Innovation in mechanical weed control in crop rows

Weed control within crop rows is one of the main problems in organic farming. For centuries, different weed removal tools have been used to reduce weeds in the crop rows. Stimulated by the demand from organic farmers, research in several European countries over the last decade has focused on mechanisation using harrowing, torsion finger weeding and weeding with compressed air (Pneumat). Intelligent weeders are now being developed which offer more advanced ways to control weeds, including larger ones and to leave the crop plants unharmed. One of the first commercially available intelligent weeders, the Sarl Radis from France, has a simple crop detection system based on light interception, which guides a hoe in and out of the crop row, around the crop plants. The inclusion of innovative technologies, including advanced sensing and robotics, in combination with new cropping systems, might lead to a breakthrough in physical weed control in row crops leading to significant reductions, or even elimination, of the need for hand weeding.     

Glyphosate-resistant soybean as a weed management tool: Opportunities and challenges

Transgenic soybean, resistant to glyphosate, represents a revolutionary breakthrough in weed control technology. Transgenic soybean is the most dominant among all transgenic crops grown commercially in the world. In 2000, glyphosate-resistant (GR) soybean was planted to 25.8 million hectares globally, which amounts to 58% of the total global transgenic crop area. The United States soybean area planted with GR soybean has increased from 2% in 1996 to 68% in 2001. Glyphosate-resistant soybean as a weed management tool has provided farmers with the opportunity and flexibility to manage a broad spectrum of weeds. The use of glyphosate in GR soybean offers another alternative to manage weeds that are resistant to other herbicides. The rapid increase in GR soybean area is caused by the simplicity of using only one herbicide and a lower cost for weed control. Adoption of GR soybean has resulted in a dramatic decrease in the area treated with other herbicides. Glyphosphate-resistant soybean should not be relied on solely to the exclusion of other weed control methods, and should be used within integrated weed management systems. Over-reliance on GR soybean could lead to problems such as shifts in weed species and population, and the development of glyphosate-resistant weeds. The challenge is for soybean farmers to understand these problems, and for weed scientists to communicate with farmers that continuous use of glyphosate may diminish the opportunity of GR soybean as a weed management tool in the future.     

Comparison of crop and weed height,for potential differentiation of weed patches at harvest

Weeds and weed control are major production costs in global agriculture, with increasing challenges associated with herbicide‐based management because of concerns with chemical residue and herbicide resistance. Non‐chemical weed management may address these challenges but requires the ability to differentiate weeds from crops. Harvest is an ideal opportunity for the differentiation of weeds that grow taller than the crop, however, the ability to differentiate late‐season weeds from the crop is unknown. Weed mapping enables farmers to locate weed patches, evaluate the success of previous weed management strategies, and assist with planning for future herbicide applications. The aim of this study was to determine whether weed patches could be differentiated from the crop plants, based on height differences. Field surveys were carried out before crop harvest in 2018 and 2019, where a total of 86 and 105 weedy patches were manually assessed respectively. The results of this study demonstrated that across the 191 assessed weedy patches, in 97% of patches with Avena fatua (wild oat) plants, 86% with Raphanus raphanistrum (wild radish) plants and 92% with Sonchus oleraceus L. (sow thistles) plants it was possible to distinguish the weeds taller than the 95% of the crop plants. Future work should be dedicated to the assessment of the ability of remote sensing methods such as Light Detection and Ranging to detect and map late‐season weed species based on the results from this study on crop and weed height differences.     

United States Department of Agriculture-Agricultural Research Service research on pest biology: weeds

Over 125 permanent full-time scientists conduct research within the USDA Agricultural Research Service (ARS) on issues related to weeds. The research emphasis of most of these scientists involves ecology and management or biological control of weeds. Many scientists perform research on weed biology as components of their primary projects on weed control and integrated crop and soil management. Describing all ARS projects involved with weed biology is impossible, and consequently only research that falls within the following arbitrarily chosen topics is highlighted in this article: dormancy mechanisms; cell division; diversity of rangeland weeds; soil resources and rangeland weeds; poisonous rangeland plants; horticultural weeds; weed traits limiting chemical control; aquatic and semi-aquatic weeds; weed/transgenic wheat hybrids; seedbanks, seedling emergence and seedling populations; and weed seed production. Within these topics, and others not highlighted, the desire of ARS is that good information on weed biology currently translates or eventually will translate into practical advice for those who must manage weeds.     

Image-based weed recognition and control: Can it select for crop mimicry?

As highly adaptable plants, weeds have evolved numerous mechanisms to evade control in agroecosystems. For example, reliance on herbicides has resulted in widespread evolution of resistance in many species. Minimising weed adaptation is a major driver for integrated weed management strategies. Crop mimicry is a notable example of weed adaptation, where weed species evolve to avoid control by mimicking aspects of the crop phenotype. Visual selection by hand weeding has been documented to select for crop mimics that are difficult to distinguish from the crop at the vegetative stage. With recent advancements in weed recognition technologies, image-based weed recognition for in-crop, site-specific weed control is on the cusp of becoming widely adopted. Whilst the control methods used in site-specific weed control will be varied (e.g., spot spraying or lasers), they will share weed recognition technology. Visual selection via image-based deep learning represents a selection pressure for weeds that can evade detection by mimicking crops. This mimicry may reduce weed recognition accuracy and thus weed control efficacy over time and result in difficult to manage mimetic weed phenotypes. Therefore, it is timely to explore the potential for selection of crop mimics by image-based weed recognition algorithms.     

Predicting the risk of weed infestation in winter oilseed rape crops

Chemical weed control before crop and weed emergence is a systematic practice in winter oilseed rape crops in France. It would be profitable both for farmers and the environment to predict the level of weed infestation early on in the growing season and to control weeds only when necessary using post‐emergence weed control. The objective of this paper was to develop and evaluate simple models to predict weed biomass in oilseed rape crops. The model input variables were related to weed population characteristics and farmers’ practices. The models can be used to classify oilseed rape plots into two categories: plots with a level of weed infestation above a threshold or those with level of weed infestation below a threshold. A data set including 3 years of experiments, conducted across several regions in France, was used to estimate the parameters and to evaluate the models. High values of sensitivity and specificity were obtained when weed biomass was predicted as a function of sowing date, type of soil tillage, soil mineral nitrogen, crop density, weed density at emergence, and main characteristics of the most abundant weed species. Model performance strongly decreased when input variables related to the weed population were not taken into account. The best models correctly classified 90% of the plots with high weed infestation and 64% of the plots with low weed infestation.     

转基因耐草甘膦作物的环境安全性

世界每年因草害造成的作物产量损失达950亿美元,为了简便有效地防除多种杂草,农民希望喷施杀草谱广的除草剂。转基因耐除草剂作物的种植为农民提供了更多的除草剂选择,在扩大杀草谱、提高除草效果、增加作物安全性、改善环境、简化栽培等方面起到了积极作用。转基因耐除草剂作物的大面积种植也引起了全球对其环境安全问题的广泛关注。本文以耐草甘膦作物为例,对国内外环境安全的相关研究结果进行归纳和总结,以期为我国耐草甘膦转基因作物的环境安全评价及耐草甘膦作物的管理提供参考。     

Site-specific weed control technologies

Site-specific weed control technologies are defined as machinery or equipment embedded with technologies that detect weeds growing in a crop and, taking into account predefined factors such as economics, take action to maximise the chances of successfully controlling them. In this study, we describe the basic parts of site-specific weed control technologies, comprising weed sensing systems, weed management models and precision weed control implements. A review of state-of-the-art technologies shows that several weed sensing systems and precision implements have been developed over the last two decades, although barriers prevent their breakthrough. Most important among these is the lack of a truly robust weed recognition method, owing to mutual shading among plants and limitations in the capacity of highly accurate spraying and weeding apparatus. Another barrier is the lack of knowledge about the economic and environmental potential for increasing the resolution of weed control. The integration of site-specific information on weed distribution, weed species composition and density and the effect on crop yield, is decisive for successful site-specific weed management.     

Could the dawn of Level 4 robotic weeders facilitate a revolution in ecological weed management?

Ecological weed management (EWM) considers that not all non-crop plants cause harm, and that non-harmful species ‘aliae plantae’ should be retained to provide multiple positive benefits. Only plants causing ‘significant harm’ are defined as weeds and should be controlled. However, this is difficult to achieve with current herbicide and mechanical weeding technologies. Robotic weeders may be able to facilitate EWM. Four Levels of robotic weeders are defined: Level 1 are row followers; Level 2 identify individual crop plants and weed around them; Level 3 individually identify all plants and individually kill all non-crop plants; Level 4 weeders individually distinguish crop plants, aliae plantae, and weeds and only kill the weeds, thus facilitating EWM. Currently only Levels 1–3 robotic weeders exist. The aim of proposing Level 4 robotic weeders is to highlight, particularly to roboticists, that the end goal of robotic weeding should not be crop monocultures, but biodiverse fields through EWM. It is envisaged that Level 4 robotic weeders would not just operate in vegetable crops, which are the current focus of Level 3 weeders, but in all crops, such as fruit trees, where they could, for example, control weeds in living mulches. It is therefore considered essential that weed scientists and roboticists collaborate to ensure that robotic weeders achieve EWM, not monocultures. If this vision can be realised, it could usher in a revolution in weed management.     

Weed management on Vertisols for small-scale farmers in Ghana

Vertisols and vertic clays represent a vast crop production resource (300 million hectares world-wide) that is underutilized, mainly because of problems with soil physical characteristics (particularly relating to water) and weeds. These montmorillonitic clays are generally more fertile and have higher water-holding capacities than many tropical soils, but they are difficult to manage as they are very sticky when wet and hard and cloddy when dry. Research in Ghana has shown that it is technically possible to increase crop yields by 90% in normal wet seasons by using raised (camber) beds to control water, but further increases in yield potential are prevented by highpopulations of Cyperus rotundus L. and Imperata cylindrica (L.) Raeuschel. These challenges have been addressed by research on farms and on a research station to determine the effectiveness of glyphosate and camber beds for weed and water management and crop production in maize-based farming systems. Field trials have shown that tuber populations of C. rotundus could be reduced by 95% after glyphosate at 1.8 kg a.e. ha-1 was applied at the beginning of four cropping seasons during 1997 and 1998. The combination of glyphosate for weed control and camber beds to shed excess water produced maize grain yields of 3.5 t ha-1 - a significant increase over the typical yields of ～1.0 t ha-1 withtraditional methods ofhoe-weeding onflat land. Economic evaluations have shown that the returns to small-scale farmers could be considerably increased by the use of glyphosate for weed control.     

Benchmark study on glyphosate-resistant cropping systems in the United States. Part 5: Effects of glyphosate-based weed management programs on farm-level profitability

BACKGROUND: Glyphosate‐resistant (GR) crops have changed the way growers manage weeds and implement control strategies. Since the introduction of GR crops, growers in many instances have relied on glyphosate almost exclusively to control a broad spectrum of weeds. This overreliance on glyphosate has resulted in the evolution of glyphosate resistance in some weed species. Growers and scientists are concerned about the sustainability of GR crops and glyphosate. When a grower is making decisions about weed control strategies, economic costs and benefits of the program are primary criteria for selection and implementation. Studies across six states were initiated in 2006 to compare the economics of using a weed resistance best management practice (BMP) system with a grower's standard production system. RESULTS: Resistance BMP systems recommended by university scientists were more costly but provided similar yields and economic returns. Rotation of GR crops resulted in a higher net return (maize and soybean) compared with continuous GR crop (cotton or soybean) or rotating a GR crop with a non‐GR crop (maize). CONCLUSION: Growers can implement weed resistance BMP systems with the confidence that their net returns will be equivalent in the short run, and, in the long term, resistance BMP systems will prevent or delay the evolution of GR weeds in their fields, resulting in substantial savings. Copyright © 2011 Society of Chemical Industry     

Managing arable weeds for biodiversity

As a result of the recent intensification of crop production, the abundance and diversity of UK arable weeds adapted to cultivated land have declined, with an associated reduction in farmland birds. A number of questions need to be addressed when considering how these declines can be reversed. Firstly, can the delivery of crop production and biodiversity be reconciled by spatially separating cropping from designated wildlife areas? A number of subsidised environmental schemes in the UK take this approach and are focused on establishing vegetation cover on uncropped land. However, because of the lack of regular disturbance in these habitats, they are dominated by perennials and they therefore have limited potential for promoting the recovery of annual weed populations. A number of farmland bird species also rely on the provision of resources in field centres, and it is therefore likely that the recovery of their populations will rely on weed management options targeted at the cropped areas of the field. This raises two further questions. Firstly, is it possible to identify beneficial weed species that are relatively poor competitors with the crop and also have biodiversity value? Secondly, are the tools available to manage these species at acceptable levels while controlling pernicious weeds? A number of approaches are being employed to answer these questions, including predicting yield loss from weed competition models and exploiting herbicide selectivity. The further development of these tools is crucial if farmer opposition to managing weeds in crops is to be overcome. Copyright © 2007 Society of Chemical Industry     

Benchmark study on glyphosate-resistant crop systems in the United States. Part 2: Perspectives

A six-state, 5 year field project was initiated in 2006 to study weed management methods that foster the sustainability of genetically engineered (GE) glyphosate-resistant (GR) crop systems. The benchmark study field-scale experiments were initiated following a survey, conducted in the winter of 2005-2006, of farmer opinions on weed management practices and their views on GR weeds and management tactics. The main survey findings supported the premise that growers were generally less aware of the significance of evolved herbicide resistance and did not have a high recognition of the strong selection pressure from herbicides on the evolution of herbicide-resistant (HR) weeds. The results of the benchmark study survey indicated that there are educational challenges to implement sustainable GR-based crop systems and helped guide the development of the field-scale benchmark study. Paramount is the need to develop consistent and clearly articulated science-based management recommendations that enable farmers to reduce the potential for HR weeds. This paper provides background perspectives about the use of GR crops, the impact of these crops and an overview of different opinions about the use of GR crops on agriculture and society, as well as defining how the benchmark study will address these issues.     

A review of non-chemical weed control on hard surfaces

Weed control research to date has mainly focused on arable land, especially regarding herbicides, but also regarding non‐chemical methods. Some of these experiences can be applied to hard surface areas. However, weeds on hard surface areas cause problems that are different from those on arable land. Additionally, crop tolerance does not need to be considered when choosing an appropriate weed control method on these areas. The aim of this review is to describe current knowledge of weeds and weed control methods on hard surface areas and reveal potential ways of advancement. One of the shortcomings of non‐chemical weed control on hard surfaces thus far, is a lack of proper definition of efficiency of the weed control methods. To obtain effective control, more frequently repeated treatments are required than chemical weed management, thereby increasing the costs of labour and fuel. One way to reduce costs can be by adjusting the level of control to the required visual street quality. Weeds are adapted to the hard surface environment and may be less susceptible to certain control methods. This review indicates that for efficient weed control on hard surfaces there is a need for combining weed control techniques, applying sensors for detecting weeds, adapting the energy dose to type of weed flora and prevention of weeds by improved construction of new surfaces.     

Improved management of Avena ludoviciana and Phalaris paradoxa with more densely sown wheat and less herbicide

Summary The effectiveness of crop competition for better weed control and reducing herbicide rates was determined for Avena ludoviciana and Phalaris paradoxa . Four experiments, previously broadcast with seeds of the two weeds in separate plots, were sown with three wheat densities, and emerged weeds were treated with four herbicide doses (0–100% of recommended rate). The measured crop and weed traits were first analysed across experiments for treatment effects. Grain yield and weed seed production data were then analysed using cubic smoothing splines to model the response surfaces. Although herbicide rate for both weeds and crop density for P. paradoxa had significant linear effects on yield, there was a significant non-linearity of the response surface. Similarly, herbicide rate and crop density had significant linear effects on weed seed production, and there was significant non-linearity of the response surface that differed for the weed species. Maximum crop yield and reduction in seed production of P. paradoxa was achieved with approximately 80 wheat plants m⁻² and weeds treated with 100% herbicide rate. For A. ludoviciana , this was 130 wheat plants m⁻² applied with 75% herbicide rate. Alternatively, these benefits were achieved by increasing crop density to 150 plants m⁻² applied with 50% herbicide rate. At high crop density, application of the 100% herbicide rate tended to reduce yield, particularly with the A. ludoviciana herbicide, and this impacted adversely on the suppression of weed seed production. Thus, more competitive wheat crops have the potential for improving weed control and reducing herbicide rates.     

A risk-qualified approach to calculate locally varying herbicide application rates

Weed competition can decrease crop yield and profit. Herbicides are applied to reduce weed populations, minimize crop loss and maximize profit. Traditional practice is to apply herbicides at a uniform rate over an entire field. Complete knowledge of the weed distribution and appropriate instrumentation on the spraying equipment would allow the farm manager to apply the 'correct' locally varying herbicide application rate. The locally variable rate would be greater in areas of high weed density and less where there are few weeds. A locally varying treatment would have both economic and environmental advantages. A major challenge facing farm managers is the unavoidable uncertainty in the spatial distribution of weeds in any particular field. This uncertainty in weed distribution influences the optimal locally varying herbicide rate. A mathematical model is presented to calculate the optimal herbicide application rate using geostatistical models of uncertainty in weed density combined with principles from decision making. Weed data from a 34-ha field near Saskatoon, Saskatchewan, Canada, illustrate the application of these tools. Weed control was achieved with a significant reduction in total herbicide use.     

发展化学除草重视综合治理

我国农田杂草有２５０多种，全国农田受草害面积４３００多万ｈｍ２，平均受草害减产１３．４％，每年减产粮食１７５０万ｔ，皮棉２５．５万ｔ和大豆５０万ｔ。传统农业生产采用机械作业及人力等除草。随着农村经济的发展，化学除草面积迅速扩大，全国农田化学除草面积从１９７５年的１７０万ｈｍ２增加到１９９５年的４１３３万ｈｍ２。但是，长期化学除草也带来了除草剂土壤残留对后茬作物药害、农田杂草种群更替和产生抗药性等新问题。必须重视农田杂草综合治理，通过采用各种有效的农业技术措施，为农作物保持良好的生态条件，结合化学除草才是最有效的防除杂草方法     

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.     

The Potential Benefits of Weeds with Reference to Small Holder Agriculture in Africa

Weed control is one of the most important crop protection activities undertaken in both intensive and low-input farming systems. However, even under intensive systems, crop protection which is less dependent on pesticides may require that weeds be managed to obtain a balance between crop and non-crop vegetation to encourage an increase in natural enemies of crop pests. In the low-input farming systems which sustain much of the rural population of Africa, weed control is usually done by hand and clean weeding is often beyond the labour resources of the farming family. The vegetational diversity of peasant agriculture in Africa to which weeds make their contribution, helps to decrease the risk of disease and pest epidemics. In addition to the pest control benefits of a diverse agroecosystem, weeds contribute to the resource base of the rural community, providing a source of secondary foods, medicines and insecticides. Weed control within an integrated crop protection system appropriate to the needs of the resource-poor farmer, requires that weeds are managed in such a way that their biodiversity is maintained and the more useful species retained within the field or field margin. Those weeds with high food potential or which have pesticidal or medicinal properties might be deliberately encouraged within the crop or field margins. Certain weed species may harbour important pests or diseases of local crops and therefore should be selectively removed. The paper reviews and discusses the literature on the beneficial and deleterious effects of weeds and argues for a weed management strategy which balances the effects of weed competition on crop production with the ethnobotanical and pest control attributes of individual weed species and weed communities.     

Advancing cover cropping in temperate integrated weed management

The effects of cover crops on weeds and the underlying mechanisms of competition, physical control and allelopathy are not fully understood. Current knowledge reveals great potential for using cover crops as a preventive method in integrated weed management. Cover crops are able to suppress 70–95% of weeds and volunteer crops in the fall‐to‐spring period between two main crops. In addition, cover crop residues can reduce weed emergence during early development of the following cash crop by presenting a physical barrier and releasing allelopathic compounds into the soil solution. Therefore, cover crops can partly replace the weed suppressive function of stubble‐tillage operations and non‐selective chemical weed control in the fall‐to‐spring season. This review describes methods to quantify the competitive and allelopathic effects of cover crops. Insight obtained through such analysis is useful for mixing competitive and allelopathic cover crop species with maximal total weed suppression ability. It seems that cover crops produce and release more allelochemicals when plants are exposed to stress or physical damage. Avena strigose, for example, showed stronger weed suppression under dry conditions than during a moist autumn. These findings raise the question of whether allelopathy can be induced artificially. © 2019 Society of Chemical Industry