Use of airborne multispectral imagery to discriminate and map weed infestations in a citrus orchard

Reliable information on weed abundance and distribution within fields is essential for weed management in agricultural systems. Such information is necessary to adopt localized and variable rates of herbicide spraying, thus reducing chemical waste, crop damage, and environmental pollution. This paper examined the potential of airborne multispectral imagery to discriminate and map weed infestations in an experimental citrus orchard in Japan. Using an airborne digital sensor, multispectral imagery was acquired over the study site on 10 April 2003. The obtained reflectance imagery was analyzed using an image object-based approach in eCognition. After creating image objects on the image, the spectral information for weeds and citrus, represented by corresponding selected sample image objects, was extracted. Significant differences in the spectral characteristics between weeds and citrus were observed in each of the red, green, and blue wavebands. The simple average values of these wavebands were used to classify image objects with the nearest neighbor algorithm. Maps were generated with different classes or levels of class groups. A subsequent accuracy assessment demonstrated that the weeds were successfully discriminated from other image objects with a classification accuracy of 99.07%. Therefore, maps generated based on the classification result could provide valuable information for developing a site-specific weed management program for the study orchard.     

Mapping Ridolfia segetum patches in sunflower crop using remote sensing

Ridolfia segetum is a frequent umbelliferous weed in sunflower crops in the Mediterranean basin. Field and remote sensing research was conducted in 2003 and 2004 over two naturally infested fields to determine the potential of multispectral imagery for discrimination and mapping of R. segetum patches in sunflower crops. The efficiency of the four wavebands blue (B), green (G), red (R) and near‐infrared (NIR), selected vegetation indices and the spectral angle mapper (SAM) classification method were studied using aerial photographs taken in the late vegetative (mid‐May), flowering (mid‐June) and senescence (mid‐July) crop growth stages. Discrimination efficiency of R. segetum patches in sunflower crops is consistently affected by their phenological stages, in this order: flowering > senescence > vegetative. In both fields, R. segetum patches were efficiently discriminated in mid‐June, corresponding to the flowering phase, by using the waveband G, the ratio R/B or SAM with overall accuracies ranging from 85% to 98%. The application of the median‐filtering algorithm to any of the classified images improved the accuracy. Our results suggest that mapping R. segetum weed patches in sunflower to implement site‐specific weed management techniques is feasible with aerial photography when images are taken from 8 to 10 weeks before harvesting.     

Evaluating the accuracy of mapping weeds in fallow fields using airborne digital imaging: Panicumeffusum in oilseed rape stubble

The potential accuracy of using airborne multispectral imaging to map weed patches rapidly in a fallow field has been evaluated. An image of a field of oilseed rape ( Brassica napus L.) stubble interspersed with Panicum effusum R. Br. was acquired using a four-camera airborne digital imaging system; recording in the infrared, red, green and blue wavebands. The image was converted into georectified weed maps using supervised and unsupervised classification procedures. Comparison of the airborne-derived maps with an accurate weed map compiled from a detailed ground survey demonstrated that weed:non-weed classification and mapping accuracies of better than 87% are possible. The limitations of assessing the accuracy of classified imagery using ground-truth data of similar spatial resolution are discussed.     

麻类作物田杂草种类与防除技术

杂草常伴随麻类作物滋生,与其争光争肥争水,严重影响其生长、降低产量和品质。因此,有效防除麻田杂草尤为必要。文章概述了我国麻类作物生产现状,主要麻类作物田杂草危害、杂草种类及防除技术。     

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     

Development of chemical weed control and integrated weed management in China

More than 200 species of weeds are infesting main crop fields in China, among which approximately 30 species are major weeds causing great crop yield losses. About 35.8 million hectares of crop fields are heavily infested by weeds and the annual reduction of crop yields is 12.3–16.5% (weighted average). Along with rural economic development, approximately 50% of the main crop fields undergo herbicide application. Chemical weed control has changed cultural practices to save weeding labor in rice, wheat, maize, soybeans and cotton. At the same time, continuous use of the same herbicides has caused weed shift problems and weed resistance to herbicides. Consequently, integrated weed management in main crops is being developed.     

Contribution of allelopathic effects to the overall weed suppression by different cover crops

Cover crops can suppress weeds within agricultural fields due to competitive and allelopathic effects. Glasshouse experiments were conducted to evaluate the relative proportions of allelopathic effects to the total weed inhibition. Six different cover crop species were combined with three weed species in the presence or absence of active carbon over a period of four weeks. Active carbon was used as an adsorbent for allelopathic substances in the soil. Our study revealed that the competition between cover crops and weeds shifted, possibly due to the minimisation of allelopathic effects by active carbon in the soil. We assume that the degree of cover crops allelopathic effects on weeds is species‐specific, both on the side of cover crops and on the weed side. The cover crops Raphanus sativus, Fagopyrum esculentum and Avena strigosa showed the highest allelopathic weed suppression with up to 28%. Additionally, Stellaria media turned out to be the most sensitive weed against allelopathic effects induced by all cover crops, except for Linum usitatissimum and Guizotia abyssinica. The knowledge about the contribution of competitive and allelopathic effects by cover crops would help to create cover crop mixtures with high weed suppressive ability.     

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     

Influence of sowing density and spatial pattern of spring wheat (Triticum aestivum) on the suppression of different weed species

To better understand the potential for improving weed management in cereal crops with increased crop density and spatial uniformity, we conducted field experiments over two years with spring wheat ( Triticum aestivum ) and four weed species: lambsquarters ( Chenopodium album ) , Italian ryegrass ( Lolium multiflorum ), white mustard ( Sinapis alba ), and chickweed ( Stellaria media ). The crops were sown at three densities (204, 449, and 721 seeds m⁻²) and in two spatial patterns (normal rows and a highly uniform pattern), and the weeds were sown in a random pattern at a high density. In most cases, the sown weeds dominated the weed community but, in other cases, naturally occurring weeds were also important. There were strong and significant effects regarding the weed species sown, the crop density, and the spatial distribution on the weed biomass in both years. The weed biomass decreased with increased crop density in 29 out of 30 cases. On average, the weed biomass was lower and the grain yield was higher in the uniform compared to the row pattern in both 2001 and 2002. Despite the differences in weed biomass, the responses of L. multiflorum , S. media , and C. album populations to crop density and spatial uniformity were very similar, as were their effects on the grain yield. Sinapis alba was by far the strongest competitor and it responded somewhat differently. Our results suggest that a combination of increased crop density and a more uniform spatial pattern can contribute to a reduction in weed biomass and yield loss, but the effects are smaller if the weeds are taller than the crop when crop–weed competition becomes intense.     

Weed flora in the Middle Valley of the Guadalquivir, Spain

A floristic study of the weeds in irrigated crops in the Guadalquivir River Valley (southern Spain) revealed a total of 284 species in the 267 fields surveyed, of which about 100 can be considered highly harmful. The families with the highest numbers of species were Compositae, Gramineae, Leguminosae, Cruciferae and Umbelliferae. Although 77·8% of the species were therophytes, geophytes were important in spring-sown crops. Most species were of Mediterranean origin, especially in autumn-sown crops; Cosmopolitan and Neotropical species were more important in the spring-sown crops. At the early and late crop growth stages 7% and 10%, respectively, of the fields had severe or very severe infestations. The relationships between the main weed species and crops were studied by cluster analysis, using the corrected frequency of each species in each crop as the reference parameter. This allowed classification of the species into subgroups and hierarchical groups according to their agro-ecological preferences. A close relationship was found between a given crop, its cycle and the usual soil management practices and the phenology of certain species, reflecting the influence of these factors in restricting the germination period. The analysis differentiated the typically winter, summer and intermediate weed floras.     

Integration of soil, crop and weed management in low-external-input farming systems

Greater adoption and refinement of low-external-input (LEI) farming systems have been proposed as ways to ameliorate economic, environmental and health problems associated with conventional farming systems. Organic soil amendments and crop diversification are basic components of LEI systems. Weed scientists can improve the use of these practices for weed management by improving knowledge of four relevant ecological mechanisms. First, multispecies crop rotations, intercrops and cover crops may reduce opportunities for weed growth and regeneration through resource competition and niche disruption. Secondly, weed species appear to be more susceptible to phytotoxic effects of crop residues and other organic soil amendments than crop species, possibly because of differences in seed mass. Thirdly, delayed patterns of N availability in LEI systems may favour large-seeded crops over small-seeded weeds. Finally, additions of organic materials can change the incidence and severity of soil-borne diseases affecting weeds and crops. Our research on LEI sweetcorn and potato production systems in central and northern Maine (USA) suggests that these mechanisms can reduce weed density and growth while maintaining crop yields. Low-external-input farming systems will advance most quickly through the application of interdisciplinary research focused on these and other ecological mechanisms.     

Using a competition model to quantify the optimal trade-off between machine vision capability and weed removal effectiveness

The algorithm of an optical detection system was first investigated for its ability to correctly classify transplanted crops and weeds during the critical early stages of crop establishment and its robustness over a range of different crop species. The trade-off was then examined between increasing the sensitivity of the detection system vs. the possibility of, in doing so, misclassifying some crop plants as weeds and inadvertently removing them. This was achieved by running a competition model using parameters derived from the image analysis and assessing the outcome of scenarios in terms of yield. The optimum parameter values to maximize the detection of the crop and the optimum parameter values to maximize the detection of the weed appeared relatively insensitive to time of image capture or weed density. They also appeared insensitive for different crop species where the crop had similar growth habit. However, competition scenarios indicated that the detection system parameter settings to achieve optimum yields were sensitive to the competitive ability of the weed species. For Veronica persica, crop yield was more sensitive to accidental crop removal than from competition. In contrast, in the presence of Tripleurospermum inodorum, yield loss was more attributable to weed competition. Importantly, linking the detection system with the competition model illustrated the principle that optimum yield may not necessarily be obtained by maximizing weed removal or minimizing crop removal. This first example of combining a detection system with a competition model presents a new opportunity to quantify the sensitivity of image classification in terms of yield.     

上海郊区农田杂草危害调查及其防除策略

根据农田杂草的相对覆盖度、高度、多度制订了5级目测草害调查方法,三年中调查了不同类型田5500块,调查结果表明,稗、异型莎草在稻田出现频率达100％和93％,危害面积达35.2％和23.2％;看麦娘、牛繁缕、春蓼在麦田出现频率为74.0％、86.0％、56.5％,危害面积达29.16％、32.84％、18.72％;千金子、马唐在棉田出现频率为99.6％、94.0％,危害面积达58.8％、36.4％;危害的种类、程度因土壤pH、轮作制度、土质、防除水平不同而异。在防除工作中要抓住主要作物和重点草害,注重农业防除,协调必要的化学除草。     

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.     

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.     

Weed communities respond to changes in the diversity of crop sequence composition and double cropping

Agricultural intensification, besides increasing land productivity, also affects weed communities. We studied weed shifts in cropping sequences differing in the identity and number of crops grown. We also evaluated whether dissimilar weed communities in different cropping systems converge towards more similar communities, when the same sequence is cropped during 2 years. In three locations in the Rolling Pampa, Argentina, field experiments were conducted including five cropping systems in the first year (winter cereal/soyabean, field pea/soyabean, and field pea/maize double crops, and maize and soyabean as single crops), while the same sequence was grown in the following 2 years (wheat/soyabean double crop and maize). Changes in weed community composition and structure were analysed through multivariate analyses and frequency–species ranking plots. Weed communities differed first among sites, while weed shifts within each site were mainly associated with growing season and crop type. Differences among crop sequences were higher in the first year, mostly related to specific crop grown, rather than to the number of crops in the sequences. Differences were reduced when the same sequence was grown during two consecutive seasons. Frequency of highly common weeds was negatively associated with the number of days with high crop cover. Our findings contribute to understand weed shifts in consecutive growing seasons, which may help readapting crop sequences to reduce the occurrence of abundant weed species.     

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.     

WEEDS OF TOMATO AND CORN FIELDS IN TWO REGIONS OF ONTARIO

Summary. Amaranthus retroflexus, Chenopodium album, Ambrosia artemisiifolia, Setaria glauca, S. viridis and Echinochloa crusgalli were the most widespread and abundant of the 103 weed species found in eighty-eight fields of tomatoes ( Lycopersicon esculentum ) and sweet corn ( Zea mays ) surveyed in Prince Edward County and in Essex and Kent Counties during 1960 and 1961. None of the important weeds in either crop occurred exclusively in that crop. Differences in weed floras were greater between regions than between crops. Abutilon theophrasti, Euphorbia maculata, Apocynum cannabinum var. suksdorfii and Physalis virginiana var. subglabrata , important weeds in both crops in Essex and Kent, were not found in any surveyed field in Prince Edward County. Average numbers of weed species per field were 15.7 in Prince Edward County and 12.9 in Essex and Kent. Small dense infestations of Fumaria officinalis and Salvia reflexa , rare weeds in Canada, were discovered in Prince Edward County.
Mauvaises herbes des cultures de tomates et du maïs dans deux régions de l'Ontario     

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.     

Effect of stale seedbed preparations and subsequent weed control in lettuce (cv. Iceboll) on weed densities

The effects of stale seedbed preparations and several weed control methods on the emergence of weeds in lettuce were studied. The specific goal was to evaluate the use of a stale seedbed in combination with chemical or mechanical weed control methods in the field. Depending on location and year, stale seedbed preparations followed by weed control prior to planting reduced the amount of weeds during crop growth by 43–83%. Control of the emerged seedlings after a stale seedbed preparation was more effective with glyphosate than with a rotary harrow. Covering the rotary harrow during control to prevent light reaching the soil improved its effect on the weed density during crop growth in two of 3 years. Radiation with far red light (FR) did not reduce the number of emerging weeds in this study. Mechanical control by finger weeder, torsion weeder and hoe was applied without stale seedbed preparations. These measures reduced the weed densities by 88–99%, compared with the untreated control and were more effective than chemical weed control with carbetamide and chlorpropham. The results show that the stale seedbed technique in combination with mechanical control of emerging weeds can reduce the weed population during crop growth as effectively as chemical control. The technique may therefore help reduce the use of herbicides in lettuce crops in the future.