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.

Efficiency of Botanical and Chemical Pesticides on the Control of Field Insect Pests under Cowpea Production

The pulse cowpea [Vigna unguiculata (L.) Walp] holds a significant agricultural position in Uganda, ranking fourth among legume crops, following common beans, groundnuts, and soybeans. Known for its versatility, cowpeas are consumable at various developmental stages, from early seedling to maturity. However, the crop faces persistent pest challenges at each stage, leading to substantial yield losses. In Uganda, chemical insecticides are the primary pest control means, but their increased and excessive use raises environmental, health, and economic concerns. This has prompted a quest for alternative and sustainable solutions, prompting an exploration of botanical insecticides. This study, conducted at Makerere University Agricultural Research Institute (MUARIK), aimed to evaluate the effectiveness of three selected botanical insecticides versus four established chemical insecticides for managing cowpea insect pests under field conditions. The treatments included: Carbofuran, Cypermethrin 10% EC, Dimethoate, Pestwin, Pyrethrum ewc , Pyrethrum 5ew, Profenofos 40% Cypermethrin 4% EC mix, and Untreated, arranged in a randomized complete block design with three replications. The significant pests studied were aphids, thrips, pod-sucking bugs, and legume pod borer. Results indicated substantial impacts of the treatments on pest infestation, with Profenofos 40% Cypermethrin 4% EC being the most effective against most pests. The plant parameter, plant height, was significantly affected by treatments in 2016B, while the number of pods was impacted in 2017A. Pestwin, a botanical insecticide blend (containing Azadirachtin indica, Pongamia pinnata, and Ricinus communis extracts) demonstrated superior efficacy against cowpea aphids. Moreover, it positively influenced plant height, number of pods, and pod biomass, surpassing many chemical insecticides. Pestwin’s environmental friendliness positions it as a potential contributor to reducing environmental pollution, making it a promising candidate for inclusion in IPM programs. Overall, the study underscores the importance of exploring botanical alternatives to chemical insecticides for sustainable pest management in cowpea cultivation.

Evaluation of the Efficacy of an Aloe barbadensis Based Biological Insecticide against Pests of Abelmochus esculentus for Promoting Ecological Agriculture (Far-North, Cameroon)

Chemical insecticides have been considered as a means to combat crop pests. Although their effectiveness is evident, their impact on the environment is increasingly being discussed. The aim of this study is to determine the agro-ecological potential of a biological insecticide (C25H32O12) based on Aloe barbadensis in a Sahelian context. For this purpose, a completely randomized block experimental design with 3 replications and 4 treatments was set up to experiment with Aloe barbadensis as a bioinsecticide against pests of Abelmoschus esculentus. However, data were collected using an observation and parameter monitoring grid. This includes the cultivation of Abelmoschus esculentus, soil preparation, seeding and watering, plot labeling, preparation of the bioinsecticide (selection and preparation of raw materials, grinding of Aloe barbadensis miller and extraction of the crude bioinsecticide, quantification of treatment doses and dilution, and obtaining the formulated bioinsecticide), plant watering, plant treatment, and finally parameter monitoring. The results obtained reveal that the level of damage is significantly high in the control treatment T0 (63%) compared to the other treatments, with 29% for treatment T1, 7% for T2, and 1% for T3, implying a strong action capability of this insecticide against pests of Abelmoschus esculentus. Therefore, it can be concluded that for a normal growing season of Abelmoschus esculentus, this biological insecticide should be sprayed 12 times. Furthermore, this biological insecticide is unique in that it does not inflict any gastric toxicity on the pests, which gives it the characteristic of being a repellent. It is a biological insecticide whose efficacy period has been tested, with a minimum duration of 21 days. In conclusion, this formulated bioinsecticide based on Aloe barbadensis demonstrates significant efficacy against pests of Abelmoschus esculentus. In the future, we will consider experimenting with its effectiveness against pests of other plants.

A Review on the Application of Deep Learning Methods in Detection and Identification of Rice Diseases and Pests

In rice production,the prevention and management of pests and diseases have always received special attention.Traditional methods require human experts,which is costly and time-consuming.Due to the complexity of the structure of rice diseases and pests,quickly and reliably recognizing and locating them is difficult.Recently,deep learning technology has been employed to detect and identify rice diseases and pests.This paper introduces common publicly available datasets;summarizes the applications on rice diseases and pests from the aspects of image recognition,object detection,image segmentation,attention mechanism,and few-shot learning methods according to the network structure differences;and compares the performances of existing studies.Finally,the current issues and challenges are explored fromthe perspective of data acquisition,data processing,and application,providing possible solutions and suggestions.This study aims to review various DL models and provide improved insight into DL techniques and their cutting-edge progress in the prevention and management of rice diseases and pests.

Technical Points of Green Prevention and Control Technology of Major Diseases and Pests in Lixian Rhubarb(Rheum palmatum L.)

Based on different types of diseases,pests and weeds in the whole growth period of rhubarb(sowing period-harvesting period),the corresponding green prevention and control technology is proposed,aiming to further reduce the application amount of pesticides and fertilizers in the production of medicinal sources of Lixian rhubarb during the"14 th Five-Year Plan"period.The results will provide a theoretical basis for increasing the promotion and application of agricultural prevention and control(including disease-resistant varieties,ecological regulation),physical prevention and control,biological prevention and control measures,thus ensuring effective protection of the ecological environment,green,healthy and sustainable development of traditional Chinese medicine agriculture in Longnan,and source quality of authentic medicinal materials.

Major Diseases and Pests of Blueberry in Guizhou Province and Progress in Their Prevention and Control

As the blueberry industry continues to evolve,the effective control of its diseases and pests has become an essential component of local agricultural development.This paper provides a comprehensive overview of the principal types of blueberry diseases and pests in Guizhou Province,along with the corresponding control measures,in order to serve as a valuable reference for blueberry growers.

Comprehensive Prevention and Control Technology of Vegetable Diseases and Pests in Shandong Province

An in-depth research and practice has been conducted on vegetable diseases and pests in Shandong Province,and the principles of comprehensive and ecological control of diseases and pests are put forward,including agricultural control measures such as crop rotation,field cleaning,fertilizer and water management,physical control measures such as catching and killing,trapping,blocking,photoelectric energy treatment,biological control measures such as the use of natural enemies,pathogenic microorganisms,other beneficial organisms and metabolites,and scientific and rational chemical control measures.Comprehensive prevention and control not only controls vegetable diseases and pests effectively,but also protects the ecological environment.

基于SWOT和PEST分析的模块化麻醉学技能培训教学模型应用

目的探讨基于SWOT和PEST分析的模块化配置麻醉学临床技能培训教学模型在研究生培训过程中的应用。方法选取2022年12月至2023年8月在郑州大学第一附属医院麻醉临床轮转的80名研究生,随机分为观察组(n=40)和对照组(n=40)。对照组采用传统教学方法,观察组采取基于SWOT和PEST分析的模块化配置麻醉学临床技能培训教学模型教学,比较两组研究生的技能考试成绩、案例分析成绩、基础理论成绩,以及对教学满意度评分。结果观察组研究生培训后的技能考试、案例分析、基础理论成绩均高于对照组,差异均有统计学意义(t分别=7.18、8.44、8.69,P均<0.05),观察组带教满意度评分高于对照组,差异有统计学意义(t=18.91,P<0.05)。结论基于SWOT和PEST分析的模块化配置麻醉学临床技能培训教学模型在研究生技能培训中的应用可有效提高临床技能水平和综合应用能力,有助于实践能力和临床思维的培养。

DRG/DIP模式下日间手术运营管理创新PEST分析

目的运用PEST分析的创新方法,对DRG/DIP模式下日间手术运营管理进行探索,以期为管理者提供新的思路。方法根据PEST分析框架,提取关键指标进行分析,根据上述数据和文献分析,提出创新的日间手术运营管理策略。结果需要推动DRG/DIP政策的修订和完善,同时加强手术管理规范,以促进日间手术管理创新;合理分配医疗资源,降低成本,提高综合效益;深入了解患者需求,提高服务质量;加强日间手术管理信息平台建设和全程管理与监测,积极开展新技术,满足患者高品质医疗服务需求。结论推动日间手术持续高质量发展,必须完善相关规范和制度,加强全流程管理。

基于PEST模型的主要发达国家农业气象服务发展及其启示

近年来气候变化带来的负面影响对农业生产产生了切实的影响,各国采取了系统性的措施来更好地应对气候变化的挑战,确保国家粮食安全和农业可持续发展。文中采用PEST模型系统分析了美国、欧洲和以色列等发达国家/地区及农业特色国家在农业气象服务发展上的最新进展和成功经验,结论:1) 在政治方面(Political),这些国家通过完善法律法规体系和优化政策,提供了强大的政策支持和法律保障;2) 在经济方面(Economic),通过农业气象资金支持和农业气象保险大力推动农业气象服务的发展,并为农业从业者应对气象灾害提供了充足的资金保障;3) 在社会方面(Social),通过打造免费共享的高质量农业气象信息服务系列产品和高度重视农业教育,扩大了农业气象服务的影响力并提升了农业从业人员的素质;4) 在技术方面(Technological),通过建立完善的农业气象观测网络,研发改进作物生长模拟模型和推广气候智能型农业,有效地保障了农业气象服务的效率和效益,并推动了农业的绿色可持续发展。这些经验对于促进我国农业气象服务发展具有重要的借鉴意义,能够为推动我国农业气象服务高质量发展提供一定的参考。

历史文化街区研究的PEST分析及更新策略建议

为了留存城市文化脉络,提出更行之有效的历史文化街区更新策略,以中国知网(CNKI)为数据来源,综合运用PEST模型和文献计量分析方法,综述历史文化街区的研究现状,为开展相关工作提供可借鉴的理论依据。通过在中国知网中检索“历史文化街区”的相关研究文献,从政治、经济、社会、技术4个维度出发,运用文献可视化分析软件对筛选出的文献进行关键词聚类分析,梳理研究热点和重点,总结得出我国历史文化街区保护工作应形成以政府为主导,社会、企业、民众多元参与的有机协调模式,坚持“原真性”修复原则,提高建筑应对灾害的能力,让历史文化街区焕发新的生机与活力。

北京地区医疗机构科技成果转化的PEST-SWOT分析

目的 探讨医疗机构科技成果转化工作策略。方法 通过专利数据库、文献检索分析北京地区医疗机构近年来的专利及转化情况,结合政策文本进行PEST-SWOT分析。结果 北京地区医疗机构专利申请、授权增多,进行成果转化的优势和机会明显,也存在一定的劣势与威胁,转化率需要提升。结论 医疗机构应顺应政策要求,发挥资源优势,加强产业融合,提升成果价值和知识产权运营能力,完善转化机制。

基于PEST模型的中国智慧医疗发展环境分析

目的/意义探讨中国智慧医疗发展的宏观环境,明晰现状,剖析存在的问题,并提出相应的建议措施,以期促进智慧医疗进一步发展。方法/过程基于PEST模型,从政治、经济、社会、技术方面讨论智慧医疗发展的宏观环境。结果/结论目前国家高度重视智慧医疗发展,智慧养老和疾病诊疗的需求逐步扩大,新兴技术飞速进步为智慧医疗的发展提供了利好环境。但其发展也存在政策法规不健全、社会接受度低、信息孤岛以及信息安全隐患等问题。对此应加强顶层设计,做好宣传培训,突破技术瓶颈,保障信息安全,促进智慧医疗良性发展。

老年失能精准防控体系建设发展的SWOT-PEST分析

目的:分析我国老年失能精准防控体系的内、外部环境和优、劣势,为促进其高质量发展提供参考。方法:运用SWOT-PEST分析模型从政治、经济、社会、技术四个方面对我国老年失能精准防控体系的内、外部因素进行系统分析,归纳总结出我国老年失能精准防控体系建设发展过程中的优势、劣势、机遇和挑战。结果:我国老年失能精准防控体系具有国家政策助力发展、信息技术发展迅速、老龄化程度加深及国外先进经验丰富等较好的内部优势与外部机遇,但也有相关标准规范不完善、老年人对精准防控体系认知不足及高质量人才缺乏等关键劣势和威胁需要规避。结论:我国老年失能精准防控体系应建立预防为主、防治结合的新思路,加大政府政策支持力度,积极培养高素质专业人才和挖掘社会资源,促进我国老年精准防控体系快速发展,助力积极应对人口老龄化战略。

数字化语境下三少民族非物质文化遗产传播的PEST 分析

鄂温克族、达斡尔族、鄂伦春族“三少”民族在发展过程中衍生出了浓郁的少数民族文化特色,但由于“三少”民族世代的文化传承大多依赖口头传播,并未形成文字,使其在非物质文化遗产的整体传承、保护和协调发展中面临着极大的挑战与困难,虽然早在2010年内蒙古自治区文化厅就启动了对鄂温克、鄂伦春和达斡尔三个少数民族非物质文化遗产的“国家抢救人口较少民族非遗项目”,加快完善了非物质文化遗产的基础设施建设,建立了非遗综合示范馆、专题保护馆和科普传习所,开展了专项保护、展示推介和教育传习等培训活动,在进一步加强文化宣传等方面发挥了相当大的推动作用,但大部分地方的宣传行动主要依靠政府主导,社会大众参与宣传的意愿并不高,很难形成合力。在当今的信息化时代,数字化技术逐渐被人类广泛应用于各个传统领域。基于此,运用pest模型对“三少”民族非物质文化遗产的数字化保护管理与数字化传承开发进行实证分析,拓展我国“三少”民族非物质文化遗产资源的保护与传承的数字化研究路径,不仅能适应信息化时代社会的迅速发展,让习惯于使用现代信息化手段的广大青少年能够熟悉“三少”民族传统文化,增强民族文化认同感,提高保护、传承民族文化的自觉,而且也能化解当前非物质文化遗产项目保护工作和对外传承中面临的双重困境,让“三少”民族文化非物质文化遗产既能“活”起来,也能“火”起来。

基于SWOT-PEST模型分析我国儿童青少年近视预防事业发展策略

目的:分析儿童青少年近视预防工作所面临的内部及外部环境因素,并提出相应策略,进而推动儿童青少年近视预防事业可持续发展。方法:基于SWOT-PEST模型,深入分析我国儿童青少年近视预防事业发展的优势与劣势,并从政治、经济、社会和技术四个维度梳理其发展的机遇与威胁。结果:从政策、经济、社会、医疗等多方主体提出发挥政策引领作用、扩大宣传、加强筛查建档等相应策略。结论:我国儿童青少年近视预防事业尚存在监管机制不健全、宣传教育欠缺等问题。本研究基于多方主体提出相关发展策略,以期为推动儿童青少年近视预防事业提供借鉴与参考。

Main Pests and Diseases of Zingiberaceae and Their Control

The primary diseases affecting Zingiberaceae plants include ginger plague, spot blotch, anthracnose, leaf spot, leaf blight, and soft rot. Insect pests that pose a threat to these plants encompass root-knot nematode disease, drilling bugs, beet nightshade moths, mesquite, thrips, and aphids. This article aims to summarize the defining features of the principal pests and diseases as well as their control methods. The intention is to offer theoretical support for the preservation of ginger plants.

Research Progress of Genomes of Insect Pests in Paddy Field

Innovations in sequencing technology and the development of bioinformatics have allowed for studies of the genomics of many rice pests.At present,draft genomes of rice pests including Nilaparvata lugens,Sogatella furcifera,Laodelphax striatellus,Sesamia inferens,Chilo suppressalis,Scirpophaga incertulas.

Advanced biosensing technologies for monitoring of agriculture pests and diseases:A review

The threat posed to crop production by pests and diseases is one of the key factors that could reduce global food security.Early detection is of critical importance to make accurate predictions,optimize control strategies and prevent crop losses.Recent technological advancements highlight the opportunity to revolutionize monitoring of pests and diseases.Biosensing methodologies offer potential solutions for real-time and automated monitoring,which allow advancements in early and accurate detection and thus support sustainable crop protection.Herein,advanced biosensing technologies for pests and diseases monitoring,including image-based technologies,electronic noses,and wearable sensing methods are presented.Besides,challenges and future perspectives for widespread adoption of these technologies are discussed.Moreover,we believe it is necessary to integrate technologies through interdisciplinary cooperation for further exploration,which may provide unlimited possibilities for innovations and applications of agriculture monitoring.

Differentiation of Wheat Diseases and Pests Based on Hyperspectral Imaging Technology with a Few Specific Bands

Hyperspectral imaging technique is known as a promising non-destructive way for detecting plants diseases and pests.In most previous studies,the utilization of the whole spectrum or a large number of bands as well as the complexity of model structure severely hampers the application of the technique in practice.If a detection system can be established with a few bands and a relatively simple logic,it would be of great significance for application.This study established a method for identifying and discriminating three commonly occurring diseases and pests of wheat,i.e.,powdery mildew,yellow rust and aphid with a few specific bands.Through a comprehensive spectral analysis,only three bands at 570,680 and 750 nm were selected.A novel vegetation index namely Ratio Triangular Vegetation Index(RTVI)was developed for detecting anomalous areas on leaves.Then,the Support Vector Machine(SVM)method was applied to construct the discrimination model based on the spectral ratio analysis.The validating results suggested that the proposed method with only three spectral bands achieved a promising accuracy with the Overall Accuracy(OA)of 83%.With three bands from the hyperspectral imaging data,the three wheat diseases and pests were successfully detected and discriminated.A stepwise strategy including background removal,damage lesions recognition and stresses discrimination was proposed.The present work can provide a basis for the design of low cost and smart instruments for disease and pest detection.