Soil and Weed Survey for Spatially Variable Herbicide Application on Railways

Weed control on railways is frequently done by herbicide application, using large amounts of chemicals and labour. Only a few hectares of surface area on a railway can be many kilometres long so high levels of spatial variability of soils and weeds are expected. Railway sprayers use similar technology to crop sprayers so it is possible to adopt concepts from precision agriculture for weed control. The objective of this study was to evaluate spatial variability of soils and weeds on railways in order to define weed control strategies and basic characteristics of a railway sprayer. This work is part of a research project aiming at the development of a system for spatially variable herbicide application on railways. Soil and weed data were collected from five different railway companies in Brazil. These data were used to simulate treatment maps based on weed control strategies and to estimate technical requirements for spatially variable herbicide application. The results showed that soil and weed survey gave important information for defining weed control strategies and spraying equipment. The sprayer must treat the three swaths (left, central and right parts of the railway surface) separately applying at least two different herbicides at the same time. On average, a variable dose rate application based on the treatment maps generated in this work could save up to 59% of herbicides.     

Beyond patch spraying: site-specific weed management with several herbicides

Site-specific weed management can include both limiting herbicide application to areas of the field where weed pressure is above the economic threshold (patch spraying) and varying the choice of herbicide for most cost-effective weed control of local populations. The benefits of patch spraying with several, postemergence herbicides in irrigated corn were evaluated in simulation studies using weed counts from 16 fields. Patch spraying with one, two or the number of herbicides that maximized net return for a field was simulated. With patch spraying of one herbicide, the average area of a field left untreated is 34.5%. Net return increases by $3.09 ha⁻¹ compared to a uniform application without decreasing crop yield. Additional herbicides increase the average benefits with just 4% more of the field treated. With two herbicides, the increase in net return is almost tripled and herbicide use is reduced nearly 10-fold compared to patch spraying with one herbicide, and weed control is better than the uniform application in 10 fields. Using more than two herbicides for patch spraying further reduces weed escapes, but herbicide use is greater than a uniform application in 10 fields. Growers might be more willing to adopt patch spraying if more than one herbicide is used in a field.     

The Economic Impact of Site-Specific Weed Control

In order to evaluate economic and ecological benefits, site-specific weed control was realised in a 4-year experiment on five fields with a GPS-guided sprayer. An average of 54% of the herbicides could be saved. Savings were strongly dependent on crop and year. For grass weed herbicides, the savings were 90% in winter cereals, 78% in maize, and 36% in sugar beet. For herbicides against broadleaf weeds, 60% were saved in winter cereals, 11% in maize, and 41% in sugar beet. The monetary savings resulting from the reduction in herbicide use varied between the crops, depending on the amount of herbicides saved and the price of the herbicides. In maize, savings of 42euro/ha were realised, in winter wheat of 32euro/ha, in winter barley of 27euro/ha and in sugar beet of 20euro/ha. Large sections of the fields needed herbicide treatment significantly less frequently. In those areas where weed density remained below the weed control threshold, flora and fauna were allowed to establish largely without disturbance.     

Site-Specific Herbicide Decision Model to Maximize Profit in Winter Wheat

A user-friendly computerized agricultural herbicide decision model has been developed for selecting profitable site-specific herbicide applications in winter wheat. The model is based on 6 years of field research in southeastern Washington State, USA. The model calibrates herbicide applications to management unit weed densities, soil organic matter, soil moisture, and preceding management, as well as to expected input and output prices. The model increased broadleaf herbicide rates by an average 0.65 of label rates compared to the recommendations by farmers and weed science professionals, but cut the more expensive grass herbicides by an average 0.56 of label rates. The model increased average projected profitability, excluding model application costs, by 65% compared to four other criteria for determining application rates. The profitability increase relative to local farmers was 19%. Both the model and the cooperating farmers properly chose to use no grass herbicides on the study sites, but the weed science experts chose to use up to 1.0 of label rates. The estimated payoff from using the model substantially exceeded the cost of weed scouting and other information collection. Determining economically optimal sampling and management units is an important challenge for the adoption of precision agriculture models like the one developed in this study.     

Development of an Image Processing System and a Fuzzy Algorithm for Site-Specific Herbicide Applications

In precision farming, image analysis techniques can aid farmers in the site-specific application of herbicides, and thus lower the risk of soil and water pollution by reducing the amount of chemicals applied. Using weed maps built with image analysis techniques, farmers can learn about the weed distribution within the crop. In this study, a digital camera was used to take a series of grid-based images covering the soil between rows of corn in a field in southwestern Quebec in May of 1999. Weed coverage was determined from each image using a greenness method in which the red, green, and blue intensities of each pixel were compared. Weed coverage and weed patchiness were estimated based on the percent of greenness area in the images. This information was used to create a weed map. Using weed coverage and weed patchiness as inputs, a fuzzy logic model was developed for use in determining site-specific herbicide application rates. A herbicide application map was then created for further evaluation of herbicide application strategy. Simulations indicated that significant amounts of herbicide could be saved using this approach.     

春草秋治对麦田杂草的防治效果

在河北省曲周县选择6个村庄的麦田进行春草秋治效果试验,不同村庄的小麦主栽品种不完全相同。采用对比试验设计,2013年11月中旬（小麦播种后1个月）利用自走式机械喷药机用苯磺隆150～180 g/hm^2对水450 kg/hm^2喷雾施药,以不进行任何处理的麦田作为对照。2014年3月对麦田杂草的发生种类和数量进行了调查。结果表明：播娘蒿为该地区麦田的主要杂草;春草秋治可以有效降低示范方杂草的发生种类、田间频率和田间密度,降低播娘蒿的相对密度,个别地块甚至出现杂草灭绝的效果。春草秋治技术具有较好的应用效果和推广前景。     

Broad-scale cruciferous weed patch classification in winter wheat using QuickBird imagery for in-season site-specific control

This article explores the potential use of multi-spectral high-spatial resolution QuickBird imagery to detect cruciferous weed patches in winter wheat fields. In the present study, research was conducted on six individual naturally infested fields (field-scale study: field area ranging between 3 and 52 ha) and on a QuickBird-segmented winter wheat image (broad-scale study: area covering approximately 263 winter wheat fields, approximately 2 656 ha) located in the province of Córdoba (southern Spain). To evaluate the feasibility of mapping cruciferous weed patches in both the field-scale and broad-scale studies, two supervised classification methods were used: the Maximum likelihood classifier (MLC) and vegetation indices. Then, the best classification methods were selected to develop in-season site-specific cruciferous weed patch treatment maps. The analysis showed that cruciferous weed patches were accurately discriminated in both field-scale and broad-scale scenarios. Thus, considering the broad-scale study, classification accuracies of 91.3 and 89.45 % were obtained using the MLC and blue/green (B/G) vegetation indices, respectively. The site-specific treatment maps obtained from the best classifiers indicated that there is a great potential for reducing herbicide use through in-season, cruciferous weed patch site-specific control on both a field-scale and broad-scale. For example, it can be determined that by applying site-specific treatment maps on a broad-scale, herbicide savings of 61.31 % for the no-treatment areas and 13.02 % for the low-dose herbicide areas were obtained.     

山东省冬小麦田杂草群落调查及其变化原因分析

【目的】过去10年,山东省冬小麦田杂草种类、数量和发生区域均发生了明显变化,明确山东省冬小麦田杂草群落演替规律,分析其演替原因,为制定小麦田杂草精准防控策略提供理论依据。【方法】在山东省冬小麦种植区域调查300个调查地,每个调查地选择3块区域,每块区域采用倒置“W”型9点取样法,从2009—2019年10年间分3次调查山东省冬小麦田杂草群落分布,明确山东省冬小麦田7大区域杂草群落组成,分析杂草群落变化规律。【结果】山东省冬小麦田杂草群落结构及其变化有如下特点：（1）播娘蒿、荠菜一直是山东省冬小麦田的优势杂草,3次调查中播娘蒿优势度始终排在第1位,相对优势度分别为20.68%、22.49%、22.24%,荠菜也始终排在前3位,相对优势度分别为15.49%、15.77%和14.51%。（2）优势杂草种类越来越多,2009—2010年度调查时,相对优势度≥10.00%的只有播娘蒿、荠菜两种,后两次调查时,则分别为3种（增加了雀麦）和5种（增加了雀麦、节节麦和猪殃殃）。（3）禾本科杂草分布区域和危害程度逐年加大。2009—2010年度恶性禾本科杂草雀麦和节节麦主要分布在西北平原区、北部滨海区、中部山区;2013—2014年度扩散蔓延至南部山区、胶潍河谷平原区;2018—2019年度时已遍及全省。且危害程度逐渐加大,3次调查中雀麦相对优势度分别为7.66%、16.39%、17.94%;节节麦分别为3.08%、7.61%、11.38%;多花黑麦草、大穗看麦娘和野燕麦虽然总优势度不高,但也在逐渐增大。（4）婆婆纳、猪殃殃等阔叶杂草分布越来越广。3次调查中猪殃殃优势度分别为8.29%、8.94%、10.00%,逐年上升,分布区域也逐渐扩大,在山东省各个区域均大面积分布,尤其在西南平洼区、南部山区和中部山区分布最多,在西北平原区分布面积也很广;婆婆纳优势度分别为1.08%、1.18%、2.05%,主要分布在西南平洼区和南部山区,在其他区域也已有分布。（5）山东省7大小麦种植区域杂草群落变化最大的是胶东丘陵区,物种多样性呈现不断上升趋势,2009—2010年度时,反映物种多样性的香农指数仅高于北部滨海区,列第6位;2013—2014年度,超过西北平原区和胶潍河谷平原区,列第4位;2018—2019年度,仅次于南部山区,列第2位。【结论】耕作制度的变化、恶性杂草的传播入侵以及单一除草剂大面积连续应用明显推动了山东省冬小麦田杂草群落的变化。因此,在山东省冬小麦田杂草防控中,应推广化学除草剂与农艺措施相结合、根据田间草相精准选择除草剂以及不同机理除草剂轮换使用等杂草综合防控策略。     

Patchy weed distribution and site-specific weed control in winter cereals

Site-specific weed control in winter cereals was performed on the same fields every year over a 5-year period (1999–2003). The most common weeds (Apera spica-venti, Galium aparine, Veronica hederifolia, Viola arvensis) were counted by species, at grid points which were georeferenced and the data were analysed spatially. For weed control, weeds were grouped into three classes: grass, broad-leaved weeds (without Galium aparine), and Galium aparine. Based on weed distribution maps generated by the spatial analyses, herbicide application maps were created and site-specific herbicide application was carried out for grouped and or single weed species. This resulted in a significant reduction in herbicide use. Averaging the results for all fields and years, the total field area treated with herbicides was 39% for grass weeds, 44% for broad-leaved weeds (without Galium aparine) and 49% for Galium aparine. Therefore, site-specific weed control has the potential to reduce herbicide use compared to broadcast application, thus giving environmental and economic benefits.     

An on-farm approach to quantify yield variation and to derive decision rules for site-specific weed management

Grain yield often varies within agricultural fields as a result of the variation in soil characteristics, competition from weeds, management practices and their causal interactions. To implement appropriate management decisions, yield variability needs to be explained and quantified. A new experimental design was established and tested in a field experiment to detect yield variation in relation to the variation in soil quality, the heterogeneity of weed distribution and weed control within a field. Weed seedling distribution and density, apparent soil electrical conductivity (EC_a) and grain yield were recorded and mapped in a 3.5 ha winter wheat field during 2005 and 2006. A linear mixed model with an anisotropic spatial correlation structure was used to estimate the effect of soil characteristics, weed competition and herbicide treatment on crop yield. The results showed that all properties had a strong effect on grain yield. By adding herbicide costs and current grain price into the model, thresholds of weed density were derived for site-specific weed control. This experimental approach enables the variation of yield within agricultural fields to be explained, and an understanding of the effects on yield of the factors that affect it and their causal interactions to be gained. The approach can be applied to improve decision algorithms for the patch spraying of weeds.     

冀东冬麦区雀麦的田间识别 发生规律及其化学防除技术的初步研究

通过田间观察对冀东冬麦区雀麦的形态特征进行了系统完整的描述,修正和完善了文献记载的不足,重点突出了直观性,使农民能够在麦田里容易地识别出雀麦。通过定期田间调查,明确了雀麦在冀东冬麦区的发生规律：在冀东冬麦区雀麦属越年生杂草,绝大部分在秋季出苗,占发生总量的97%以上;雀麦分蘖力强,单株平均分蘖达10.6个。同时进行了啶磺草胺7.5%WG 3个剂量处理（135、180、360 g/hm2）对雀麦的田间防除药效试验,结果表明：啶磺草胺7.5%WG是目前防除麦田雀麦的理想除草剂,春季在雀麦7叶期前用啶磺草胺7.5%WG 135～180 g/hm2＋专用助剂225 mL/hm2,对雀麦鲜重防效达97%以上,对混发的荠菜和播娘蒿也有较好的兼治效果,并且对小麦安全。     

节节麦在山东省冬小麦田的扩散蔓延及对甲基二磺隆抗性测定

【背景】节节麦（Aegilops tauschii）是小麦的野生近缘植物,是世界公认的十大恶性杂草之一,可安全有效防除节节麦的除草剂品种很少,目前只有ALS抑制剂类除草剂甲基二磺隆作为苗后茎叶处理剂能够应用,该药剂在小麦田应用多年,部分区域发现效果下降,这可能与抗性有关。【目的】明确山东省冬小麦田节节麦扩散蔓延规律以及对甲基二磺隆的抗性水平和抗性机理,为制定山东省冬小麦田节节麦精准区域防控策略提供理论依据。【方法】分别于2009—2010、2013—2014、2018—2019年3次田间调查节节麦在山东省冬小麦田的分布,分析其扩散蔓延规律,室内采用整株生物测定法测定62个节节麦种群对甲基二磺隆的抗性水平,对中等抗性种群进行靶标基因序列检测。【结果】节节麦在山东省冬小麦田10年间呈现快速增长趋势,分布区域逐渐扩大,相对优势度逐渐增大。2009—2010年度,节节麦主要分布在山东西北平原区、中部山区和北部滨海区,平均相对优势度为3.18,在所有杂草中位列第8位;2013—2014年度,节节麦已在山东西北平原区等5个区域广泛分布,平均相对优势度达到7.33,位列第5位;2018—2019年度,节节麦在山东省全境大面积发生,平均相对优势度为11.38,位列第4位。62个节节麦种群中有20个种群对甲基二磺隆产生一定程度的抗性,这些抗性种群分布在节节麦发生早且用药时间长的西北平原区、西南平洼区和中部山区,其他区域未见抗性种群。其中低抗、中抗种群分别为16个（相对抗性指数在5.00—10.00）、4个（相对抗性指数在10.00—15.00）,分别占种群总数的25.81%和6.45%,最高相对抗性指数达到12.63,无高抗种群。对4个中抗种群进行靶标位点突变测定,未检测到位点突变。【结论】节节麦已在山东省7大种植区域大面积分布,且分布区域和相对优势度逐年提高。未有对甲基二磺隆高抗的节节麦种群产生,但已有32.26%种群产生低等或中等程度的抗性,未检测到靶标位点突变,可能是代谢酶引起的非靶标抗性。生产中应避免过分依赖甲基二磺隆进行节节麦防控,建议推广深翻、土壤封闭和苗后茎叶处理相结合的节节麦综合防控策略,延缓节节麦抗性发展。     

Camera steered mechanical weed control in sugar beet,maize and soybean

In sugar beet, maize and soybean, weeds are usually controlled by herbicides uniformly applied across the whole field. Due to restrictions in herbicide use and negative side effects, mechanical weeding plays a major role in integrated weed management (IWM). In 2015 and 2016, eight field experiments were conducted to test the efficacy of an OEM Claas 3-D stereo camera^® in combination with an Einböck Row-Guard^® hoe for controlling weeds. Ducks-foot blades in the inter-row were combined with four different mechanical intra-row weeding elements in sugar beet, maize and soybean and a band sprayer in sugar beet. Average weed densities in the untreated control plots were from 12 to 153 plants m^?2 with Chenopodium album, Polygonum convolvulus, Thlapsi arvense being the most abundant weed species. Camera steered hoeing resulted in 78% weed control efficacy compared to 65% using machine hoeing with manual guidance. Mechanical intra-row elements controlled up to 79% of the weeds in the crop rows. Those elements did not cause significant crop damage except for the treatment with a rotary harrow in maize in 2016. Weed control efficacy was highest in the herbicide treatments with almost 100% followed by herbicide band-applications combined with inter-row hoeing. Mechanical weed control treatments increased white sugar yield by 39%, maize biomass yield by 43% and soybean grain yield by 58% compared to the untreated control in both years. However, yield increase was again higher with chemical weed control. In conclusion, camera guided weed hoeing has improved efficacy and selectivity of mechanical weed control in sugar beet, maize and soybean.     

Crop/Weed Outcomes from Site-Specific and Uniform Soil-Applied Herbicide Applications

While uniform broadcast application (BC) of soil-applied herbicides is the norm, advances in geospatial technologies have enabled the deployment of site-specific herbicide application (SS). Since there are several, largely-untested decision rules for SS herbicide use, the objective of this work was to evaluate crop/weed outcomes and isoxaflutole use for a number of BC and SS strategies. Field experiments were established where isoxaflutole dose response functions were quantified from early-season Zea mays (L.), Sorghum bicolor (L.) Moench., and Abutilon theophrasti Medic. response data at multiple plots (64 in 1999; 62 in 2000) throughout a variable field. These data were then used to infer crop and weed outcomes from simulated application strategies. While BC and SS strategies that relied on the product label were similar in terms of total herbicide use, extent of crop tolerance, and A. theophrasti efficacy, the SS strategy resulted in a significant redistribution of herbicide. Using biologically effective doses (ED) resulted in the highest efficacy and herbicide use was highly species-dependent. By using a historical weed map of the field to guide herbicide application, herbicide use could be reduced some 20–48% when following the product label where seedlings were present, or >90% when using the ED for A. theophrasti. In order to maximize the potential agronomic benefits of SS, biological and spatial information of both the weed and soil should be taken into account.An erratum to this article can be found at     

黄河三角洲地区除草剂对紫花苜蓿产量及杂草群落影响的初探

针对紫花苜蓿田杂草,选用咪唑乙烟酸、精喹禾灵、高效氟吡甲禾灵和乙氧氟草醚4种除草剂,研究了不同除草剂和浓度对苜蓿产量和杂草群落特征的影响。结果表明,喷施咪唑乙烟酸、高效氟吡甲禾灵均能提高苜蓿产量,咪唑乙烟酸2000mL·hm^-2、高效氟吡甲禾灵700mL·hm^-2增产效果最好,喷施乙氧氟草醚明显抑制苜蓿生长;咪唑乙烟酸、精喹禾灵、乙氧氟草醚能明显降低杂草种类。从物种重要值来看,马唐、马齿苋、稗草等属于较难防除杂草;喷施除草剂对杂草群落产生了影响,物种多样性指数随药剂浓度的增大均呈下降趋势。从试验结果综合判断,除草剂最佳选择为咪唑乙烟酸2000mL·hm^-2,其次为高效氟吡甲禾灵700mL·hm^-2。     

Machine vision smart sprayer for spot-application of agrochemical in wild blueberry fields

An essential part of the wild blueberry cropping system is the proper management of agrochemical inputs including herbicides, fungicides and insecticides. A machine vision system was developed and mounted on the rear sprayer boom 0.18 m in front of the sprayer nozzles capable of targeting the agrochemical application on an as-needed basis. The three-point hitch mounted sprayer featured 27 nozzles over a 13.7 m boom width and a storage tank capacity of 1135 l. Nine digital color cameras continually take images in real-time while computer software processes the images in 0.15 s to determine the target locations where the nozzles open and spray at speeds up to 1.77 m s^?1. Two wild blueberry fields in central Nova Scotia were selected for smart sprayer performance testing with spot-application (SA) of agrochemical as compared to control and uniform application techniques. Chateau^® herbicide was applied in a field with an infestation of hair cap moss. Spray droplet comparison showed moss patches were properly targeted using the smart sprayer. SA provided the same coverage performance as compared to uniform on the moss targets with herbicide application savings of 78.5% using the smart sprayer. Harvestable yield results were similar for all application tracks. TruPhos Magnesium and ZincMax foliar fertilizers were tank mixed with Bravo^® and Proline^® fungicides and applied to compare the difference of SA, control and uniform application. Results showed SA of foliar fertilizer and fungicide led to less premature leaf drop and increased the blueberry stem height, number of branches, stem diameter and fruit buds. SA of foliar fertilizer and fungicide also increased the percent of healthy wild blueberry plants by 57.8% and the harvestable yield by 137.8%. Fungicide application savings using the smart sprayer for SA were 11.6%.