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肯尼亚五种入侵卷蛾科害虫基于线粒体 COI 条码区的侵害水平和分子鉴定。

Infestation Levels and Molecular Identification Based on Mitochondrial COI Barcode Region of Five Invasive Gelechiidae Pest Species in Kenya.

机构信息

Plant Health Theme, International Centre of Insect Physiology and Ecology (icipe), GPO, Nairobi, Kenya.

Department of Biological Sciences, University of Embu, Embu, Kenya.

出版信息

J Econ Entomol. 2019 Mar 21;112(2):872-882. doi: 10.1093/jee/toy357.

Abstract

Invasive Gelechiidae pest species, namely Tuta absoluta, Phthorimaea operculella, Aproaerema simplixella, Sitotroga cerealella, and Pectinophora gossypiella are among the major constraints hampering agricultural economy in Kenya. Infestation levels were determined on respective host crops sampled from different localities and P. operculella recorded the highest infestation of 68.00 ± 4.92% on stored potato. Aproaerema simplixella and T. absoluta accounted for 61.33 ± 5.35% and 51.56 ± 5.22% maximal infestation on groundnuts and tomato leaves, respectively. Stored maize was significantly infested by S. cerealella (54.33 ± 5.31%) while no infestation was observed on the freshly harvested grains. Infestation on open bolls by P. gossypiella was relatively low (6.11 ± 3.46%) compared to Anatrachyntis simplex (45.67 ± 7.84%) that emerged as the key pest of cotton. The species were discriminated based on sequence similarities, evolutionary divergences, and phylogenetic analyses. A 658-bp fragment of mitochondrial cytochrome c oxidase subunit I (COI) gene was obtained from 302 specimens. Generally, genetic variations were low within and between Gelechiid populations, with an average of 0.02% and all intraspecific divergences were less than 2% except for S. cerealella. The Gelechiids data set generated eight Barcode Index Numbers (BINs), five of which were concordant and three belonging to S. cerealella were singleton. All species were separated into distinct clusters on a maximum likelihood tree. Data on infestation levels will be useful in defining the pest status of these Gelechiids in Kenya. DNA barcoding is also presented as a valuable tool to complement traditional taxonomy for rapid and accurate identification of these species of agronomic interest.

摘要

入侵的卷叶蛾科害虫,如桃蚜、小菜蛾、棉铃虫、玉米螟和棉红铃虫,是肯尼亚农业经济的主要制约因素之一。在不同地点采集的各自寄主作物上确定了虫害水平,小菜蛾在储存的马铃薯上的最高感染率为 68.00 ± 4.92%。Aproaerema simplixella 和 T. absoluta 在花生叶和番茄叶上的最大感染率分别为 61.33 ± 5.35%和 51.56 ± 5.22%。储存的玉米受到玉米螟的严重感染(54.33 ± 5.31%),而新收获的谷物则没有感染。与 Anathrachyntis simplex(45.67 ± 7.84%)相比,桃蚜在开放棉铃中的感染相对较低(6.11 ± 3.46%),Anathrachyntis simplex 是棉花的主要害虫。这些物种是基于序列相似性、进化分歧和系统发育分析来区分的。从 302 个标本中获得了线粒体细胞色素 c 氧化酶亚基 I(COI)基因的 658-bp 片段。一般来说,卷叶蛾种群内和种群间的遗传变异较低,平均为 0.02%,除了 S. cerealella 外,所有种内分歧都小于 2%。卷叶蛾数据集生成了 8 个条形码索引编号(BIN),其中 5 个是一致的,3 个属于 S. cerealella 的是单峰。所有物种都在最大似然树上分为不同的聚类。这些关于感染水平的数据将有助于确定这些卷叶蛾在肯尼亚的害虫地位。DNA 条形码也被证明是一种有价值的工具,可以补充传统的分类学,用于快速准确地识别这些具有农业重要性的物种。

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