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Comparative Morphogenesis of Antennal Sensilla Between the Leptocybe invasa and Ophelimus maskelli (Hymenoptera: Eulophidae) and its relationship to their vital Capacity.
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- Author(s): Hamdy, Nagwan M.1 ; Emam, Azza K.1
- Source:
Egyptian Academic Journal of Biological Sciences. A, Entomology. Sep2022, Vol. 15 Issue 3, p123-136. 14p.
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- Abstract:
Insects have several sensory (sensilla) structures on their antennae, which are crucial for the concept of environmental cues as well as host recognition and positioning strategies. Sensilla thus have a significant impact on how parasite hosts locate, classify, and maybe accept a host. Based on the types, numbers, and locations of sensory organs, it is possible to deduce how they perform certain tasks. The examined biological variables are listed. The purpose of this work was to describe the external sensilla found on the antennae of Ophelimus Maskelli (Ashmead) and Leptocype Invasa (Fisher and La Salle) (Hymenoptera: Chalcidoidea: Eulophidae). In Egypt, Eucalyptus camaldulensis was primarily plagued by these two inducer insects. The sensilla have been labelled according to their distribution, size, and shape. May also use scanning electron microscopy to reveal sensory organs. On the antennae of L. invasa, sensilla were dispersed in six different types, while on the antennae of O. maskelli, they were placed in nine different types. According to this study, O. maskelli had more sensilla overall than L. invasa; along the antenna, O. maskelli had 100 sensilla compared to L. invasa more than 37 sensilla. The results from the measured biological characteristics were explained by the qualitative and quantitative differences in the sensilla types of the two species on the antenna, favouring O. Maskelli. The results tended to show that O. Maskelli was the strongest rival that could displace L. invasa. [ABSTRACT FROM AUTHOR]
- Abstract:
Copyright of Egyptian Academic Journal of Biological Sciences. A, Entomology is the property of Egyptian Academic Journal of Biological Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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