杂草密度与作物产量损失的预测模型

通过对国内外多个用于杂草密度和作物产量损失关系的经验模型比较分析，并对１０组不同来源的杂草与作物竞争资料进行模拟，证明模型Ｙ_Ｌ＝ｄ／（ａ＋ｂｄ）具有实际的生物学意义，能确地描述多种杂草和多种作物间的竞争关系，预测杂草竞争对作物可能造成的危害和损失。     

确定杂草防治期的新方法（一）

本文综合杂草生物学,作物与杂草的竞争及经济学三方面的知识,提出了一种确定杂草防治最佳时期的方法本方法的依据是时间密度相当量（ＴＤＥ）概念,指出与作物同时萌发生与作物竞争至收获期的杂草密度,该密度下与给定萌发时间,消亡时间和种群密度的杂草引起相同的产量损失,由于处理前后均有杂草萌发,发展了一种考虑杂草萌发的模式,以最小的经济损失决定杂草防治时间的模型,以两个例子表述模拟结果,玉米与苘麻（Ａｂｕｔｉｌ     

数学模型在杂草科学中的应用

早在1965年,荷兰人deWit就提出了一个杂草与作物竞争的数学模型,其研究竞争关系的"置换试验法"至今仍被杂草科学工作者所采用。近年来,国际上数学模型在杂草科学研究中的应用已极其普遍。运用数学模型的方法,可以定量地来分析杂草的发生、生长、分布,及其对作物产量的损失,并在此基础上,对现有的杂草防除技术进行综合评价和筛选,以求最终提出既能满足经济利益。又能满足生态效益的杂草综合管理体系。本文旨在对此方面的工作作一概述,以供杂草科学工作者参考。一、杂草种群动态模型和空间分布规律杂草种群不仅会受到自然环境条件的…     

龙葵和苘麻发生数量与大豆产量的关系

龙葵和苘麻发生数量与大豆产量的关系王义明（黑龙江省农科院植保所哈尔滨１５００８６）作物因杂草的危害而减产。但杂草发生数量不同，作物产量损失的程度也不同。龙葵（Ｓｏｌａｎｕｍｎｉｇｒｕｍ）植株繁茂多枝，菏麻（Ａｂｕｔｉｌｏｎｔｈｅｏｐｈｒａｓｉｔ）植株...     

作物害虫损失估计

探明造成作物损失的原因,是建立确保子孙后代吃穿战略思想的基础。象昆虫、杂草、植物的病害、线虫、啮齿类动物及某些鸟类等有害生物,是生物因素引起绝大部份作物损失的重要原因。这些有害生物在作物产前为害一般可使作物的潜在产量损失30％以上。在美国,有害生物至少包括160种细菌、250种病毒、800种真菌、2000种杂草以     

作物中杂草防除的经济问题

世界人口的近期增长及其对自然资源产生的压力,目前正影响着杂草防除的经济状况,对将来也将产生深远的影响。杂草在作物中造成的各种损失由于杂草的存在而造成的作物损失是严重的,虽然其损害不象其它害物所造成的损失那样一目了然。这些损失发生在作物生长周期的各个阶段。杂草①使作物减产;②影响作物质     

玉米田全程化学除草技术

宜都市现有玉米种植面积12千hm~2,是主要的饲用作物,每年因杂草危害给玉米产量造成了很大损失。本文摘要简述了几类玉米除草剂的特性及应用,玉米各个生育时期的用药选择、药剂用量、施用方法、注意事项以及对后茬作物的影响,以期能有效地防除玉米田杂草,减少除草剂在土壤中的残留,最大限度减少玉米产量的损失。     

近年我国农田杂草防控中的突出问题与治理对策

我国田园杂草有1 400多种,严重危害的130余种,恶性杂草37种。我国杂草发生面积约9 246.7万hm2次,防治面积1.04亿hm2次,挽回粮食损失2 699万t,每年主粮作物仍有近300万t产量损失。杂草防控中的突出问题是:杂草群落演替,难治杂草种群增加;除草剂单一使用,杂草抗药性发展迅速;除草剂对作物药害频发,影响种植结构调整;新除草剂创制能力不足,难以满足不同作物田除草需求;农村劳动力短缺,杂草防控更依赖于化学防治。解决上述问题,应实施以下对策:加强杂草发生危害的监测预警,科学轮换使用除草剂,推广除草剂减量与替代技术,加快新除草剂研制及推广应用,加速耐除草剂作物商业化进程,推进统防统治及农民培训。     

杂草对农牧业生产的影响及其种子的检疫检验和鉴定方法

杂草与农牧业生产密切相关,有着直接的和间接的影响。世界各国每年由于杂草而造成的损失是巨大的,防除费用也相当大。由于杂草的竞争,使得作物产量显著降低,世界曾统计过,在热带和亚热带地区产量减少达50%之多,温带地区达20%。就粮食总产量损失来看,曾已估计,生产潜力大,发展中国家粮食损失达25%,而在这些国家中农业技术水平较高的国家粮食损失达10%,已发达的国家是5%,如按总平均数11.5%来计算,每年粮食损失达287.5百万公吨。     

湖北省小麦田杂草种类调查初报

小麦是湖北省最主要作物之一,每年种植面积在66.67万hm2以上,而杂草危害对小麦生产所造成的损失非常严重,据统计,杂草危害使小麦减产达10%~20%,严重的可达30%以上。因此,对我省小麦田杂草的种类、地区分布进行调查研究,对于开展杂草防除,减少草害损失,提高我省小麦产量和品质,具有重要意义。为此,我们于2007年4月对湖北省小麦田杂草发生情况做了大面积调查,现将调查结果报告如下。1材料与方法1.1调查范围调查范围涉及湖北省主要小麦种植区域,包括鄂北岗地、江汉平原以及鄂东地区,调查点遍布以上地区的21个县、市。1.2调查方法调查方法参照强…     

Predicting the competitive effects of weed and crop density on weed biomass, weed seed production and crop yield in wheat

Competition between winter-sown wheat and Viola arvensis Murray or Papaver rhoeas L. was studied in two experiments in two successive years. The effects of varying crop and weed density were modelled in terms of weed biomass over time, weed seed production and crop yield. Biomass model parameters, representing maximum weed biomass and intra- and interspecific competition, were obtained for different assessment dates, enabling biomass levels to be predicted during the two growing seasons. Weed biomass declined, and its maximum level was reached earlier, with increasing crop density. Intraspecific competition was higher in the absence than in the presence of crop, increasing with time and with weed density. Halving the wheat population increased June biomass of V. arvensis by 74% and of P. rhoeas by 63%. Crop yield losses with increasing weed density were greater with low than with medium and high crop populations. P. rhoeas was significantly more competitive than V. arvensis in both years. Weed biomass in 1989 responded more to reductions in crop density following the milder winter of 1988/89 than in the previous year; however crop yields were less affected in 1989 due to summer drought, restricting late weed growth and competition. Weed seed production was related to weed biomass; the progressive lowering of crop density increased seed production, and both species were very prolific in the absence of crop. By combining models, seed production could be derived for a given competitive effect on the crop. Threshold weed populations, based on low weed levels that are not economic to control, could then be equated with the accompanying weed seed production.     

Modelling herbicide dose and weed density effects on crop:weed competition

The effects of a range of herbicide doses on crop:weed competition were investigated by measuring crop yield and weed seed production. Weed competitivity of wheat was greater in cv. Spark than in cv. Avalon, and decreased with increasing herbicide dose, being well described by the standard dose–response curve. A combined model was then developed by incorporating the standard dose–response curve into the rectangular hyperbola competition model to describe the effects of plant density of a model weed, Brassica napus L., and a herbicide, metsulfuron‐methyl, on crop yield and weed seed production. The model developed in this study was used to describe crop yield and weed seed production, and to estimate the herbicide dose required to restrict crop yield loss caused by weeds and weed seed production to an acceptable level. At the acceptable yield loss of 5% and the weed density of 200 B. napus plants m^–2, the model recommends 0.9 g a.i. metsulfuron‐methyl ha^–1 in Avalon and 2.0 g a.i. in Spark.     

Modelling the effect of crop and weed on herbicide efficacy in wheat

Recommended field application rates of herbicides have to give effective weed control in every situation and are, thus, often higher than that required for specific fields. An understanding of the interaction between crop:weed competition and herbicide dose may, in many cases, allow herbicide application rates to be reduced, important both environmentally and economically. We have developed a model of the interaction between crop:weed competition and herbicide dose, using an empirical model of the relationship between crop yield and weed biomass (related to weed density), and an empirical model of the relationship between weed biomass and herbicide dose. The combined model predicts crop yield, given herbicide dose and weed biomass at an interim assessment date. These crop yield loss predictions may be used to quantify the herbicide dose required to restrict yield loss to a given percentage. Parameters of the model were estimated and the model tested, using results from experiments, which used cultivated oats ( Avena sativa ) or oilseed rape ( Brassica napus ) as model weeds in a crop of winter wheat ( Triticum aestivum ).For the crop:weed:herbicide combinations investigated there was little increase in crop yield for herbicide dose rates above 20% of recommended field rates, in broad agreement with the model predictions. There may still be potential for further reduction below this level on economic grounds; the model could be used to estimate the `break-even' herbicide dose.     

Modelling the effects of weeds on crop production

In most quantitative studies on interplant competition, static regression models are used to describe experimental data. However, the generality of these models is limited. More mechanistic models for interplant competition, which simulate growth and production of species in mixtures on the basis of the underlying physiological processes, have been developed in the past decade. Recently, simulation models for competition between species for light and water were improved and a detailed version was developed for sugarbeet and fat hen (Chenopodium album L.). The model was validated with data sets of five field experiments, in which the effect of fat hen on sugarbeet production was analysed. About 98% of the variation in yield loss between the experiments (which ranged from –6 to 96%) could be explained with the model. Further analysis with the model showed that the period between crop and weed emergence was the main factor causing differences in yield loss between the experiments. Sensitivity analysis showed a strong interaction between the effect of the variables weed density and the period between crop and weed emergence on yield reduction. Different quantitative approaches to crop-weed competition are discussed in view of their practical applicability. Simulations of experiments, where both the weed density and the period between crop and weed emergence were varied over a wide range, showed a close relation between relative leaf cover of the weeds shortly after crop emergence and yield loss. This relation indicates that relative leaf cover of the weeds accounts for both the effect of weed density and the period between crop and weed emergence. This relation has the potential to be developed into a powerful tool for weed-control advisory systems.     

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.     

Impact of Indian mustard growth and incorporation on annual weed population dynamics and communities

Biofumigation from Brassica cover crops may be used to control soilborne pests and weeds. A study was conducted to understand the influence of biofumigation on key processes of annual weed population dynamics. Five combinations of Indian mustard (M) and oat (O) cover crop treatments were assessed in a 3 year field study at two locations in Québec, Canada. Treatments included four spring/fall cover crop combinations (M/M, M/O, O/M, O/O) and a weedy check control with no cover crop. Prior to mowing and incorporation of cover crops, weed identification, count and biomass measurements were recorded to evaluate the total weed density, to calculate the relative neighbour effect (RNE) and weed diversity metrics and to perform principal co‐ordinates analyses. Indian mustard cover crops had no impact on weed establishment in 2014 due to low biofumigant potential compared to the oat cover crop. In 2015 and 2016, Indian mustard isothiocyanate (ITC) production increased and weed establishment within the Indian mustard cover crop decreased. Moreover, post‐cover crop incorporation decreased the next year spring weed emergence. Allelopathic interference of Indian mustard was significant when plant tissues produced more than 600 μg of allyl‐ITC g^?1. It is now possible to rationalise the use of Brassica cover crops and biofumigation for weed control with an enhanced understanding of the impact of biofumigation on key processes of weed population dynamics.     

Critical periods of weed competition in cotton in Greece

Four experiments were conducted in central Greece during 1997 and 1998 to determine the late-season presence of weeds in cotton (Gossypium hirsutum L.) and the critical times for removing weeds. Experiments were conducted in natural, heavily infested cropland. The presence of weeds for more than 3 weeks after crop emergence caused significant reductions in crop growth and lint yields. However, weeds that emerged 11 weeks or more after crop emergence did not adversely impact yields. Total weed biomass increased with increasing time prior to weed removal. A weed-free period of 11 weeks after crop emergence was needed to prevent significant reductions in cotton height, biomass, number of squares, and yield. These results indicated that postemergence herbicides or other control measures should be initiated within 2 weeks after crop emergence to avoid significant yield reduction. For greater efficiency, soil-applied herbicides in cotton should provide effective weed control for at least 11 weeks. Curvilinear regression equations were derived to describe the relationship between critical periods of weed presence and cotton growth and fruit development.     

Weed population dynamics during the groundnut crop cycle in the wet tropical zone of Kombe (Congo)

Weed competition in crops constitutes the main limiting factor for groundnut crop yields in the Congolese humid zone. In order to control the problems related to weed interference in the crop, the most appropriate weeding period for good production has been investigated. The critical period of weed interference has been determined from a groundnut crop experiment weeded at different times during two crop cycles. The data obtained allowed the authors to propose a suitable weeding regime that would reduce the costs and frequencies of weeding and enable local farmers to plan their work more effectively.     

Competition between annual weeds and vining peas grown at a range of population densities: effects on the weeds

Linear regression of dry weight of weeds against crop density, together with the use of diversity indices and principal component analysis were used to derive information about changes in the behaviour of annual weeds over the growing season and in response to a wide range of crop densities in vining peas Pisum sativum L. Using linear regression it was possible to quantify reductions in weed dry weights per unit increase in crop plant density The ‘weed losse’ factor was acceptably consistent between experiments. Indices examining richness and evenness showed that numbers of weed species declined with increasing crop density and as the season progressed, but although species evenness became less at successive sampling dates the presence of a pea crop, whatever its density, did not radically alter the composition of the weed flora. Principal component analysis demonstrated that although there was competition within the weed flora, the crop did not replace the dominant weed species on high density plots, but reduced growth of all weed species alike.