Effects of Transgenic Bt+CpTI Cotton on Field Abundance of Non-Target Pests and Predators in Xinjiang, China

Transgenic insect-resistant cotton is being increasingly planted in Xinjiang cotton-planting regions, where geographical climate conditions and species composition of pests and natural enemies are greatly unique in China. Limited studies have been conducted on the ecological impacts of transgenic insect-resistant cotton, especially for transgenic double genes （Bt＋CpTI） cotton, in this region. In this study, the potential effects of transgenic Bt＋CpTI cotton on the seasonal abundance of non-target pests and predators were assessed from 2009 to 2011 in Korla, Xinjiang. The results showed that species composition and seasonal abundance of 5 groups of pests and 5 groups of predators were not significantly different between transgenic Bt＋CpTI cotton and non-transgenic cotton every year. It suggests that transgenic Bt＋CpTI cotton per se does not affect the population dynamics of non-target pests and predators on this crop in Xinjiang.

An Intelligence Decision Support System for Diagnosis and Management of Grain and Cotton Crop Pests in Xinjiang

Xinjiang Uygur Autonomous Region is a scarcely populated area in China and technicians for plant protection are extremely deficient.The occurrence areas of insect pests in grain and cotton crops have been increasing year by year, causing serious economic losses. Aiming for several main grain and economic crops of Xinjiang(cotton, corn and wheat), an intelligence decision support system for diagnosis and management of grain and cotton crop pests in Xinjiang was designed and developed, which was based on android platform and windows system architecture. APP application program of smart phones was used as an implementation form. The intelligence decision support system will help plant protection personnel and farmers to solve local pest recognition and prevention control problem at the grassroots level in Xinjiang remote regions.

Analysis and Study on Characteristics and Detection Methods of Cotton Diseases and Insect Pests

[Objectives]The paper was to find the diseases and insect pests in the process of cotton growth quickly,effectively and timely.[Methods]The growth process of cotton was dynamically monitored by UAV aerial photography,and the aerial data map was converted into geotif image with longitude and latitude and then inputted into the detection system for preprocessing,mainly for image feature extraction and classification.Through deep learning of MATLAB software and BP neural network algorithm,the feature similarity of the images in the established characteristic database of cotton diseases and insect pests was compared.[Results]Through comparative analysis of characteristics of a large number of diseases and insect pests,it was found that deep learning method had high discrimination accuracy and good reliability.[Conclusions]The dynamic detection system using deep learning can well find cotton diseases and insect pests,and achieve early detection and early treatment,so as to effectively improve the yield and quality of cotton.

基于改进YOLOv7的棉田虫害检测

棉田虫害的快速检测与准确识别是预防棉田虫害、提高棉花品质的重要前提。针对真实棉田环境下昆虫相似度高、背景干扰严重的问题,该研究提出一种ECSF-YOLOv7棉田虫害检测模型。首先,采用EfficientFormerV2作为特征提取网络,以加强网络的特征提取能力并减少模型参数量;同时,将卷积注意力模块(convolution block attention module,CBAM)嵌入到模型的主干输出端,以增强模型对小目标的特征提取能力并削弱背景干扰;其次,使用GSConv卷积搭建Slim-Neck颈部网络结构,在减少模型参数量的同时保持模型的识别精度;最后,采用Focal-EIOU(focal and efficient IOU loss,Focal-EIOU)作为边界框回归损失函数,加速网络收敛并提高模型的检测准确率。结果表明,改进的ECSF-YOLOv7模型在棉田虫害测试集上的平均精度均值(mean average precision,mAP)为95.71%,检测速度为69.47帧/s。与主流的目标检测模型YOLOv7、SSD、YOLOv5l和YOLOX-m相比,ECSF-YOLOv7模型的mAP分别高出1.43、9.08、1.94、1.52个百分点,并且改进模型具有参数量更小、检测速度更快的优势,可为棉田虫害快速准确检测提供技术支持。

棉铃虫发生发展与气候条件的关系研究进展

棉铃虫(Helicoverpa armigera)属鳞翅目夜蛾科,是一种世界性的害虫,在世界各地均有分布。因其具有远距离迁飞,繁殖力强等特点,条件适宜时常大面积暴发成灾,给农业生产带来较大损失。摸清棉铃虫生活习性、种群变化规律是棉铃虫防治的前提条件。由于棉铃虫是变温昆虫,气候条件对其生长发育、成灾机制等产生极大影响。因此,本文系统综述了气候变暖对棉铃虫影响的研究进展,包括棉铃虫生长发育、体色变化、繁殖、滞育、飞行、越冬、与作物的互作关系等方面,并对未来研究重点进行了展望。

新疆棉花病虫害防治药剂剂型研发策略

棉花是我国重要的经济作物,也是受病虫害危害最严重的农作物之一。目前化学防治仍是棉田病虫害防治的重要技术。新疆棉区是我国最大的棉花主产区,气候类型属于典型的温带大陆性气候,具有光照充足、夏季高温干旱、多风、昼夜温差大等特殊气候特点,农药药液喷施过程中容易发生蒸发、飘移、降解等损失,严重影响药剂的防治效果。本文综述了温湿度、风、光照等环境因子对药剂防治效果的影响,以及国内外对提升药剂防治效果采取的调控措施,并结合新疆棉田的特殊气候条件提出了剂型研发的新策略。在提升产品理化稳定性的前提下,还需综合考虑有效成分的理化性质、棉花叶片的结构及润湿特性、施药器械等多种因素。结合农药学、植物保护学、界面化学、有机化学等多学科交叉理论知识指导,利用先进的技术和载体材料研发环境响应型、靶向高效的农药剂型,结合配套使用技术及措施,探索农药高效利用及减量调控途径,为实现农药减量增效、引领棉花产业绿色发展提供科技支撑。

基于RoBERTa多特征融合的棉花病虫害命名实体识别

针对棉花病虫害文本语料数据匮乏且缺少中文命名实体识别语料库,棉花病虫害实体内容复杂、类型多样且分布不均等问题,构建了包含11种类别的棉花病虫害中文实体识别语料库CDIPNER,提出了一种基于RoBERTa多特征融合的命名实体识别模型。该模型采用掩码学习能力更强的RoBERTa预训练模型进行字符级嵌入向量转换,通过BiLSTM和IDCNN模型联合抽取特征向量,分别捕捉文本的时序和空间特征,使用多头自注意力机制将抽取的特征向量进行融合,最后利用CRF算法生成预测序列。结果表明,该模型对于棉花病虫害文本中命名实体的识别精确率为96.60%,召回率为95.76%,F1值为96.18%;在ResumeNER等公开数据集上也有较好的效果。表明该模型能有效地识别棉花病虫害命名实体且具有一定的泛化能力。

棉花病虫害遥感监测研究进展

病虫害严重威胁棉花的产量与质量,阻碍棉花产业的发展,传统人工田间调查病虫害发生状况的方法难以满足大范围病虫害监测预报的需求。遥感监测技术可以无损获取棉花表型信息,能快速、大面积解译病虫害发生程度及空间分布信息,已发展成为棉花病虫害监测的重要途径。本文阐述了棉花病虫害近地、低空、卫星遥感监测的研究进展,总结了现有发展面临的问题,并对未来的研究方向和应用前景进行了展望,以期为棉花病虫害遥感监测研究提供指导和建议。

基于ERNIE及改进DPCNN的棉花病虫害问句意图识别

针对目前没有公开的棉花病虫害相关问句数据集且问句较短、类型多样等问题,本研究通过查阅文献及咨询相关领域专家,构建了棉花病虫害问句数据集CQCls,定义了78种棉花病虫害实体和9种问句类型;同时提出了一种基于ERNIE预训练模型的棉花病虫害问句意图识别模型,首先通过ERNIE模型将输入问句映射到向量空间,使用融合词位置信息的DPCNN模型进行特征向量的抽取,与基础的DPCNN模型相比,通过融合词位置信息能有效提高模型的表达能力,然后经过Softmax得到最终结果。实验结果表明,本研究提出的意图识别模型相较于其他模型取得了较好的结果,宏平均和加权平均的F1分数值分别为97.45%和97.31%;在文本语料数据内容复杂多样且文本格式不规范的DMSCD数据集上,训练结果中不同类别的F1分数的权重平均也能达到73.42%,进一步证明了该模型的有效性及泛化能力。

Predatory Efficacy of Cotton Inhabiting Spiders on Bemisiatabaci, Amrascadevastans Thripstabaci and Helicoverpa armigera in Laboratory Conditions

Distinction of predator＇s diet and prey choice preference is a hot topic of current investigations. Spider being generalist predator and cosmopoliter in nature acts as biological control agent in many agro-ecosystems. In the current study, predatory efficacy of five spiders （Pardosa birmanica, Cyclosa insulana, Thomisus projectus, Plexippus paykulli and Lycosa terrestris） inhabiting the cotton fieldevaluated in the laboratory conditions maintained at （27＋2）℃ temperature, 65%-5% relative humidity and 12 ： 12 h of light and dark photoperiod. Four key cotton pests＇ viz. Bemisiatabaci, Amrascaderastans Thripstabaci and Helicoverpa armigera were utilized in the choice and no-choice predatory studies. The findings of current investigation revealed that each predatory spider utilized at least one pest species. Predation rate was found higher in the no-choice predation because of unavailability of substitutes feeding source. The investigation also indicated each predatory spider killed more pests than consumed. The findings of this study support the predatory role of spiders in controlling the cotton major pests.

基于改进YOLOv8的棉花虫害检测算法

传统的棉花病虫害检测方法依赖于植物保护专家或经验丰富的农民,这种方法费时费力,并且对于人眼难以观察到的微小病变识别准确率较低。这对如何利用深度学习方法提高识别的准确率和效率,降低人力成本,并且能够对微小病变进行准确识别,提出了新的挑战。针对此问题,提出一种准确率高和实时性好的基于改进YOLOv8的棉花虫害检测算法。首先,使用DCNv3结构,替换YOLOv8 C2模块Bottleneck结构中的普通卷积,形成新的模块记为C2f-DCNv3;其次,在Head的最后一个C2f-DCNv3模块后面加入高效通道注意力,在提升模型精度的同时保持能够实现实时检测。在开源的CottonInsect棉田昆虫识别研究图像数据集上的试验结果表明,所改进方法的mAP为0.706,推理时间为0.6ms,模型大小5.7 MB,相较于原模型YOLOv8n,mAP提升3.0,推理时间提升0.1 ms,模型大小基本保持不变,实现了对于棉花虫害准确且高效的识别。

基于CBAM-YOLO v7的自然环境下棉叶病虫害识别方法

针对自然环境下棉花叶片病害检测难度大和人工设计特征提取器难以获取与棉叶病虫害相近特征表达的问题,提出一种改进的注意力机制YOLO v7算法(CBAM-YOLO v7)。该模型在YOLO v7模型基础上,在Backbone与Head中间增加注意力机制CBAM,并在Head部进行4倍下采样,然后将CBAM-YOLO v7模型用于棉叶病虫害识别,并与YOLO v5和YOLO v7进行对比试验。试验结果表明:蚜虫和正常叶片检测方面,YOLO v7可取得好的检测结果;CBAM-YOLO v7对黄萎病、棉盲蝽、红蜘蛛棉叶病虫害图像检测的准确率高于其他模型。CBAM-YOLO v7的mAP为85.5%,相较于YOLO v5提高21个百分点,相较于YOLO v7提高4.9个百分点;单幅图检测耗时为29.26 ms,可为棉叶病害在线监测提供理论基础。

Cotton Production Systems for Soil and Energy Conservation in Coastal Plain Soils

Cotton growers in the southern USA are facing new production problems that are reducing farm profits and sustainability: 1) herbicide-resistant weeds are spreading throughout the Southeast, 2) thrips are consistently ranked as an important insect pest group Beltwide, 3) the most effective tool for managing nematodes and thrips (aldicarb) currently is only available in the southeastern USA in limited amounts, and 4) fuel costs have increased significantly over the last ten years. An interseeding system was developed at Clemson University that allows planting of cotton into standing wheat, about 2 - 3 weeks before wheat harvest. This system, which combines benefits of crop residue and minimum tillage operations, has the potential to alleviate many of the production problems cited above, while enhancing farm profits and soil properties. Crop residue associated with the interseeding production system reduced weed populations and required significantly less herbicide inputs compared with the conventional system. Columbia lance nematodes populations were reduced in the interseeding system by 83% without an application of nematicide. Populations of thrips were reduced by 74% in the interseeding production system. No differences were observed between the yields from interseeded and the conventional full-season cotton. However, revenues from the interseeding system were higher due to harvest of the wheat crop. In addition, the interseeding system consumed 35% less fuel than the conventional production systems.

中亚地区棉花主要害虫及其综合防治技术应用现状

中亚五国与我国新疆在地理位置上均为远离海洋的区域,属于温带大陆性气候。中亚五国与新疆在作物品种、栽培管理、植物保护和土壤改良等农业生产方面具有相似性。本课题组自2000年起与中亚地区的乌兹别克斯坦植物检疫及植物保护研究所建立了合作,针对棉田有害生物防治进行了长达20余年的合作研究。文章总结了中亚地区棉田主要害虫的发生种类和为害特点,尤其是以天敌繁育释放为重点的综合防治技术,为我国西北荒漠绿洲生态区棉田的害虫防治策略提供了思路。同时提出了在“一带一路”合作倡议背景下,我国与中亚五国加强棉花害虫防控技术合作与交流、学习借鉴乌兹别克斯坦棉田害虫生物防治技术、共同推进棉花重大害虫区域性综合防控技术进步的设想和建议。

郭予元院士在创建中国主要粮棉作物多病虫复合群体综合防治技术体系上的学术贡献——纪念郭予元院士诞辰90周年

本文回顾了郭予元院士在20世纪80-90年代对中国主要粮棉作物多病虫复合群体综合防治技术体系研究与实践中的重要工作,包括组建粮棉作物多病虫复合群体综合防治技术体系的创新性思路、创建主要粮棉作物多病虫复合群体综合防治技术体系,以及对21世纪我国粮棉作物多病虫复合群体综合防治技术体系提出的发展前景和目标等,其中粮棉作物多病虫复合群体综合防治技术体系实施后取得了显著成效。郭予元院士在我国主要粮棉多病虫复合群体综合防治领域的相关学术思想及贡献,对我国农作物病虫害综合防治、可持续治理、绿色防控策略制定以及植物保护学科的发展产生了深远的影响,为我国实现农作物生物灾害可持续控制做出了重要贡献。

Impact Analysis of Genetically Modified (Bt) Cotton Genotypes on Economically Important Natural Enemies under Field Conditions

Field studies were conducted at Hisar during Kharif, 2009-2010 and 2010-2011 under natural and unsprayed condition. RCH 134 Bt, HS 6 (non Bt), H 1117 and Ganganagar Ageti (non Bt) were selected for the studies. The experiment was laid down in Randomized Block Design replicated thrice having plant spacing 67.5 × 60 cm. Among the bollworms, Erias spp. exhibited positive correlation with rainfall, minimum temperature and relative humidity morning hours significantly at 5 percent level whereas Helicoverpa and Pectinophora displayed positive relations only with evening hours relative humidity significantly while Spodoptera were significantly positive correlated with relative humidity of morning and evening hours. Bollworm complex was negatively correlated with all the weather parameters employed to study although being non-significant in case of rainfall, maximum and minimum of temperature, morning and evening hours of relative humidity. Among the sucking pests, leafhoppers, whitefly, thrips and aphids population showed significantly negative correlation with weather parameters. The comparison of natural bio-agents in cotton hybrids under study revealed that overall mean population of natural enemies were higher in Bt cotton hybrid as compared to non-Bt. These results confirm that use of genetically modified (Bt) cotton in lieu of conventional genotypes could positively impact non-target and beneficial insect species by preserving their host populations.

Risk of control failure to insecticides malathion,profenophos+cypermethrin mixture,and fipronil in boll weevil(Coleoptera:Curculionidae)populations from Bahia,Brazil

Background To control the boll weevil Anthonomus grandis grandis(Coleoptera:Curculionidae),a key pest of cotton in the Americas,insecticides have been intensively used to manage their populations,increasing selection pressure for resistant populations.Thus,this study aimed to detect insecticide resistance and assess insecticide control failure likelihood of boll weevil populations exposed to malathion,profenophos+cypermethrin,and fipronil insecticides.Results Twelve populations of the boll weevil were collected from commercial cotton fileds of the state of Bahia,northeastern Brazil.These populations were exposed to malathion,profenophos+cypermethrin mixture,and fipronil,at their respective maximum label dose for field applications.Three replicates of 10 adult beetles were exposed to the insecticides and mortality was recorded after 24 h treatment.The control failure likelihood was determined after 48 h.Highest median lethal times(LT_(50))were observed for malathion and the profenophos+cypermethrin mixture.Resistance to at least one insecticide was detected in 11 populations;three populations were resistant to malathion and profenophos+cypermethrin;seven were resistant to all insecticides tested.The resistance levels were low(<10-fold)for the three insecticides.Among 12 populations tested,58%of them exhibited significant risk of control failure for the insecticides malathion and profenophos+cypermethrin.The insecticide fipronil was efficient for the control of the boll weevil in 83%of the populations.Conclusions The results confirm the significant risk of insecticide control failure in the boll weevil populations to the main compounds used in the region.Thus,proper insecticide resistance management plans are necessary for the boll weevil in the region,particularly for malathion and profenophos+cypermethrin insecticides.

植保无人飞机施药防治农作物病虫害研究进展

近年来,植保无人飞机在我国迅猛发展,已成为防治农作物病虫害的重要手段。目前,植保无人飞机施药已经被广泛应用于水稻、小麦、玉米等主粮作物和以棉花为主的经济作物的病虫害防治中。本文综述分析了植保无人飞机施药对小麦赤霉病、白粉病和蚜虫,水稻纹枯病、稻瘟病和虫害,玉米螟、草地贪夜蛾和杂草以及棉花虫害的防治效果和药剂选择,简要分析了影响植保无人飞机控制效率的因素以及植保无人飞机的发展趋势。上述研究结果对植保无人飞机在作物病虫害防治中的快速发展起到了积极的推动作用。

一种基于Faster-RCNN的棉花虫害识别与统计方法

棉花是我国重要的经济作物,其在生长过程中极易受虫害影响。因此,准确识别棉花害虫并确定其危害程度,为化学防治提供依据意义重大。文章设计了一种基于Faster-RCNN模型的棉花虫害识别方法,并统计其类型和数量参数。试验结果表明:与CNN+RCNN模型相比,单RCNN模型耗时长,且准确率低。该研究工作可为智能化虫害识别系统的开发提供一定的方法基础。

巴基斯坦棉花主要害虫及其综合治理

棉花是巴基斯坦重要的经济作物,棉花产品出口是该国外汇收入的主要来源。在过去10年中巴基斯坦棉花种植面积大幅减少,棉花产量也从2011年的261万t下降至2021年的154万t。烟粉虱Bemisia tabaci及其传播的棉花曲叶病和棉红铃虫Pectinophora gossypiella等有害生物危害是棉花产量下降的主要原因之一。目前,棉花害虫的防治主要依靠背负式喷雾器或机车式喷雾器喷施杀虫剂,无人机施药的政策及大规模推广应用尚处于起始阶段。害虫对杀虫剂抗性上升是目前害虫治理的主要问题。由于信德省和旁遮普省等传统植棉区棉花害虫发生比较严重,巴基斯坦政府计划在俾路支省和开伯尔-普赫图赫瓦省扩大棉花种植面积。为了恢复棉花的生产,政府制定了一系列计划来提高害虫综合治理水平,如研发生物杀虫剂、转基因品种等。针对当前棉花生产过程中所面临的虫害问题,未来应更新害虫治理策略,加强对农业部门技术人员的培训,为巴基斯坦棉花的可持续生产提供技术支持。