重大农业入侵害虫番茄潜叶蛾检测鉴定技术研究进展

姚若楠,  王玉生,  张桂芬,  谭琳

姚若楠, 王玉生, 张桂芬, 等. 重大农业入侵害虫番茄潜叶蛾检测鉴定技术研究进展 [J]. 环境昆虫学报, 2025, 47(1): 12-21. doi: 10.3969/j.issn.1674-0858.2025.01.2
引用本文: 姚若楠, 王玉生, 张桂芬, 等. 重大农业入侵害虫番茄潜叶蛾检测鉴定技术研究进展 [J]. 环境昆虫学报, 2025, 47(1): 12-21. doi: 10.3969/j.issn.1674-0858.2025.01.2
YAO Ruo-Nan, WANG Yu-Sheng, ZHANG Gui-Fen, et al. Advances in identification techniques for Tuta absoluta (Meyrick), a notorious invasive agricultural insect pest [J]. Journal of Environmental Entomology, 2025, 47(1): 12-21. doi: 10.3969/j.issn.1674-0858.2025.01.2
Citation: YAO Ruo-Nan, WANG Yu-Sheng, ZHANG Gui-Fen, et al. Advances in identification techniques for Tuta absoluta (Meyrick), a notorious invasive agricultural insect pest [J]. Journal of Environmental Entomology, 2025, 47(1): 12-21. doi: 10.3969/j.issn.1674-0858.2025.01.2

重大农业入侵害虫番茄潜叶蛾检测鉴定技术研究进展

doi: 10.3969/j.issn.1674-0858.2025.01.2
基金项目: 

国家重点研发计划 2021YFD1400200;

湖南省自然科学基金 2024JJ6238

详细信息
    作者简介:

    姚若楠,女,硕士研究生,研究方向为植物保护与植物检疫,E-mai: yaoruonan202202@163.com

    共同通讯作者 Author for correspondence:

    张桂芬,博士,研究员,研究方向为入侵生物学,E-mail: guifenzhang3@163.com;

    谭琳,博士,副教授,研究方向为植物保护与害虫生物防治,E-mail: hqltanlin@163.com

  • 中图分类号: Q968.1

    文献标识码: A

    文章编号: 1674-0858(2025)01-0012-10

Advances in identification techniques for Tuta absoluta (Meyrick), a notorious invasive agricultural insect pest

  • 摘要:

    番茄潜叶蛾Tuta absoluta(Meyrick)(异名Phthorimaea absoluta)是一种多食性的重大农业入侵害虫,主要危害番茄、马铃薯等茄科作物,可造成番茄减产50%~80%,甚至绝产绝收,有“番茄埃博拉病毒”之称,2017年首次在我国新疆被发现,已在我国局部地区暴发。番茄潜叶蛾常隐蔽发生,且在我国的适生区广泛,主要随番茄苗及果实的销运进行远距离传播,进一步扩散势头明显。因此,亟需研发高效低成本的番茄潜叶蛾检测鉴定技术和方法,进而实现对重大入侵物种的及早发现和提前预警,降低农业经济损失。目前,用于番茄潜叶蛾的检测鉴定技术方法主要包括传统形态学鉴定、分子生物学检测以及基于人工智能的图像识别技术等,本文综述了番茄潜叶蛾检测鉴定技术的研究现状并展望了其发展趋势,旨在为延缓番茄潜叶蛾传播扩散与对靶施策提供技术支撑。

     

    Abstract:

    The tomato leaf miner, Tuta absoluta (Meyrick), also known as Phthorimaea absoluta, is a significant polyphagous invasive agricultural pest. It primarily infests Solanaceae crops, such as tomatoes and potatoes, and can cause tomato yield losses of 50%~80%, or even complete crop failure. Therefore, as the "Ebola virus of tomatoes", T. absoluta was first found in Xinjiang, China, in 2017, and has broken out in several regions of China. T. absoluta often occurs covertly, and its suitable habitats are widespread in China. This pest can transmitted over long distances through the transport of tomato seedlings and fruits, indicating a clear trend of further spread.Therefore, there is an urgent need to develop efficient and low-cost detection and identification technologies and methods for T. absoluta, in order to achieve early detection and advance warning of this significant invasive species.Currently, the primary techniques used to identify T. absoluta include traditional morphological identification methods, molecular biological detection techniques, and artificial intelligence-based image recognition methods. In this paper, the research status of detection and identification technology of T. absoluta was reviewed, and its development trend was prospected, aiming at providing technical support for delaying the spread and diffusion of T. absoluta and targeting strategies.

     

  • 番茄潜叶蛾Tuta absoluta(Meyrick)(异名Phthorimaea absoluta),又称番茄潜麦蛾、番茄麦蛾、南美番茄潜叶蛾,属于鳞翅目Lepidoptera麦蛾科Gelechiidae,原发于南美洲(Corro,2021),是全球范围内对番茄及其他茄科作物构成严重威胁的重大农业入侵害虫(Santana et al.,2019)。自2009年在土耳其首次报道番茄潜叶蛾入侵亚洲以来(Kılıç,2010),该虫随鲜食番茄以及种苗的贸易活动,迅速扩散至印度(Sridhar et al.,2014)、孟加拉国和尼泊尔(Bajracharya et al.,2016;Hossain et al.,2016)、巴基斯坦(Ishtiaq et al.,2020)、中国(Zhang et al.,2020)、缅甸(Yule et al.,2021)、韩国(Lee et al.,2024)等国家,目前已在南美洲、欧洲、非洲、亚洲、大洋洲等的110多个国家和地区发生和危害(Soares and Campos,2020)。

    番茄潜叶蛾寄主植物种类多,可危害番茄、马铃薯、茄子、人参果、烟草、甜椒、龙葵、以及黄瓜、菜豆等11科50种植物,且发育速度快、繁殖能力强,世代重叠现象明显,卵、幼虫(1~4龄)、蛹、成虫常同时发生(Biondi et al.,2018;Soares and Campos,2020;张桂芬等,2022;Pandey et al.,2023)。番茄潜叶蛾适生区范围广,传播扩散迅速,而且与潜蝇类害虫同时发生,常造成误识误判,延误防治时机,或防治措施不得当,在新入侵地严重发生时可导致番茄种植业近乎100%的产量损失(Desneux et al.,2010;Zhang et al.,2020;尹艳琼等,2021;Acharya et al.,2023)。如,在荷兰、伊朗等地,每年因番茄潜叶蛾危害造成的番茄作物经济损失分别高达1 700万美元和3 500万美元(Aigbedion et al.,2019)。目前,番茄潜叶蛾已经对多种杀虫剂产生了抗性,如有机磷类、双酰胺类等(Guedes et al.,2019;李晓维等,2023),导致防治难度进一步增强。番茄潜叶蛾入侵新地域后,不仅显著增加了防治成本,还导致化学农药使用量的大幅提升,造成环境污染,严重威胁农业生产安全(Biondi et al.,2018)。因此,研发精准、低成本、高效的番茄潜叶蛾检测鉴定技术以指导正确防治势在必行。精准、快速的检测鉴定手段,不仅能够实现早期预警,有效遏制其传播扩散,更是生产实践中对靶施策的关键。

    在田间,与番茄潜叶蛾同时发生的潜叶蝇类害虫,主要有美洲斑潜蝇Liromyza sativa、南美斑潜蝇Liriomyza huidobrensis、豌豆彩潜蝇Chromatomyia horticola等,他们同域同期发生,甚至在同一块番茄田或同一番茄植株上同时发生;而其他鳞翅目害虫,如棉铃虫Helicoverpa armigera、甜菜夜蛾Spodoptera exigua、马铃薯块茎蛾Phthorimaea operculella等,亦常常出没于番茄田,且其幼龄幼虫潜食或啃食的为害症状与番茄潜叶蛾的为害状极为相似,加之幼虫(尤其是幼龄幼虫)形态相近,难以通过单一的形态学鉴定方法对物种进行准确识别鉴别。基于物种的外部形态特征,并结合分子生物学检测技术、人工智能图像识别等技术,可为番茄潜叶蛾的精准检测提供更为可靠的识别鉴定方案(Tabuloc et al.,2019;Liu et al.,2023)。本文将简要综述番茄潜叶蛾鉴定技术的最新研究进展,以期为重大农业害虫防治、农作物生产安全保护、以及入侵害虫监控提供科学依据。

    传统的形态学鉴定主要依赖于对昆虫外部形态特征的观测或解剖分析,方法简单直观,成本低廉,对害虫的早期发现和防控具有重要意义,但主要依赖于成虫(或成虫某一性别)的外表特征,依赖于检测鉴定人员的经验,准确率可达90%左右(Barrientos et al.,1998)。然而,番茄潜叶蛾个体微小,卵和初孵幼虫体长不足0.5 mm(Soares and Campos,2020),极难准确辨识;而成虫的鉴别,尚需借助雄性外生殖器的外部形态特征(番茄潜叶蛾雄虫抱握器呈指状,顶端多毛,阳茎发达,具有突出的盲囊)(Bajracharya et al.,2016;张桂芬等,2019),对基层一线植保植检人员亦具有相当的挑战性。尽管,在田间还可借助手持放大镜对靶标种害虫的外部形态特征进行观察,通过对不同发育阶段/虫态的形态特征对比分析,完成对物种的初步判定(Povolný,1994),但亦绝非易事。

    基于物种外部特征的形态学鉴定方法虽然简单直观,但在实际应用中存在一定局限性。如,在田间利用粘胶式性诱捕器或电击式灯光诱捕器采集的番茄潜叶蛾成虫样本,常混杂有其他种类的鳞翅目害虫,且多数样本肢体残缺不全,进而影响了样本形态学特征的完整性,即使是经验丰富的专业人员也难以准确识别,从而限制了该技术方法应用的广泛性和普适性(王雅娜等,2024)。

    基于分子生物学的物种检测鉴定技术,不受昆虫发育阶段或标本完整性的影响,而且准确、快速、高通量,亦即,可同时检测鉴定同一物种的多个个体或多个种类的昆虫物种。目前,常用于番茄潜叶蛾检测鉴定的分子生物学技术主要包括随机扩增多态性DNA标记(Random Amplified Polymorphic DNA,RAPD)技术、DNA序列分析(DNA Sequencing)技术、特征序列扩增区域(Sequence Characterized Amplified Regions,SCAR)标记技术、物种特异性PCR(Species-Specific PCR,SS-PCR)技术、实时荧光定量PCR(Real-Time Fluorescent Quantitative PCR,qPCR)技术、微滴式数字PCR(Droplet Digital Polymerase Chain Reaction,ddPCR)技术、环介导等温扩增(Loop-mediated Isothermal Amplification,LAMP)技术、重组酶聚合酶扩增(Recombinase Polymerase Amplification,RPA)技术和重组酶介导等温核酸扩增(Recombinase Aided Amplification,RAA)技术等(表 1)。通常,基于分子生物学的检测鉴定技术多选取长度适中、保守性强、信息位点丰富且核苷酸变异较快的序列作为目标物种的特异性靶基因序列,如核糖体内源转录间隔区1(Internal Transcribed Spacer 1,ITS1)、内源转录间隔区2(Internal Transcribed Spacer 2,ITS2),或线粒体DNA细胞色素C氧化酶亚基Ⅰ(Cytochrome C Oxidase Subunit Ⅰ,CO I)、细胞色素C氧化酶亚基Ⅱ(Cytochrome C Oxidase Subunit Ⅱ,CO Ⅱ)和细胞色素C氧化酶亚基Ⅲ(Cytochrome C Oxidase Subunit Ⅲ,CO Ⅲ)基因等,以区分番茄潜叶蛾与其近似种或近缘种(Hillis,1991;Desneux et al.,2011)。

    表  1  用于番茄潜叶蛾检测鉴定的分子生物学技术
    Table  1  Molecular detection techniques for the identification of tomato leaf miner
    检测技术Techniques 靶标序列
    Target sequence
    靶标物种
    Target species
    参考文献
    References
    RAPD-PCR 核酸基因组Genomics 番茄潜叶蛾Tuta absoluta Bettaïbi et al.,2012
    DNA序列分析 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta 马琳等,2021
    SCAR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta 张桂芬等,2020
    SS-PCR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta 张桂芬等,2013
    qPCR 核苷酸基因组Genomics mtDNA CO I、核糖体rDNA ITS 番茄潜叶蛾Tuta absoluta(多靶标检测) Lewald et al.,2023
    ddPCR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta Zink et al.,2022
    LAMP 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta Yang et al.,2024
    RPA-CRISPR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta(多靶标检测) Lewald et al.,2023
    番茄潜叶蛾Tuta absoluta Shashank et al.,2024
    RAA-LFS 核苷酸基因组Genomics mtDNA CO Ⅰ 番茄潜叶蛾Tuta absoluta Cao et al.,2024

    1983年,Mullis等发明了一种在体外模拟生物体复制特定DNA片段的分子生物学技术,即聚合酶链式反应(Polymerase Chain Reaction,PCR)技术(Kb,1987)。PCR技术的发明推动了基于DNA核酸扩增的分子生物学技术的快速发展,并催生了RAPD-PCR、SCAR等多项技术,得以用于物种鉴定和物种多样性研究(Power,1996)。

    2.1.1   RAPD-PCR标记技术

    RAPD-PCR标记技术是借助设计长度为10个碱基对的随机寡核苷酸引物,通过PCR对未知序列的基因组DNA进行随机扩增,产生不同长度的扩增子片段,从而实现对样本的区分和鉴定。2012年,Bettaïbi等以在突尼斯不同地区采集的番茄潜叶蛾为靶标,采用RAPD-PCR技术对其基因组DNA进行遗传变异分析,获得了140条多态性片段(Bettaïbi et al.,2012)。虽然RAPD标记技术对样本模板DNA的需求量比较少,且单次检测成本比较低,然而,由于结果重复性较差,特异性不高,整个实验过程约需5 h,因此难以满足物种快速、准确鉴定的需求,逐渐被更为稳定、灵敏和可靠的SCAR标记技术所取代。

    2.1.2   DNA序列分析技术

    DNA序列分析对于了解物种的基因结构、表达及分子进化关系等具有十分重要的意义,序列测定是对入侵害虫分类鉴别的重要手段。随着昆虫物种特异性区段的不断挖掘和一代Sanger测序成本的大幅度下降,从疑似样本中提取虫体总基因组DNA,使用rDNA ITS或mtDNA CO I通用型引物进行PCR扩增,经Sanger测序即可快速确定PCR纯化产物的碱基序列,经扩增产物的序列比对,构建系统发育树后判定待测样本的物种种类,目前已逐渐成为一种常见的入侵害虫检测技术,且准确率高(通常可达99%)(Vrijenhoek,1994;Zhang et al.,2000;Cifuentes et al.,2011;Tamura et al.,2013)。其中,隶属鳞翅目的入侵害虫番茄潜叶蛾、苹果蠹蛾和美国白蛾等均已形成了基于序列分析的物种检测鉴定技术体系(马琳等,2021;李安娟和柳丽君,2023)。然而,DNA序列分析技术需要外送测序,通常耗时3 d以上,且尚需后续的序列剪切、比对分析等,其适用性和时效性受到了制约(顾建锋等,2023)。

    2.1.3   SCAR标记技术

    SCAR标记技术由Paran和Michelmore等研发,是在RAPD基础上研发的基于特异性扩增区的分子标记技术(Paran and Michelmore,1993),其扩增产物通常单一,且特异性强,检测结果的重复性和准确性更高,更适合物种鉴定和种间差异检测(Agustí et al.,2000)。如,张桂芬等(2020)研发了基于SCAR标记技术的番茄潜叶蛾检测试剂盒,使用设计的特异性检测引物对TAZBF1/TAZBR1可准确区分番茄潜叶蛾与其它22种常见的潜叶类、食叶类、以及蛀果类昆虫,检测时长约为5 h,基因组DNA模板的检测极限为1.08 ng/μL,且识别准确率高(达100%),为番茄潜叶蛾的早期识别鉴定和有效防范提供了技术支撑。然而,SCAR检测鉴定技术需要进行DNA提取、受限于PCR反应条件以及电泳检测分析,难以满足田间现场检测鉴定需求(Amiteye,2021)。

    2.1.4   SS-PCR检测技术

    SS-PCR检测技术是一种用于扩增物种特异性DNA片段的技术,主要特征在于能够产生单链DNA扩增产物,且物种鉴定准确率高(达98%以上)(Guedes et al.,2019)。与传统PCR不同,SS-PCR关注的是在扩增过程中生成的单链DNA,而不是双链DNA(Sun et al.,2023)。SS-PCR检测技术通过对靶标种的DNA序列测定、以及与近似种相关序列的比对分析,设计靶向番茄潜叶蛾的特异性扩增引物对,经过特异性检验验证,可直接利用该对特异性引物对靶标种DNA进行PCR扩增,然后通过对PCR产物的琼脂糖凝胶电泳检测,借助特异性条带的有无判定样品物种(张桂芬等,2012)。如,张桂芬等(2013)开发了番茄潜叶蛾的SS-PCR技术,设计了靶向番茄潜叶蛾COI基因的特异性引物对TAZJCE1/TAZJCF1,使用该引物对可扩增单粒卵、单根触角、头部、胸部、腹部、膜质的翅以及角质化程度比较高的足等微量样品或残体DNA,仅需琼脂糖凝胶电泳检测,即可准确区分番茄潜叶蛾与其它6种形态相似的潜叶类害虫,DNA检测极限为0.31 ng/μL,该技术在首次发现番茄潜叶蛾入侵我国的物种确证中发挥了巨大作用。然而,该技术面临难以现场化应用的问题。

    2.2.1   qPCR检测技术

    qPCR是在常规PCR基础上发展起来的一种核酸定量检测技术,其基本原理是在PCR反应体系中加入荧光标记物,随着PCR反应的进行和扩增产物的增加,荧光信号也随之增强(Heid et al.,1996)。进而通过专用检测设备对荧光信号进行实时采集和检测,可以实现对PCR扩增过程的动态监控,最终通过荧光扩增曲线对扩增结果进行定量分析(Higuchi et al.,1992)。根据荧光标记物的不同,qPCR又可分为荧光染料法和荧光探针法。其中,荧光探针法的TaqMan探针与特定靶序列完全互补,只有当引物和探针与靶基因同时结合时,扩增时探针才会被水解酶切发出荧光,从而避免了非特异性扩增产物的干扰;而且,荧光探针法还可检测两个或多个靶标,非常适合入侵害虫的检测鉴定(Kaltenboeck,2005)。如,Lewald等(2023)利用CO I基因,建立了靶向番茄潜叶蛾、番茄茎麦蛾Keiferia lycopersicella和马铃薯块茎蛾的单核苷酸多态性标记的多重探针qPCR检测技术,仅需约2 h即可完成从DNA提取到检测结果判定的整个过程,DNA检测极限为0.02 ng/µL。目前该技术主要用于海关、口岸有害生物的检测鉴定分析。然而,qPCR所需仪器和试剂价格较高,而基层植保植检部门的相应设备及专业技术人员配置匮乏,实用性欠佳。

    2.2.2   ddPCR检测技术

    微滴式数字PCR(ddPCR)是继qPCR之后发展起来的一项新兴的分子检测技术,可将PCR反应混合物分散成数万个微小液滴,每个液滴均可作为一个独立的PCR反应单元进行扩增和检测,可提供比qPCR更精确和重复性能更好的数据(Hindson et al.,2013;Taylor et al.,2017)。且该技术无需标准曲线,可更高效地实现低浓度核酸分子的绝对定量,有利于入侵害虫的早期发现和准确判定(Taylor et al.,2019;Lei et al.,2021)。如,Zink等(2020)设计了可同时用于番茄潜叶蛾qPCR和ddPCR的检测体系,仅需1个多小时即可准确区分番茄潜叶蛾与美国番茄产区的其它近似种昆虫,该技术的DNA检测极限更是低至了1.00 pg/µL。之后,Zink等(2022)又对ddPCR技术的DNA提取方法进行了优化,可无损伤提取数百个样品基因组DNA,缩短了批量混检样品的检测时间;如获得的检测结果为阳性,则可使用实时qPCR完成样本的单独检测,以进一步明确是否存在番茄潜叶蛾的入侵,进而实现了对入侵区域的及时监测。然而,ddPCR检测技术所需仪器昂贵,且对仪器操作人员要求较高,进而限制了该技术应用的广泛性和普及性。

    环介导等温扩增(LAMP)检测技术由日本荣研化学株式会社于2000年研发成功,该技术主要依赖于Bst DNA聚合酶的自动链置换特性,可在60~65℃恒温条件下,通过4~6个引物高效扩增靶基因核酸序列(Notomi et al.,2000;Becherer et al.,2020)。LAMP检测技术扩增产物可通过琼脂糖凝胶电泳、比色法、荧光信号测定、实时监测浊度测定、侧向层析检测等方法进行结果显示,已被广泛用于多种入侵昆虫的田间检测和监测(Mori et al.,2004;Parida et al.,2008;Tomita et al.,2008;Wong et al.,2018)。如Yang等(2024),基于CO I基因研发了番茄潜叶蛾LAMP可视化检测鉴定技术,基因组DNA扩增后,无需开盖,通过观察反应液SYBR Green染料的荧光信号即可准确区分番茄潜叶蛾与美洲斑潜蝇、豌豆彩潜蝇和马铃薯块茎蛾等近似种,DNA检测灵敏度达0.83 ng/µL,单次使用DNA模板反应成本低至约7.00元。同时,该检测技术体系还可直接检测昆虫组织,并可在控温保温杯中进行反应,完全可以满足基层植保植检人员对番茄潜叶蛾疫情的快速现场鉴定的需求。然而,LAMP检测技术容易发生非特异性扩增,以及反应体系不稳定等缺点(王旭等,2022;顾建锋等,2023)。

    2006年报道的重组酶聚合酶扩增(RPA)技术,主要是利用T4噬菌体的重组酶uvsX、单链DNA结合蛋白gp32和链置换DNA聚合酶,模拟DNA的体内扩增,在等温条件下,实现对目的片段的指数扩增(Piepenburg et al.,2006)。如,英国TwistDx Inc公司开发的商业化TwistAmp®检测试剂盒,单次检测费用约为110.00元(Lin et al.,2021)。该产品可结合探针检测系统,在37℃条件下15 min内即可实现对单分子的核酸检测,并借助侧向层析检测或荧光信号测定,实现可视化的快速检测(Zetsche et al.,2015)。由于RPA技术具有对样品制备要求宽松、反应温度低(25~42℃)、冻干试剂可商业化供应等优势,目前,已成为核酸靶基因快速、特异、高效检测鉴定的重要工具。

    近年来开发的CRISPR-Cas免疫系统与RPA结合,实现了DNA/RNA的快速检测,为入侵害虫快速检测鉴定提供了新方法(Chen et al.,2018)。CRISPR-Cas是一种强大的基因编辑技术,能够识别并切割外来DNA,与RPA技术相结合,通过等温扩增后,可以放大目标核酸序列,从而提高检测灵敏度(Shashank et al.,2024)。如,Lewald等(2023)靶向COI基因开发了番茄潜叶蛾RPA-CRISPR-Cas12a等温检测技术。该方法无需使用热循环仪,在37℃反应条件下只需1.5 h,即可通过紫外线光源或手机摄像头等观察检测结果,基因组DNA的检测极限达0.10 ng/µL,但其检测灵敏度相较qPCR检测技术低了10倍(Gootenberg et al.,2017;Li et al.,2018)。又如,Shashank等(2024)设计了靶向番茄潜叶蛾、番茄茎麦蛾和山黄蝶Scrobipalpa atriplicella的多靶标一管式RPA-CRISPR-Cas12a检测技术,以DNA溶液为模版,在同一反应管内即可完成CO I基因片段的扩增和Cas12a的切割反应,将检测时长缩短至1 h之内,DNA最低检测限达3.00 fg/µL,完全可用于番茄潜叶蛾的检测鉴定。然而,RPA检测技术反应过程中容易形成气溶胶污染,导致结果时有假阳性出现,且单个样本检测成本较高(周洁等,2024)。

    近年来,相继报道了重组酶介导等温核酸扩增技术(RAA)(Song et al.,2018)、多酶恒温快速扩增技术(Coronaviruses Are Lipid-enveloped,MIRA)等多种类似于RPA的恒温扩增技术(Yiling et al.,2022;Heng et al.,2023)。这些技术通过使用来源更广泛的细菌或真菌重组酶,并研发了靶向DNA和RNA等不同类型核酸靶基因检测的侧向层析试纸条(Lateral Flow Strip,LFS)(毛迎雪等,2024)。LFS是一种纸基生物传感器,广泛应用于快速检测领域。通过毛细作用将样本液体引导通过试纸上的多个功能区域,从而完成目标分子的检测,其中,LFS与RAA技术相结合的RAA-LFS检测技术,利用“双抗体夹心”原理,可以快速检测扩增产物并实现可视化(Wang et al.,2024)。RAA-LFS通过试纸条检测线的颜色变化或量子点荧光信号的读取,实现对靶标种核酸水平的定性或定量检测(Van et al.,1993;Koczula,2016;Feng et al.,2024;Kakka et al.,2024)。由于该技术具有设备便携、操作简便、结果精准等优势,RAA-LFS已在入侵害虫检测鉴定中展现了巨大潜力(Ye,2018;Boehringer,2022;Cao et al.,2024)。如,基于线粒体COI基因,Cao等(2024)建立了番茄潜叶蛾RAA-LFS田间可视化快速检测技术,无需基因组DNA核酸提取步骤,仅对样本进行简单研磨和常温下的裂解,即可使用裂解液对卵、幼虫(1~4龄)、蛹和成虫等不同虫态/幼虫龄期样品进行直接检测。该方法可以将番茄潜叶蛾与26种近似种区分开来,检测时长更是缩短至了25 min,检测灵敏度低至了32.00 fg/μL的靶基因,完全可以满足海关、口岸等相关部门以及基层植保植检人员对番茄潜叶蛾检测、监测和防控的迫切需求。然而,RAA检测成本(约30.00元/样本)相对较高,广泛应用尚需时日。

    2006年Hinton等提出了深度学习概念,且因其准确性和高效性广受关注(Hinton,2006)。随着对农业害虫防治需求的不断增长,计算机视觉与机器学习技术在害虫识别鉴定中的应用也日趋成熟,尤其是深度学习中的卷积神经网络法(Convolutional Neural Networks,CNN)表现出了较高的识别准确率(崔晓辰和雷一东,2024)。CNN的核心优势主要在于其具有自我学习机制,亦即,在机器学习、模式识别和图像处理过程中,特征提取从初始的一组测量数据开始,并建立旨在提供信息和非冗余的派生值(特征),对提取特征进行图像分类,无需依赖人工识别。该技术仅需对番茄潜叶蛾的为害植株与为害特征进行拍摄,并通过上传图像照片,经模型处理后,即可自动输出害虫的识别、分类及数量信息,显著提升检测识别效率(Singh et al.,2018)。在害虫入侵的早期阶段可快速有效地进行物种识别和鉴定,有助于及时采取相应的防控措施(Lecun et al.,2015;Rusk,2016;Zhu et al.,2022)。

    近年来,番茄潜叶蛾的图像识别成为深度学习领域的热门研究方向之一,研究内容多集中在基于图像数据集的模型开发与应用等方面。如,Fuentes团队使用CNN模型学习多种摄像设备现场捕获的5 000余张图像,通过图形处理器(Graphics Processing Unit,GPU)的硬件和软件系统对图像进行实时处理,可实现较高(超过80%)准确率的番茄潜叶蛾识别(Fuentes et al.,2017)。Lilian团队致力于研究外来番茄潜叶蛾识别技术,利用3种架构模型训练了包含健康和受侵染番茄叶片的2 145张图像数据集,结合CNN模型在番茄植株生长的早期阶段即能检测到番茄潜叶蛾,识别准确率高达91.9%(Lilian et al.,2020)。Loyani团队以5 235张图像进行模型训练,提出了一种基于CNN的识别模型,可以准确识别叶片上被番茄潜叶蛾侵染的区域,并获取番茄潜叶蛾的确切位置,检测精准性可达85%(Loyani et al.,2021)。Georgantopoulos团队采用CNN法建立番茄植株的多光谱数据集,实现了对番茄潜叶蛾和烟粉虱Bemisia tabaci的双靶标检测鉴定(Georgantopoulos et al.,2023)。Şahin团队(2023)以1 200张受害番茄叶片照片为靶标进行模型训练,实现了受害叶片分类以及对番茄潜叶蛾幼虫潜道的检测,识别准确率为80%。Uygun团队(2024)以在温室条件下获取的800张健康和受损番茄植株的图像创建原始数据集,提出了一种基于CNN的番茄受害植株识别模型,识别准确率达86.2%,可实现番茄潜叶蛾的早期检测诊断。

    不同研究团队在番茄潜叶蛾检测中多数采用了分类与检测两种方法,反映了深度学习在害虫识别与管理中的多样化应用。其中,Fuentes等(2017)和Lilian等(2020)的研究更侧重于分类,通过模型预测识别是否存在害虫侵染,并对危害程度进行评估,且无需精确定位;而Loyani等(2021)、Georgantopoulos等(2023)、Şahin等(2023)、Uygun等(2024)则更关注于检测模型,专注于害虫侵染部位的识别与定位,该类模型能准确地标识出受番茄潜叶蛾侵害的区域,为对靶防治提供了依据。但图像识别技术的鉴定准确性,尚有待进一步提高。

    随着番茄潜叶蛾检测技术的发展和对高效防控的需求,精准、便携、快速的检测鉴定技术/方法必将成为今后研发的主攻方向。如,基于恒温扩增技术的现场检测工具可实现对番茄潜叶蛾的田间实时鉴定,满足农业生产中现场快速响应的需求;与多重检测和高通量检测平台相结合,可进一步提升检测效率。此外,基于PCR扩增体系或高通量测序技术,构建同时识别多种害虫或病原物的检测诊断平台,并结合人工智能和大数据分析技术,亦将会显著提升对番茄潜叶蛾的检测监管覆盖范围和防控效率。基于人工智能(Artificial Intelligence,AI)的图像识别系统,不仅能实现自动检测监测,通过与大数据分析整合还能实现动态风险预警,为害虫防控提供决策依据,助推跨区/跨境贸易的快速检疫和提升前瞻性预警水平,保障农业生产的持续向好发展。

  • 表  1   用于番茄潜叶蛾检测鉴定的分子生物学技术

    Table  1   Molecular detection techniques for the identification of tomato leaf miner

    检测技术Techniques 靶标序列
    Target sequence
    靶标物种
    Target species
    参考文献
    References
    RAPD-PCR 核酸基因组Genomics 番茄潜叶蛾Tuta absoluta Bettaïbi et al.,2012
    DNA序列分析 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta 马琳等,2021
    SCAR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta 张桂芬等,2020
    SS-PCR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta 张桂芬等,2013
    qPCR 核苷酸基因组Genomics mtDNA CO I、核糖体rDNA ITS 番茄潜叶蛾Tuta absoluta(多靶标检测) Lewald et al.,2023
    ddPCR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta Zink et al.,2022
    LAMP 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta Yang et al.,2024
    RPA-CRISPR 核苷酸基因组Genomics mtDNA CO I 番茄潜叶蛾Tuta absoluta(多靶标检测) Lewald et al.,2023
    番茄潜叶蛾Tuta absoluta Shashank et al.,2024
    RAA-LFS 核苷酸基因组Genomics mtDNA CO Ⅰ 番茄潜叶蛾Tuta absoluta Cao et al.,2024
  • Acharya R, Barman AK, Sharma SR, et al. Biology, distribution, and management of invasive South American tomato leafminer, Tuta absoluta (Meyrick) (Lepidoptera; Gelechiidae), in Asia[J]. Archives of Insect Biochemistry and Physiology, 2023, 114(4): e22056.
    Agustí N, de Vicente MC, Gabarra R. Developing SCAR markers to study predation on Trialeurodes vaporariorum[J]. Insect Molecular Biology, 2000, 9(3): 263-268.
    Aigbedion-Atalor PO, Hill MP, Zalucki MP, et al. The South America tomato leafminer, Tuta absoluta (Lepidoptera: Gelechiidae), spreads its wings in Eastern Africa: Distribution and socioeconomic impacts[J]. Journal of Economic Entomology, 2019, 112(6): 2797-2807.
    Amiteye S. Basic concepts and methodologies of DNA marker systems in plant molecular breeding[J]. Heliyon, 2021, 7(10): e08093.
    Bajracharya ASR, Mainali RP, Bhat B, et al. The first record of South American tomato leaf miner, Tuta absoluta (Meyrick 1917) (Lepidoptera: Gelechiidae) in Nepal[J]. Journal of Entomology and Zoology Studies, 2016, 4(4): 1359-1363.
    Barrientos R, Apablaza J, Norero A, et al. Temperatura base y constante térmica de desarrollo de la polilla del tomate, Tuta absoluta (Lepidoptera: Gelechiidae)[J]. Ciencia e Investigacion Agraria (Chile), 1998, 25(3): 82469736.
    Becherer L, Borst N, Bakheit M, et al. Loop-mediated isothermal amplification (LAMP)-review and classification of methods for sequence-specific detection[J]. Analytical Methods, 2020, 12(6): 717-746.
    Bettaïbi A, Mezghani-Khemakhem M, Bouktila D, et al. Genetic variability of the tomato leaf miner (Tuta absoluta Meyrick; Lepidoptera: Gelechiidae), in Tunisia, inferred from RAPD-PCR[J]. Chilean Journal of Agricultural Research, 2012, 72(2): 212.
    Biondi A, Guedes RNC, Wan FH, et al. Ecology, worldwide spread, and management of the invasive South American tomato pinworm, Tuta absoluta: Past, present, and future[J]. Annual Review of Entomology, 2018, 63: 239-258.
    Boehringer HR, Farrell BJ. Lateral flow assays in infectious disease diagnosis[J]. Clinical Chemistry, 2022, 68(1): 52-58.
    Cao Y, Yan D, Zhou H, et al. Achieving precise dual detection: One-tube reverse transcription-recombinase aided amplification (RT-RAA) combined with lateral flow strip (LFS) assay for RNA and DNA target genes from pepper mild mottle virus and Colletotrichum species in crude plant samples[J]. Talanta, 2024, 281: 126908.
    Cao Y, Yao R, Wang Y, et al. Unlocking precision: Advancing rapid field molecular identification of Tuta absoluta across its life cycle using locked nucleic acid strategies[J]. Sensors and Actuators: B. Chemical, 2024, 416: 136059.
    Chen JS, Ma E, Harrington LB, et al. CRISPR-Cas12a target binding unleashes indiscriminate single-stranded DNase activity[J]. Science, 2018, 360(6387): 436-439.
    Cifuentes D, Chynoweth R, Bielza P. Genetic study of Mediterranean and South American populations of tomato leafminer Tuta absoluta (Povolny, 1994) (Lepidoptera: Gelechiidae) using ribosomal and mitochondrial markers[J]. Pest Management Science, 2011, 67(9): 1155-1162.
    Corro P, Metz M. Classification of Tuta absoluta (Meyrick, 1917) (Lepidoptera: Gelechiidae: Gelechiinae: Gnorimoschemini) based on cladistic analysis of morphology[J]. Proceedings of the Entomological Society of Washington, 2021, 123(1): 41-54.
    崔晓辰, 雷一东. 基于深度学习的林业害虫智能化检测方法研究进展[J]. 世界林业研究, 2024, 37(4): 53-57

    Cui XC, Lei YD. Research progress in deep-learning-based intelligent forest pest detection methods[J]. World Forestry Research, 2024, 37(4): 53-57.
    Desneux N, Luna MG, Guillemaud T, et al. The invasive South American tomato pinworm, Tuta absoluta, continues to spread in Afro-Eurasia and beyond: The new threat to tomato world production[J]. Journal of Pest Science, 2011, 84: 403-408.
    Desneux N, Wajnberg E, Wyckhuys KA, et al. Biological invasion of European tomato crops by Tuta absoluta: Ecology, geographic expansion and prospects for biological control[J]. Journal of Pest Science, 2010, 83: 197-215.
    Feng J, Lan H, Wu Z, et al. Novel integration of lateral flow strip and point-of-care isothermal amplification techniques for meat adulteration detection: A comprehensive review[J]. Trends in Food Science & Technology, 2024, 152: 104698.
    Fuentes A, Yoon S, Kim SC, et al. A robust deep-learning-based detector for real-time tomato plant diseases and pests recognition[J]. Sensors, 2017, 17(9): 2022.
    Georgantopoulos PS, Papadimitriou D, Constantinopoulos C, et al. A multispectral dataset for the detection of Tuta absoluta and Leveillula taurica in tomato plants[J]. Smart Agricultural Technology, 2023, 4: 100146.
    Gootenberg JS, Abudayyeh OO, Lee JW, et al. Nucleic acid detection with CRISPR-Cas13a/C2c2[J]. Science, 2017, 356(6336): 438-442.
    顾建锋, 方亦午, 马欣欣, 等. 松材线虫检测鉴定技术研究进展[J]. 植物检疫, 2023, 37(1): 1-6

    Gu JF, Fang YW, Ma XX, et al. Advances in detection and identification of Bursaphelenchus xylophilus[J]. Plant Quarantine, 2023, 37(1): 1-6.
    Guedes R, Roditakis E, Campos M, et al. Insecticide resistance in the tomato pinworm Tuta absoluta: Patterns, spread, mechanisms, management and outlook[J]. Journal of Pest Science, 2019, 92(4): 1329-1342.
    Heid CA, Stevens J, Livak KJ, et al. Real time quantitative PCR[J]. Genome Research, 1996, 6(10): 986-994.
    Heng P, Shi B, Li D, et al. Rapid visualization molecular fluorescence detection of methicillin‐resistant Staphylococcus aureus using the multiplex MIRA‐qPCR method[J]. Biotechnology Journal, 2023, 18(12): 2300200.
    Higuchi R, Dollinger G, Walsh PS, et al. Simultaneous amplification and detection of specific DNA sequences[J]. Biotechnology, 1992, 10(4): 413-417.
    Hillis DM, Dixon MT. Ribosomal DNA: Molecular evolution and phylogenetic inference[J]. The Quarterly Review of Biology, 1991, 66(4): 411-453.
    Hindson CM, Chevillet JR, Briggs HA, et al. Absolute quantification by droplet digital PCR versus analog real-time PCR[J]. Nature Methods, 2013, 10(10): 1003-1005.
    Hinton GE, Salakhutdinov RR. Reducing the dimensionality of data with neural networks[J]. Science, 2006, 313(5786): 504-507.
    Hossain M, Mian M, Muniappan R. First record of Tuta absoluta (Lepidoptera: Gelechiidae) from Bangladesh[J]. Journal of Agricultural and Urban Entomology, 2016, 32(1): 101-105.
    Ishtiaq M, Sadique M, Faried N, et al. First record of tomato leafminer, Tuta absoluta (Meyrick 1917) (Lepidoptera: Gelechiidae) from southern part of Punjab, Pakistan[J]. Journal of Animal & Plant Sciences, 2020, 30(6): 2309-8694.
    Kakkar S, Gupta P, Yadav SPS, et al. Lateral flow assays: Progress and evolution of recent trends in point-of-care applications[J]. Materials Today Bio., 2024, 28: 101188.
    Kaltenboeck B, Wang C. Advances in real-time PCR: Application to clinical laboratory diagnostics[J]. Advances in Clinical Chemistry, 2005, 40: 219-259.
    Kb M. Specific synthesis of DNA in vitro via a polymerase-catelyzed chain reaction[J]. Methods in Enzymology, 1987, 155: 335-350.
    Kılıç T. First record of Tuta absoluta in Turkey[J]. Phytoparasitica, 2010, 38(3): 243-244.
    Koczula KM, Gallotta A. Lateral flow assays[J]. Essays in Biochemistry, 2016, 60(1): 111-120.
    Lecun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 2015, 521(7553): 436-444.
    Lee MH, Jeong D, Lee GS, et al. First report of Phthorimaea absoluta (Lepidoptera: Gelechiidae) in Korea[J]. Journal of Integrated Pest Management, 2024, 15(1): 36.
    Lei S, Chen S, Zhong Q. Digital PCR for accurate quantification of pathogens: Principles, applications, challenges and future prospects[J]. International Journal of Biological Macromolecules, 2021, 184: 750-759.
    Lewald KM, Song W, Eweis LD, et al. Probe-based quantitative PCR and RPA-Cas12a molecular diagnostics for detection of the tomato pest Phthorimaea absoluta (Lepidoptera: Gelechiidae)[J]. Journal of Economic Entomology, 2023, 116(3): 993-1001.
    李安娟, 柳丽君. 检疫性蛾类鉴定方法和标准的研究进展[J]. 植物保护学报, 2023, 50(6): 1397-1410

    Li AJ, Liu LJ. Research progress in identification methods and criteria for quarantine moths[J]. Journal of Plant Protection, 2023, 50(6): 1397-1410.
    Li SY, Cheng QX, Wang JM, et al. CRISPR-Cas12a-assisted nucleic acid detection[J]. Cell Discovery, 2018, 4(1): 20.
    李晓维, 易松望, 陈利民, 等. 番茄潜叶蛾行为调控技术研究进展[J]. 昆虫学报, 2023, 66(6): 835-848

    Li XW, Yi SW, Chen LM, et al. Research progress of behavioral manipulation techniques of Tuta absoluta[J]. Acta Entomologica Sinica, 2023, 66(6): 835-848.
    Lilian M, Denis R, Mgaya R, et al. Early identification of Tuta absoluta in tomato plants using deep learning[J]. Scientific African, 2020, 10: e00590.
    Lin L, Zheng Y, Huang H, et al. A visual method to detect meat adulteration by recombinase polymerase amplification combined with lateral flow dipstick[J]. Food Chemistry, 2021, 354: 129526.
    Liu DN, Wu HP, Zhou GH. Research progress of visual detection in rapid on-site detection of pathogen nucleic acid[J]. Yi Chuan, 2023, 45(4): 306-323.
    Loyani LK, Bradshaw K, Machuve D. Segmentation of Tuta sbsoluta's damage on tomato plants: A computer vision approach[J]. Applied Artificial Intelligence, 2021, 35(14): 1107-1127.
    马琳, 李晓维, 郭文超, 等. 基于CO Ⅰ基因的新入侵害虫番茄潜叶蛾遗传多样性分析[J]. 应用昆虫学报, 2021, 58(6): 1356-1364

    Ma L, Li XW, Guo WC, et al. Genetic diversity analysis of the newly invasive pest Tuta absoluta based on the CO Ⅰ gene[J]. Chinese Journal of Applied Entomology, 2021, 58(6): 1356-1364.
    毛迎雪, 刘蒙达, 张皓博, 等. 重组酶介导等温扩增技术(RAA)在病原微生物检测中的应用进展[J]. 中国动物检疫, 2024, 41(1): 60-66

    Mao YX, Liu MD, Zhang HB, et al. Advances on application of recombinase aided amplification in detection of pathogenic microorganisms[J]. China Animal Health Inspection, 2024, 41(1): 60-66.
    Mori Y, Kitao M, Tomita N, et al. Real-time turbidimetry of LAMP reaction for quantifying template DNA[J]. Journal of Biochemical and Biophysical Methods, 2004, 59(2): 145-157.
    Notomi T, Okayama H, Masubuchi H, et al. Loop-mediated isothermal amplification of DNA[J]. Nucleic Acids Research, 2000, 28(12): e63-e63.
    Pandey M, Bhattarai N, Pandey P, et al. A review on biology and possible management strategies of tomato leaf miner, Tuta absoluta (Meyrick), Lepidoptera: Gelechiidae in Nepal[J]. Heliyon, 2023, 9(6): e16474.
    Paran I, Michelmore RW. Development of reliable PCR-based markers linked to downy mildew resistance genes in lettuce[J]. Theoretical and Applied Genetics, 1993, 85(8): 985-993.
    Parida M, Sannarangaiah S, Dash PK, et al. Loop mediated isothermal amplification (LAMP): A new generation of innovative gene amplification technique; perspectives in clinical diagnosis of infectious diseases[J]. Reviews in Medical Virolog, 2008, 18(6): 407-421.
    Piepenburg O, Williams CH, Stemple DL, et al. DNA detection using recombination proteins[J]. PLoS Biology, 2006, 4(7): e204.
    Povolný D. Gnorimoschemini of southern South America Ⅵ: Identification keys, checklist of Neotropical taxa and general considerations (Insecta, Lepidoptera, Gelechiidae)[J]. Steenstrupia, 1994, 20(1): 1-42.
    Power E. RAPD typing in microbiology-a technical review[J]. Journal of Hospital Infection, 1996, 34(4): 247-265.
    Rusk N. Deep learning[J]. Nature Methods, 2016, 13(1): 35-35.
    Şahin YS, Erdinç A, Bütüner AK, et al. Detection of Tuta absoluta larvae and their damages in tomatoes with deep learning-based algorithm[J]. International Journal of Next-Generation Computing, 2023, 14(3): 555-565.
    Santana P, Kumar L, Da Silva R, et al. Global geographic distribution of Tuta absoluta as affected by climate change[J]. Journal of Pest Science, 2019, 92: 1373-1385.
    Shashank PR, Parker BM, Rananaware SR, et al. CRISPR-based diagnostics detects invasive insect pests[J]. Molecular Ecology Resources, 2024, 24(1): e13881.
    Singh AK, Ganapathysubramanian B, Sarkar S, et al. Deep learning for plant stress phenotyping: trends and future perspectives[J]. Trends in Plant Science, 2018, 23(10): 883-898.
    Soares MA, Campos MR. Phthorimaea absoluta (tomato leafminer)[M]. CABI Compendium, 2020.
    Song Z, Ting L, Kun Y, et al. Establishment of a recombinase-aided isothermal amplification technique to detect Schistosoma japonicum specific gene fragments[J]. Chinese Journal of Schistosomiasis Control, 2018, 30(3): 273.
    Sridhar V, Chakravarthy A, Asokan R, et al. New record of the invasive South American tomato leaf miner, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) in India[J]. Pest Management in Horticultural Ecosystems, 2014, 20(2): 148-154.
    Sun X, Lu G, Sun R, et al. An accurate, efficient, and economical identification technology for black twig borer based on species-specific cytochrome C oxidase subunit Ⅰ PCR assay[J]. Journal of Economic Entomology, 2023, 116(4): 1372-1378.
    Tabuloc CA, Lewald KM, Conner WR, et al. Sequencing of Tuta absoluta genome to develop SNP genotyping assays for species identification[J]. Journal of Pest Science, 2019, 92: 1397-1407.
    Tamura K, Stecher G, Peterson D, et al. MEGA6: molecular evolutionary genetics analysis version 6.0[J]. Molecular Biology and Evolution, 2013, 30(12): 2725-2729.
    Taylor SC, Laperriere G, Germain H. Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: From variable nonsense to publication quality data[J]. Scientific Reports, 2017, 7(1): 2409.
    Taylor SC, Nadeau K, Abbasi M, et al. The ultimate qPCR experiment: Producing publication quality, reproducible data the first time[J]. Trends in Biotechnology, 2019, 37(7): 761-774.
    Tomita N, Mori Y, Kanda H, et al. Loop-mediated isothermal amplification (LAMP) of gene sequences and simple visual detection of products[J]. Nature Protocols, 2008, 3(5): 877-882.
    Uygun T, Ozguven MM. Determination of tomato leafminer: Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) damage on tomato using deep learning instance segmentation method[J]. European Food Research and Technology, 2024, 250(6): 1837-1852.
    Van Amerongen A, Wichers J, Berendsen L, et al. Colloidal carbon particles as a new label for rapid immunochemical test methods: Quantitative computer image analysis of results[J]. Journal of Biotechnology, 1993, 30(2): 185-195.
    Vrijenhoek R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit Ⅰ from diverse metazoan invertebrates[J]. Molecular Marine Biology and Biotechnology, 1994, 3(5): 294-299.
    Wang S, Zhou Z, Cao M, et al. A comprehensive review of aptamer screening and application for lateral flow strip: Current status and future perspectives[J]. Talanta, 2024, 275: 126181.
    王旭, 彭德良, 葛建军. 马铃薯孢囊线虫分子检测技术研究进展[J]. 植物检疫, 2022, 36(6): 1-9

    Wang X, Peng DL, Ge JJ. Research progress on molecular detection technology of potato cyst nematode[J]. Plant Quarantine, 2022, 36(6): 1-9.
    王雅娜, 于艳雪, 田茜, 等. 基于RPA-CRISPR/Cas12a的美国白蛾可视化快速检测新方法[J]. 环境昆虫学报, 2024, 46(5): 1051-1058 doi: 10.3969/j.issn.1674-0858.2024.05.04

    Wang YN, Yu YX, Tian Q, et al. New and rapid visual detection assay for Hyphantria cunea Drury based on recombinase polymerase amplification and CRISPR/Cas12a[J]. Journal of Environmental Entomology, 2024, 46(5): 1051-1058. doi: 10.3969/j.issn.1674-0858.2024.05.04
    Wong YP, Othman S, Lau YL, et al. Loop‐mediated isothermal amplification (LAMP): A versatile technique for detection of micro‐organisms[J]. Journal of Applied Microbiology, 2018, 124(3): 626-643.
    Yang LF, Liu YG, Tao YL, et al. Development of an on-site diagnostic LAMP assay for rapid differentiation of the invasive pest Phthorimaea absoluta (Meyrick) using insect tissues[J]. Pest Management Science, 2024, 80(8): 4069-4073.
    Ye H, Xia X. Enhancing the sensitivity of colorimetric lateral flow assay (CLFA) through signal amplification techniques[J]. Journal of Materials Chemistry B, 2018, 6(44): 7102-7111.
    尹艳琼, 郑丽萍, 李峰奇, 等. 云南弥渡县番茄潜叶蛾的发生情况及田间防治效果[J]. 环境昆虫学报, 2021, 43(3): 559-566 doi: 10.3969/j.issn.1674-0858.2021.03.4

    Yi YQ, Zheng LP, Li QF, et al. Occurrence and control of Tuta absoluta in midu county, Yunnan Province[J]. Journal of Environmental Entomology, 2021, 43(3): 559-566. doi: 10.3969/j.issn.1674-0858.2021.03.4
    Yiling F, Zhen F, Bo J, et al. Multi-enzyme isothermal rapid amplification assay for the detection of Escherichia coli O157: H7[J]. Shanghai Journal of Preventive Medicine, 2022, 34(6): 511-518.
    Yule S, Htain NN, Oo AK, et al. Occurrence of the south American tomato leaf miner, Tuta absoluta (Meyrick) in Southern Shan, Myanmar[J]. Insects, 2021, 12(11): 962.
    Zetsche B, Gootenberg JS, Abudayyeh OO, et al. Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system[J]. Cell, 2015, 163(3): 759-771.
    张桂芬, 毕思言, 张毅波, 等. 南美番茄潜叶蛾SCAR引物及其应用: ZL202011019496.9[P]. 2020-09-25(2021-12-24)

    Zhang GF, Bi SY, Zang YB, et al. SCAR primers for Tuta absoluta and their applications: ZL202011019496.9[P]. 2020-09-25(2021-12-24).
    张桂芬, 刘万学, 郭建洋, 等. 重大潜在入侵害虫番茄潜叶蛾的SS-COI快速检测技术[J]. 生物安全学报, 2013, 22(2): 80-85

    Zhang GF, Liu WX, Guo JY, et al. Species-specific COI primers for rapid identification of Tuta absoluta, a significant, potential alien species[J]. Journal of Biosafety, 2013, 22(2): 80-85.
    张桂芬, 刘万学, 郭建英, 等. 美洲斑潜蝇SS-PCR检测技术研究[J]. 生物安全学报, 2012, 21(1): 74-78

    Zhang GF, Liu WX, Guo JY, et al. Species-specific PCR primers for identification of Liriomyza sativae[J]. Journal of Biosafety, 2012, 21(1): 74-78.
    张桂芬, 马德英, 刘万学, 等. 中国新发现外来入侵害虫——南美番茄潜叶蛾(鳞翅目: 麦蛾科)[J]. 生物安全学报, 2019, 28(3): 200-203

    Zhang GF, Ma DY, Liu WX, et al. The arrival of Tuta absoluta (Lepidoptera: Gelechiidae), in China[J]. Journal of Biosafety, 2019, 28(3): 200-203.
    Zhang GF, Ma DY, Wang YS, et al. First report of the South American tomato leafminer, Tuta absoluta (Meyrick), in China[J]. Journal of Integrative Agriculture, 2020, 19(7): 1912-1917.
    张桂芬, 张毅波, 冼晓青, 等. 新发重大农业入侵害虫番茄潜叶蛾的发生为害与防控对策[J]. 植物保护, 2022, 48. (4): 51-58

    Zhang GF, Zhang YB, Xian XQ, et al. Damage of an important and newly invaded agricultural pest, Tuta absoluta, and its prevention and management measures[J]. Plant Protection, 2022, 48(4): 51-58.
    Zhang Z, Schwartz S, Wagner L, et al. A greedy algorithm for aligning DNA sequences[J]. Journal of Computational Biology, 2000, 7(1-2): 203-214.
    周洁, 黄夏宁, 卢玲敏, 等. 基于恒温扩增技术的病原体快速检测研究进展[J]. 中国口岸科学技术, 2024, 6(S2): 19-27

    Zhou J, Huang XN, Lu LM, et al. Research progress on pathogen rapid detection based on isothermal amplification technology[J]. China Port Science and Technology, 2024, 6(S2): 19-27.
    Zhu Y, Wang M, Yin X, et al. Deep learning in diverse intelligent sensor based systems[J]. Sensors, 2022, 23(1): 62.
    Zink FA, Tembrock LR, Timm AE, et al. A droplet digital PCR (ddPCR) assay to detect Phthorimaea absoluta (Lepidoptera: Gelechiidae) in bulk trap samples[J]. Journal of Economic Entomology, 2022, 115(6): 2125-2129.
    Zink FA, Tembrock LR, Timm AE, et al. A real-time PCR assay for rapid identification of Tuta absoluta (Lepidoptera: Gelechiidae)[J]. Journal of Economic Entomology, 2020, 113(3): 1479-1485.
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  • 收稿日期:  2024-11-30
  • 修回日期:  2024-12-09
  • 接受日期:  2024-12-10

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