), and new technologies and precision agriculture tools (e.g., Decision Support Systems , robots, remote sensing, UAVs, omics and nanotechnology). A special focus should be appointed to agroecology and biodiversity conservation.
Thesis
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In recent years, precision agriculture and precision weed control have been developed aiming at optimising yield and cost while minimising environmental impact. Such solutions include robots for precise hoeing or spraying. The commercial success of robots and other precision weed control techniques has, however, been limited, partly due to a combination of a high acquisition price and low capacity compared to conventional spray booms, limiting the usage of precision weeding to high-value crops. Nonetheless, conventional spray booms are rarely used optimally. A study by Jørgensen et al. (2007) has shown that selecting the right herbicides can lead to savings by more than 40 percent in cereal fields without decreasing the crop yield when using conventional sprayers. Therefore, in order to utilise conventional spray booms optimally, a preliminary analysis of the field is necessary. This analysis should determine which weeds are present in the field and the density of those weeds so that herbicides targeting those weeds may be selected. Researchers have sought to detect and classify weeds and crops in images, but studies are limited regarding the number of plant species that can be discriminated and the flexibility of the camera setup. In the present PhD thesis, requirements for the camera set-up are loosened, allowing the use of consumer grade cameras or even cell phones for weed species localisation and identification in images from conventionally grown fields. In total 4 537 images have been collected over three growth seasons from Danish fields. In these images 31397 plants are annotated with names, from which the 17 most frequent species are selected for automated classifiiiication. The automated classification consists of two steps: Initially, weeds are located in images after which, the weeds are classified. Three types of weed localisation approaches are tested: Two approaches that perform a pixel-wise segmentation of plants, and one approach, that detects regions in images containing weeds. Common for all three approaches is that they aim at overcoming some of the challenges when working with images from fields: Namely changes in lighting, soil types, and plant stress due to lack of nutrition. The first of the suggested approaches segments plant material from the soil by using fuzzy C -means clustering combined with a threshold value for each pixel, which depends on the neighbourhood pixels, which helps to detect non-green stem regions. The second approach uses a fully convolutional neural network for segmenting pixels in three categories: Soil, weeds, and crops. The Neural Network is trained solely on modelled images but can segment weeds from maize with an intersection-over-union of between 0.69 and 0.93 for weeds and maize. Rather than segmenting images, the third approach produces region proposals that indicate weed locations in images. This method also uses a fully convolutional neural network, that enables it to detect weed instances in wheat fields despite occluding leaves. The three methods for weed segmentation and localisation solve four problems in the field of camera based weed detection: handling of changing environments, handling of non-green plant stems, segmentation of weeds and crops that are overlapping, and instance detection in cereal fields with occluding leaves. Following the detection of the weeds, the weed species are to be determined. For solving this problem, a convolutional neural network is used, which classifies the weeds with an overall accuracy of 87 percent for 17 species despite a severe degree of leaf occlusion. Because of the ability to handle weed detection and classification in natural environments, these methods can potentially reduce the investment of farmers, and thus lead to a higher adoption rate than existing precision weed control techniques, resulting in huge potential savings regarding herbicide consumption.
Chapter
Conventional weed control methods are based on uniform treatments of the whole field, however, weeds are not distributed uniformly within fields, which means that the uniform distribution of herbicides is inappropriate. Considerable research has been conducted on different aspects of site-specific weed management in the past three decades from fundamental studies on the spatial distribution of weeds to the applied development and testing of new technologies for weed detection and site-specific control. Despite the available technologies and knowledge, there has been little practical adoption of these technologies mainly due to the lack of automated weed detection methods. However, significant progress has been made in the past few years. This chapter describes the general principles of automated weed detection and how these principles can be used in an agricultural context. Two cases demonstrate the progress of spot-application of herbicides based on automated weed detection using RGB cameras mounted on unmanned aerial vehicles (UAV) and ground vehicles.
Article
In order to ensure higher sustainability of winter wheat and maize production in Europe, cropping systems featuring different levels of Integrated Pest Management (IPM) need to be tested in the field and validated for their sustainability before being adopted by farmers. However, the sustainability evaluation of cropping systems is difficult to perform effectively due to the complex economic, social and environmental dimensions of sustainability. Within the EU research project PURE, nine long-term experiments were conducted in various European regions from 2011 to 2014, comparing two IPM levels against the conventional system (CS) in winter wheat- and maize-based cropping systems. IPM1 encompassed some pesticide use in semi-diverse crop rotations while IPM2 favoured reduced- and non-chemical methods in diverse rotations. The modified DEXiPM (DEXi Pest Management) model for arable cropping systems was used for ex-post assessments to compare the economic, environmental and social sustainability of these systems. The assessments showed that in six out of nine trials the CS was overall unsustainable because of low evaluation of the environmental sustainability that was mainly due to high pesticide use and simplified crop rotations where the choice of crops is primarily market-driven. In contrast, six IPM1 and five IPM2 systems could be classified as sustainable, achieving ‘medium’ or ‘high’ scores for all three sustainability dimensions. Differences in the socio-economic conditions across countries and/or climatic and soil conditions across experimental trials highlighted that IPM is based on general principles that must be adapted to address specific local conditions. Overall, IPM systems included more diverse crop rotations and practices compared to the CS, promoting IPM-based strategies with less pesticide use but also a reduced reliance on pesticides that could partially compensate for any yield reductions by the savings on pesticide and application costs. It is recommended that the results of the study should be disseminated to policy-makers, advisors and farmers and that their implementation should be considered on a regional level. Regional policies to encourage the adoption of more sustainable systems based on IPM principles, as well as better support by more closely involving the regional advisory services for the general implementation of IPM is further recommended. Ex-post analysis with DEXiPM also identified the constraints of the IPM1 and IPM2 systems evaluated as not sustainable. These were related to i) environmental issues for those IPM1 systems that still relied mainly on pesticide use and had less diverse crop rotations, and ii) economic issues for IPM2 systems, mainly due to the choice of less profitable crops in the rotation, as well as to yield penalties caused by the very low pesticide use or replacing pesticides with less effective non-chemical methods. The identification of these constraints is a valuable input to the local and regional discussion on how to adopt IPM and develop more sustainable cropping systems.
Chapter
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
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Summary Since 1986, Pesticide Action Plans, with the overall aim of reducing pesticide use have been operative in Denmark. By 2004, farmers had reduced pesticide use by 58% and 20%, measured as kg active ingredient and treatment frequency index, respectively. The reduction schemes have so far not had any direct effect on the economics of farming. Reduction at farm level is mainly cost-driven and is widely supported by data from field trials, including calculations of margin over pesticide use. Farmers are generally using appropriate and reduced rates for controlling pests, diseases and weeds and are using threshold-based decisions where possible. Reduction of dose rates from full to quarter rate has improved biodiversity indicators, such as weeds, insects and birds. During the period 1998-2003, pesticides were found in 27% of samples analysed from groundwater abstraction wells with 6% exceeding the Maximum Acceptable Concentration (MAC) for drinking water (0.1µg/l). Most cases where these levels are exceeded have been caused by BAM and triazine metabolites. From 1998 to 2003, the percentage exceeding the MAC for drinking water decreased from 10% to 5%; a reduction, which is seen as the result of prohibiting pesticides with a potential for being washed out to water reservoirs. History of pesticide plans For many years, government policy in Denmark has been to remove the most harmful pesticides and minimise the use of pesticides. In 1986, the first Pesticide Action Plan was introduced. The objective was to tighten up the approval procedure and to reduce the total use of pesticides by 50% within a period of ten years. The overall aim was to protect the groundwater against pollution, and the flora and fauna against further degradation. The term Treatment Frequency Index (TFI) was introduced in 1986 and is the theoretical number of pesticide treatments per hectare, calculated by dividing the amount of pesticides sold for agriculture by the standard approved dosages. The reduction was compared to a reference TFI of 2.67, which was the average use in 1981-1985. Several attempts to develop a more precise method of determining the environmental load caused by pesticides than the Treatment Frequency Index have been made without success (Anon., 1997). The TFI is believed, in a simple way, to
Article
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Injury to weeds from sublethal doses of POST herbicides may reduce the effect of weed interference on crop yield. Information on how herbicide dose influences weed mortality, growth, and seed production is needed to assess the potential benefit of applying reduced herbicide doses. Field experiments were conducted at Mead, NE, in 2001 and 2002 to quantify velvetleaf mortality, growth, and corn–velvetleaf interference in response to varying doses of three POST herbicides. Untreated velvetleaf at six densities (0, 1, 3, 6, 12, and 20 plants m−1 corn row) was grown in mixture with corn to establish a baseline corn–velvetleaf interference relationship. Treated velvetleaf at a density of 20 plants m−1 row received one of five doses of dicamba, halosulfuron, or flumiclorac. Untreated velvetleaf height, biomass, and seed capsule production were greater in 2002 than 2001 and declined with increasing velvetleaf density in both years. Corn yield was not affected by untreated velvetleaf in 2001, but yield loss increased with increasing velvetleaf density in 2002. Mortality of herbicide-treated velvetleaf was 56% greater in 2001 than 2002 and increased with increasing herbicide dose. Maximum height of treated velvetleaf was similar for all treatments in 2001 but declined with increasing herbicide dose in 2002. Biomass and seed production of treated velvetleaf varied among herbicides in 2002 and decreased with increasing dose. Corn yield was not influenced by velvetleaf in 2001, but yield loss in response to herbicide-treated velvetleaf declined with increasing herbicide dose in 2002. Results show that the assumption that weeds surviving herbicide application are as competitive as untreated weeds is incorrect. Reduction in growth and resource consumption by herbicide-damaged weeds reduced the negative effects of weeds on corn. Nomenclature: Dicamba; halosulfuron; flumiclorac; velvetleaf; Abutilon theophrasti Medic. ABUTH; corn; Zea mays L.
Article
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Public concern of possible effects of pesticides on human health and the environment has lead to an increased pressure on farmers to optimise their use of pesticides. Reducing pesticide doses below the recommended doses whenever possible is a straightforward approach to reduce the risk of adverse side effects. To adopt this approach decision-making has to be improved. The parameters to consider optimising herbicide doses are: weed flora and growth stage, crop competitiveness, climatic conditions, application technique, formulation/adjuvant and combination with other pesticides. In Denmark this information is provided to farmers through the decision support system ‹Plant Protection Online’. Based on input on weed species and densities, climatic conditions, soil type, crop cultivar and expected yield ‹Plant Protection Online’ will provide farmers with optimum herbicide solution usually with doses lower than standard recommended doses.
Article
Injury to weeds from sublethal doses of POST herbicides may reduce the effect of weed interference on crop yield. Information on how herbicide dose influences weed mortality, growth, and seed production is needed to assess the potential benefit of applying reduced herbicide doses. Field experiments were conducted at Mead, NE, in 2001 and 2002 to quantify velvetleaf mortality, growth, and corn–velvetleaf interference in response to varying doses of three POST herbicides. Untreated velvetleaf at six densities (0, 1, 3, 6, 12, and 20 plants m-1 corn row) was grown in mixture with corn to establish a baseline corn–velvetleaf interference relationship. Treated velvetleaf at a density of 20 plants m-1 row received one of five doses of dicamba, halosulfuron, or flumiclorac. Untreated velvetleaf height, biomass, and seed capsule production were greater in 2002 than 2001 and declined with increasing velvetleaf density in both years. Corn yield was not affected by untreated velvetleaf in 2001, but yield loss increased with increasing velvetleaf density in 2002. Mortality of herbicide-treated velvetleaf was 56% greater in 2001 than 2002 and increased with increasing herbicide dose. Maximum height of treated velvetleaf was similar for all treatments in 2001 but declined with increasing herbicide dose in 2002. Biomass and seed production of treated velvetleaf varied among herbicides in 2002 and decreased with increasing dose. Corn yield was not influenced by velvetleaf in 2001, but yield loss in response to herbicide-treated velvetleaf declined with increasing herbicide dose in 2002. Results show that the assumption that weeds surviving herbicide application are as competitive as untreated weeds is incorrect. Reduction in growth and resource consumption by herbicide-damaged weeds reduced the negative effects of weeds on corn.
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.
Article
A suite of European Union (EU) legislation under a thematic strategy on the Sustainable Use of Pesticides constitutes the policy instruments supporting the wishes of the European Parliament to achieve significant reductions in the use of conventional pesticides in EU agriculture. The adoption of integrated pest management (IPM) is the main pillar of the strategy to decrease pesticide use while maintaining or expanding present levels of European food production. This paper supports this approach in principle, but argues that the rapid pace of pesticide withdrawals will decrease farm output and/or the profitability of farming. Furthermore, there are insufficient IPM component technologies and systems available to farmers which offer practical and economically viable alternatives to fill the gap in the crop protection toolbox that widens with each additional pesticide removal.
Article
Weed management must be based on integrated plant protection methods that minimise economically unacceptable loss of crop yield but preserve the contribution of weeds to biodiversity. The on-line decision support system "Weeds" has been developed to assist in achieving this balance by the selection of appropriate herbicides and the calculation of appro-priate doses to control the weeds present in individual fields. The results of field trials in spring wheat in Latvia in 2006 and 2007 showed that satisfactory weed control could be achieved and increases of yield obtained where herbicides were applied at reduced doses. Economic analyses showed that the reduced dose treatments were the most profitable.
Article
Integrated cropping systems are gaining prominence on the Canadian Prairies. Research that documents weed management, crop production and economic benefits of single and combined optimal agronomic practices is on-going and is currently being adopted by forward-thinking and innovative growers. These weed management approaches have proven to be effective. There are however, plenty of opportunities to study and improve current systems at research and farm levels. The continued improvement, extension, uptake and feedback of these systems play a key role in increasing the viability, sustainability and competitiveness of our crop industry.
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.
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.
Article
Integrated weed management (IWM) can be defined as a holistic approach to weed management that integrates different methods of weed control to provide the crop with an advantage over weeds. It is practiced globally at varying levels of adoption from farm to farm. IWM has the potential to restrict weed populations to manageable levels, reduce the environmental impact of individual weed management practices, increase cropping system sustainability, and reduce selection pressure for weed resistance to herbicides. There is some debate as to whether simple, herbicidal weed control programs have now shifted to more diverse IWM cropping systems. Given the rapid evolution and spread of herbicide-resistant weeds and their negative consequences, one might predict that IWM research would currently be a prominent activity among weed scientists. Here we examine the level of research activity dedicated to weed control techniques and the assemblage of IWM techniques in cropping systems as evidenced by scientific paper publications from 1995 to June 1, 2012. Authors from the United States have published more weed and IWM-related articles than authors from any other country. When IWM articles were weighted as a proportion of country population, arable land, or crop production, authors from Switzerland, the Netherlands, New Zealand, Australia, and Canada were most prominent. Considerable evidence exists that research on nonherbicidal weed management strategies as well as strategies that integrate other weed management systems with herbicide use has increased. However, articles published on chemical control still eclipse any other weed management method. The latter emphasis continues to retard the development of weed science as a balanced discipline.
Article
Integrated Weed Management in arable crops relies on the combination of various measures for preventing, avoiding and suppressing weeds, with the aim of reducing the reliance on herbicides and their environmental impacts. As IWM requires potentially deep changes in the cropping systems, modifying e.g. the crop sequence, the strategies for soil tillage and eventually introducing mechanical weeding, it is important to perform comprehensive evaluations of IWM-based cropping system prototypes. In this study, a Life Cycle Assessment method was used to compute several environmental impacts for four variants of IWM-based cropping system tested over a pluri-annual experiment, and compared with a standard reference. When expressed per unit of cultivated area, most environmental indicators were improved in IWM-based systems, including the energy input, greenhouse gas emission, eutrophication and acidification, and ecotoxicity and human toxicity. In-field fuel consumption was a rather minor contribution to the overall energy demand and to global warming. The ranking of the tested cropping systems was different when the indicators were expressed per unit of harvested agricultural goods or per unit of farmer's income. With these two functional units, the differences among systems tended to be weaker, and some indicators of environmental impacts were higher in IWM-based systems. Indicators focusing on biodiversity and soil quality displayed few differences among systems.
Article
The selection of the best weed control option can be improved using decision-support systems considering the different factors affecting the efficacy (weed species, growth stage, climatic conditions) and the economics of the treatments. An interactive microcomputer program called GESTINF has been developed to assist in the selection of weed control options in soybean and winter wheat. Using observed weed densities, crop weed-free yield and grain price as input data, the program estimates potential crop damage from multispecies weed complexes and ranks the different weed control options according to expected net returns. The program also gives estimates of yield loss due to weeds surviving the treatment and an environmental index indicating how hazardous the treatment is for the water-table, thus allowing a selection of treatments both on an economic and an environmental basis. The system has been tested for 4 years in different locations of north-eastern Italy. The system forecasted the yield losses observed in the field fairly accurately and proved capable of selecting appropriate interventions on the basis of type of flora and weed growth stage.
Article
Integrated pest management (IPM) will be obligatory in all European Union (EU) member states from January 1, 2014. Successful IPM implementation will depend not only on the sound guidelines and goodwill of the farmers, but also on conditions in farmers' environment. This paper presents the most important factors influencing IPM implementation in Poland. The most favorable aspects on the eve of obligatory IPM implementation are the relatively low use of plant protection products and popularity of some non-chemical methods of pest control, such as sowing cereal in mixture. The most important challenges are the improvement of advisory service and the crop structure with almost three-quarters of sown area covered by cereals.
Article
Row crop weed management decisions can be complex due to the number of available herbicide treatment options, the multispecies nature of weed infestations within fields, and the effect of soil characteristics and soil-moisture conditions on herbicide efficacy. To assist weed managers in evaluating alternative strategies and tactics, three computer programs have been developed for corn, cotton, peanut, and soybean. The programs, called HADSS� (Herbicide Application Decision Sup­ port System), Pocket HERB�, and WebHADSS�, utilize field-specific information to estimate yield loss that may occur if no control methods are used, to eliminate herbicide treatments that are inap­ propriate for the specified conditions, and to calculate expected yield loss after treatment and expected net return for each available herbicide treatment. Each program has a unique interactive interface that provides recommendations to three distinct kinds of usage: desktop usage (HADSS), internet usage (WebHADSS), and on-site usage (Pocket HERB). Using WeedEd�, an editing program, co­ operators in several southern U.S. states have created different versions of HADSS, WebHADSS, and Pocket HERB that are tailored to conditions and weed management systems in their locations. Nomenclature: Corn, Zea mays L.; cotton, Gossypium hirsutum L.; peanut, Arachis hypogea L; soybean, Glycine max L. Additional index words: Bioeconomic models, computer decision aids, decision support systems, weed management. Abbreviations: HADSS, Herbicide Application Decision Support System; PDS, postemergence-di­ rected; POST, postemergence; PPI, preplant-incorporated; PRE, preemergence.
Article
Modern weed control tactics have played a major role in the productivity of cropping systems. Herbicides have been an effective component of weed control for major crops, greatly reducing yield losses and facilitating reduced tillage systems. Although these benefits are important, weed problems, soil erosion, and environmental concerns persist. Herbicides will continue to play a key role in most production systems, but weed species will continue to evolve and weed communities shift in response to selection pressures. Weed science must develop and incorporate additional practices to create integrated management systems that diversify selection pressures and reduce environmental degradation. Integrated pest management (IPM) may provide a useful framework for the development of integrated weed management systems. The basic principles of IPM are well established and have been successfully applied to many agricultural pests. However, the application of IPM to weed management has lagged behind other pest management disciplines. Many of the concepts and approaches of IPM are relevant to weed management, but these were not developed specifically for weed management and are not sufficient to address it adequately. Principles of IPM unique to weed management need to be delineated, developed, and put into practice. Although IPM for other pests provides an excellent framework, weed science must develop its own theory, management tactics, and monitoring procedures based on the unique characteristics of weed communities.
Article
Rigid ryegrass and wild radish dominate and coexist throughout southern Australian dryland cropping regions. Widespread herbicide resistance in these species has led to adoption of diverse and complex integrated weed management practices, which require evaluation of their impact on farming systems. Therefore, a multispecies version of the bioeconomic model resistance and integrated management (RIM) has been developed to compare long-term economic and weed population outcomes of various integrated management scenarios. We have extended the original single-species ryegrass RIM model to include wild radish biology and additional weed management practices used to control this species. The multispecies model can be used to evaluate weed management scenarios for coexisting herbicide-resistant species by investigating the implications of different crop–pasture rotational sequences and of varying herbicide availability. Multispecies RIM shows that economic differences between the scenarios are not due to differences in weed densities but to differences in total weed control costs. Nomenclature: Rigid ryegrass, Lolium rigidum Gaud. LOLRI; wild radish, Raphanus raphanistrum L. RAPRA.
Article
Field experiments were conducted at Lacombe, Lethbridge, and Vegreville, Alberta, Canada and Kalispell, MO, over several years to determine the influence of recommended (minimum label) and lower-than-recommended tralkoxydim rates on wild oat seed production, spring wheat yield, and economic return. Wild oat seed production as a function of tralkoxydim rate varied considerably among locations and years. For example, at the recommended rate, wild oat seed production varied from none at both Lethbridge and Vegreville in 1994 to over 800 seeds/m2 at Vegreville in 1995. At 50% of recommended rate, seed production varied from none at Lethbridge in 1994 to over 3,000 seeds/m2 at Vegreville in 1995. In most cases, wheat yield response to tralkoxydim rate was curvilinear. Yields generally increased exponentially as rates increased up to about 40 or 50% of the recommended rate, but then plateaued as rates were increased further. In some cases economic returns tended to plateau or decrease at rates higher than this, but reductions in economic returns at the recommended herbicide rates were, in most cases, relatively slight. In contrast, at Lethbridge in 1993 and 1995 and at Kalispell in 1994 and 1996, yield and economic returns generally increased as herbicide rate increased, and there was an economic disadvantage to reducing the tralkoxydim rate below that recommended. In view of the variable effects on wild oat seed production, and the questionable economic benefit, our study suggests that reducing the rate of tralkoxydim below that recommended may not be without risk. Further studies are necessary to determine the long-term implications of returning relatively large amounts of wild oat seed to the soil seedbank at reduced herbicide rates.
Article
Size, germination and viability of seeds as well as growth of seedlings derived from three weed species were studied in a pot trial. Fallopin convolvulus (L.) A. Loeve, Galium. spurium L. and Thlaspi arvense L. were treated with MCPA or tribenuron-methyl at four doses and at five growth stages, from seedling stage to flowering, In G. spurium subnormal doses of tribenuron-methyl, applied at intermediate growth stages, greatly reduced seed weight, gennination, viability, seedling shoot biomass and root biomass. Germination and viability, as well as the shoot biomass and root biomass of seedlings, were highly correlated with seed weight. In addition, but to a smaller extent, seed weight was reduced in F. convolvidus and T. arvense by tribenuron-methyl and in G. spurium by MCPA. Germination was reduced in F. convolvulus by MCPA and in T. arvense by tribenuron-methyl. However, the effects varied greatly depending on the growth stage at application.
Article
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.
Article
Benjamin LR, Milne AE, Parsons DJ, Cussans J & Lutman PJW (2009). Using stochastic dynamic programming to support weed management decisions over a rotation. Weed Research49, 207–216.SummaryThis study describes a model that predicts the impact of weed management on the population dynamics of arable weeds over a rotation and presents the economic consequences. A stochastic dynamic programming optimisation is applied to the model to identify the management strategy that maximises gross margin over the rotation. The model and dynamic programme were developed for the weed management decision support system –‘Weed Manager’. Users can investigate the effect of management practices (crop, sowing time, weed control and cultivation practices) on their most important weeds over the rotation or use the dynamic programme to evaluate the best theoretical weed management strategy. Examples of the output are given in this paper, along with discussion on their validation. Through this study, we demonstrate how biological models can (i) be integrated into a decision framework and (ii) deliver valuable weed management guidance to users.
Article
This paper explores short and long run economic outcomes of fixed label herbicide doses versus a flexible “best efficacy targeting strategy” (BETS), which is factor adjusted to current weather and density of weeds. A herbicide efficacy model is combined with water balance, wheat yield, yield loss and weed seedbank dynamics models to construct a bioeconomic simulation model. Results with long run weather records from two contrasting rain fed wheat districts and a range of weed densities showed BETS was superior to static maximum label or half maximum dose rates at both locations, in terms of Hamiltonians representing mean net present values of current plus future benefits and costs of weed management. BETS also resulted in lower overall herbicide use, except in the case of the highest weed density where the half max dose was lower. These positive results raise the question whether such benefits from factor adjusting dose can be realised more generally, at other locations and in the cases of other weeds, crops and herbicides.
Article
In order to lower the risks associated to intensive pesticide use, efforts have been made at the European and the national level of several member countries of the European Union. In Germany, a national reduction programme for pesticides had been set up. The programme makes use of the methods elaborated in the context of the NEPTUN-project. The NEPTUN-approach had introduced several indicators to assess the intensity of pesticide use in agriculture. This approach was exemplarily applied to data from a case study region in north-eastern Germany. The aim of the paper is to discuss the strengths and weaknesses of the presented approach as based on results gained in the chosen case study region.
Article
Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here.
Evaluation of the weed module in the Danish decision support system Crop Protection Online " adapted to Norwegian conditions
  • J Netland
  • K S Torresen
  • P Rydahl
  • P Barberi
  • L Bastiaans
  • S Christensen
  • C Fernandez-Quintanilla
  • B Froud-Williams
  • A Grundy
  • P Hatcher
  • P Kudsk
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