75%噻吩磺隆水分散粒剂防除大豆田阔叶杂草效果研究

研究75%噻吩磺隆水分散粒剂对大豆田阔叶杂草的防治效果,结果表明:75%噻吩磺隆水分散粒剂能有效防除反枝苋、铁苋菜、茴麻、黎等大豆田阔叶杂草,对大豆安全,注意与防除禾本科杂草大豆田除草剂混用,以扩大杀草谱。     

菜用大豆地膜覆盖栽培试验

研究除草麻地膜、普通麻地膜、塑料地膜覆盖和露地栽培对菜用大豆田的除草效果与菜用大豆产量的影响,结果表明,杂草株防效以除草麻地膜覆盖的最高,为80.5%,塑料地膜覆盖的最低,为4.4%;鲜重防效以除草麻地膜、普通麻地膜覆盖的最高,为87.3%和87.6%,塑料地膜覆盖的最低,为53.7%;产量以普通麻地膜覆盖的最高,为13.83 t.hm-2,露地栽培最低,为10.40 t.hm-2;平均粒仁鲜重是塑料麻地膜覆盖的最大,为0.68 g。菜用大豆以覆盖普通麻地膜栽培较好。     

广东省烟田杂草的发生与分布现状调查

在烟草大田期,采用测量法和目测法对广东省5种土壤类型烟田杂草进行了调查,结果表明:广东省烟田杂草共计有29科82属105种,根据对每种杂草重要值的评价,最主要的杂草有15种,包括马唐、无芒稗、铁苋菜、丛枝蓼、狗尾草等;广东省5种土壤类型烟田在烟草大田期的主要杂草群落及其分布各有其特点,牛肝土田的主要杂草为丛枝蓼、铁苋菜、无芒稗和鳢肠,紫色土旱地的主要杂草为铁苋菜、狗尾草、香附子、苍耳和马唐,红火泥地的主要杂草为马唐、无芒稗、荩草和胜红蓟,石灰性土田的主要杂草为无芒稗、牛筋草、荩草和异型莎草,麻沙泥田的主要杂草为马唐、弯曲碎米荠、蚤缀、丛枝蓼和小藜.     

驻马店市芝麻田杂草发生特点及综合防治技术

通过近几年对驻马店市平舆、上蔡等几个高产示范县芝麻田间的杂草种类调查，发现田间发生量比较大的有马唐、牛筋草、稗草、千金子、野燕麦、茼麻、田旋花、狗尾草等杂草，针对这些杂草的发生规律提出以植物检疫为前提，因地制宜地采用农业、地膜、化学等多种措施来进行综合防治。     

玉米田杂草防治技术

玉米是河南省重要的粮食作物之一,玉米田的主要杂草种类有田旋花、香附子、马齿苋、黎、牛筋草、马唐、狗尾草、画眉草、铁苋、泽漆、茼麻等,草害面积达80％以上。其中。中等以上危害面积达55％-66名,玉米苗期受杂草的危害最重。所以,玉米田杂草的化学防治应抓好播后苗前和苗后早期两个关键时期,及时进行化学除草。     

珲春市玉米田杂草种类及主要化学除草技术

根据农业部《主要农作物有害生物种类与发生危害特点研究》公益性项目实施的总体要求,作为项目县市,2009年~2011年连续三年,采取双对角线五点取样法,对我市玉米田杂草发生情况进行调查。调查表明,我市玉米田杂草种类有23个科、54种。不好防治的杂草有狗牙根、问荆、鸭趾草、芦苇、茼麻5种。此文简单阐述了我市玉米田主要的化学除草技术。     

玉米田杂草防治技术

玉米是河南省重要的粮食作物之一,玉米田的主要杂草种类有田旋花、香附子、马齿苋、黎、牛筋草、马居、狗尾草、画眉草、铁苋、泽漆、茼麻等,草害面积达80%以上.其中,中等以上危害面积达55%～66%,玉米苗期受杂草的危害最重.所以,玉米田杂草的化学防治应抓好播后苗前和苗后早期两个关键时期,及时进行化学除草.     

夏季大豆花生田科学除草技术

夏大豆、花生通常在6月份播种。正处于高温多雨的季节。杂草发生来势猛、密度高、长势强、种类多。铲除不及时、彻底,很容易形成草荒,真是“草长豆苗稀”。严重影响花生、大豆的生长,造成减产。大豆花生田主要单子叶有马唐、牛筋草、藜、狗尾草;阔叶杂草有反枝苋、鳢肠、铁苋、茼麻。杂草一般在大豆播种后5天开始出土,整个杂草出土期持续长达60天左右,对大豆高产极为不利。而化学除草却可很轻松地防除田间杂草,尤其在连阴雨天效果更明显。     

介绍三种豆类除草剂

正1.欢乐豆产品名称:15%精喹·氟磺胺乳油+助剂适用作物:春大豆、花生、杂豆防除对象:稗草、狗尾草、马唐、牛筋草、狗牙根、野燕麦、野黍、千金子、蓼、马齿苋、苋菜、龙葵、荠菜、苍耳、茼麻、鸭跖草、藜、问荆草、刺儿菜、苣荬菜、蒿草等禾本科杂草和阔叶杂草。性能特点:为特效苗后除草剂,对     

浅析影响玉米田化学除草效果的因素

玉米杂草种类繁多,主要危害玉米的杂草有:藜、蓼、苋、稗、马唐、狗尾草、茼麻、猪毛菜、田旋菜、苦苣菜、苍耳、马齿苋、铁苋菜、香薷、刺儿菜、车前草等.由于玉米田中禾本科杂草和阔叶杂草大部分混生,而且混生情况不一,因此必须因地制宜,正确选择广谱性除草剂或几种除草剂混合使用与分期搭配使用.近年来,虽然玉米化学除草技术得到了广泛应用,但农民在应用过程中受到了很多因素干扰,降低了防治效果.     

Modelling Wild-Oat Density in Terms of Soil Factors: A Machine Learning Approach

In crop fields, weed density varies spatially in non-random patterns. Initial knowledge of weed distribution would greatly improve weed management for Precision Agriculture operations. Site properties could be correlated to weed distribution, since the former vary among crop fields and also certain factors such as soil texture or nitrogen may condition the weed growth. This paper presents a method, based on artificial intelligence techniques, for inducing a model that appropriately predicts the heterogeneous distribution of wild-oat (Avena sterilis L.) in terms of some environmental variables. From several experiments, distinct rule sets have been found by applying a genetic algorithm to carry out the automatic learning process. The best rule set extracted was able to explain about 88% of weed variability.     

广东农田杂草防控的问题与对策

广东光温水热资源丰富，作物四季种植，杂草周年为害，已成为影响农作物生产的重要生物因子。目前，广东农田杂草防控主要依赖化学除草剂，在控制农田杂草危害和提高作物产量方面发挥了重要作用。但随着农业现代化进程的推进，杂草防控面临诸多挑战：化学除草剂的过量使用，导致杂草种群演替及抗药性问题突出，除草剂药害问题频发，防治成本增加的同时给农田生态环境带来巨大的压力；绿色防控技术储备不足，适应杂草防控的智能化和机械化手段不多，人才队伍总量不足等。针对上述问题，提出了以下相应对策：推进杂草群落动态和抗性监测预警工作；加强杂草抗性机理研究；研发推广除草剂药害诊断及防控技术；加强杂草绿色防控技术和精准除草技术研究；组建产学研联盟，增强协同创新能力；推进杂草统防统治及基层从业者培训。     

Weed Detection Using Canopy Reflection

For site-specific application of herbicides, automatic detection and evaluation of weeds is desirable. Since reflectance of crop, weeds and soil differs in the visual and near infrared wavelengths, there is potential for using reflection measurements at different wavelengths to distinguish between them. Reflectance spectra of crop and weed canopies were used to evaluate the possibilities of weed detection with reflection measurements in laboratory circumstances. Sugarbeet and maize and 7 weed species were included in the measurements. Classification into crop and weeds was possible in laboratory tests, using a limited number of wavelength band ratios. Crop and weed spectra could be separated with more than 97% correct classification. Field measurements of crop and weed reflection were conducted for testing spectral weed detection. Canopy reflection was measured with a line spectrograph in the wavelength range from 480 to 820 nm (visual to near infrared) with ambient light. The discriminant model uses a limited number of narrow wavelength bands. Over 90% of crop and weed spectra can be identified correctly, when the discriminant model is specific to the prevailing light conditions.     

The influence of selected agronomic factors on the chemical composition of spelt wheat(Triticum aestivum ssp. spelta L.) grain

The increase of spelt crop area is a result of overproduction of the basic cereals and the introduction of environmentally-friendly cultivation methods.Due to high interest in healthy lifestyle,healthy food and intensive development of organic agriculture,it was necessary to thoroughly examine the newly-formed cereal strains in order to register the best ones as varieties in the future.The experimental factors included:two weed control methods(mechanical and chemical),two sizes of sowing rate(300 and 500 seeds m~(-2)) and the strains of spelt:three new breeding strains(STH 28-4609,STH 28-4614,STH 28-4619) and Oberkulmer Rotkorn cultivar.The research did not show protein diversity depending on a genotype,mean protein content reached 13%in grain dry mass.The plants weeded mechanically showed the significantly highest crude fat content(2%dry matter(DM)).Mean value of crude fibre for all plants equalled 3.3%DM.The increase of neutral detergent fibre,acid detergent fibre and acid detergent lignin fractions was directly proportional to the increase in crude fibre content,which is beneficial for civilisation diseases prophylaxis.The studied agronomic factors did not significantly influence the essential amino acids content or total amino acids.The harrowed plants had grain with significantly increased nutrient content(crude protein,ether extract,crude fibre,acid detergent fibre(ADF),cellulose,sulphur amino acids,leucine,and sum of essential amino acids) which is very important for organic farming.     

Automated Crop and Weed Monitoring in Widely Spaced Cereals

An approach is described for automatic assessment of crop and weed area in images of widely spaced (0.25 m) cereal crops, captured from a tractor mounted camera. A form of vegetative index, which is invariant over the range of natural daylight illumination, was computed from the red, green and blue channels of a conventional CCD camera. The transformed image can be segmented into soil and vegetative components using a single fixed threshold. A previously reported algorithm was applied to robustly locate the crop rows. Assessment zones were automatically positioned; for crop growth directly over the crop rows, and for weed growth between the rows. The proportion of crop and weed pixels counted was compared with a manual assessment of area density on the basis of high resolution plan view photographs of the same area; this was performed for views with a range of crop and weed levels. The correlation of the manual and automatic measures was examined, and used to obtain a calibration for the automatic approach. The results of mapping of a small field, at two times, are presented. The results of the automated mapping appear to be consistent with manual assessment.     

硬茬复播玉米和大豆田主要杂草及化学防除技术研究

硬茬复播田杂草种类达15科27种。采用除草剂JNH－1,JNH－2或JNH－3进行苗前土壤处理,对已出苗和未出苗的杂草皆有极显著防效,一次用药不仅可保证作物苗期免遭草害,而且对作物生育后期的杂草也可达到有效控制。所用除草剂均对玉米、大豆安全。由于有效减轻了草害和虫害,大豆平均增产19．4％,玉米平均增产26．2％。     

除草剂土壤处理对谷子生物学特性的影响

试验采用随机区组设计,研究了扑草净、乙草胺、速收、赛克等除草剂在大田条件下对谷子安全性的影响。本文探讨了各除草剂对谷子株高、叶面积、地上部鲜重等形态指标和叶绿素相对含量、硝酸还原酶活性、过氧化物酶活性、可溶性糖含量等生理指标的相关影响。结果表明：土壤处理中,乙草胺100ml＋赛克50g／667m。对谷子的生长无显著影响,且对谷子田杂草有良好的防除效果。如果施用其它除草剂,对谷子的生长发育不安全,有的表现为株高受到抑制,有的表现为细胞膜透性增大,有的表现为叶片失绿,鲜重降低,最终导致植株死亡,还有的表现为产量下降。随着除草剂的研究开发,除草剂混用或除草剂加油类助剂的施药方式,是杂草综合治理中的重要措施。通过除草剂的混用可以扩大杀草谱、提高除草效果、降低药害、减少残留活性、延缓除草剂抗药性的发生和发展,是提高除草剂应用水平的除草重要方式。     

Image Processing Performance Assessment Using Crop Weed Competition Models

Precision treatment of both crops and weeds requires the accurate identification of both types of plant. However both identification and treatment methods are subject to error and it is important to understand how misclassification errors affect crop yield. This paper describes the use of a conductance growth model to quantify the effect of misclassification errors caused by an image analysis system.Colour, morphology and knowledge about planting patterns have been combined, in an image analysis algorithm, to distinguish crop plants from weeds. As the crop growth stage advances, the algorithm is forced to trade improved crop recognition for reduced weed classification. Depending on the chosen method of weed removal, misclassification may result in inadvertent damage to the crop or even complete removal of crop plants and subsequent loss of yield. However incomplete removal of weeds might result in competition and subsequent yield reduction. The plant competition model allows prediction of final crop yield after weed or crop removal. The competition model also allows the investigation of the impact on yield of misclassification in the presence of both aggressive and benign weed types. The competition model and the image analysis algorithm have been linked successfully to investigate a range of misclassification scenarios in scenes containing cabbage plants.     

江苏省长江以北地区麦田杂草群落的定量分析

用 7级目测法调查江苏省长江以北地区 6 9个样点的 6 38块麦田共计约 5 4 5hm2 的草害情况 ,数据转化成综合值后 ,进行主成分分析 ,并赋予生态学意义上的解释。研究结果表明 ,决定江苏长江以北地区麦田杂草发生、分布和危害的主要因素是土壤水分、土壤性质 地带性气候因素 ;主成分分析结果表明 ,生境相似 ,杂草群落有趋同性 ;可将 6 9个样点划分为 3个聚类群 ,即沿海旱茬麦类群、内陆旱茬麦类群和稻茬麦类群 ,各聚类群均有相应的优势杂草 ,粘毛卷耳、波斯婆婆纳、刺儿菜、猪殃殃等为沿海旱茬麦田优势杂草 ,内陆旱茬麦田的主要杂草是播娘蒿和麦家公 ,稻茬麦田的杂草优势种为硬草、棒头草 ,并就该地区杂草发生的特点提出了综合治理的建议     

抗药性杂草种群的发展及其防治对策

叙述了全球抗药性杂草种群的分布及其发展动态,杂草抗药性的原因和抗性杂草种群对作物的危害,提出了以作物轮作,栽培,来茬等农业措施为主,结合生态防治,生物防治和合理使用除草剂来治理抗性杂草,延缓杂草产生抗性的综合防治对策。