Literature DB >> 29659900

Monitoring of the Cowpea Bruchid, Callosobruchus maculatus (Coleoptera: Bruchidae), Feeding Activity in Cowpea Seeds: Advances in Sensing Technologies Reveals New Insights.

James A Bittner1, Susan Balfe2, Barry R Pittendrigh2, John S Popovics1.   

Abstract

Cowpea provides a significant source of protein for over 200 million people in Sub-Saharan Africa. The cowpea bruchid, Callosobruchus maculatus (F) (Coleoptera: Bruchidae), is a major pest of cowpea as the larval stage attacks stored cowpea grains, causing postharvest loss. Cowpea bruchid larvae spend all their time feeding within the cowpea seed. Past research findings, published over 25 yr ago, have shown that feeding activity of several bruchids within a cowpea seed emit mechanical vibrations within the frequency range 5-75 kHz. This work led to the development of monitoring technologies that are both important for basic research and practical application. Here, we use newer and significantly improved technologies to re-explore the nature of the vibration signals produced by an individual C. maculatus, when it feeds in cowpea seeds. Utilizing broadband frequency sensing, individual fourth-instar bruchid larvae feeding activities (vibration events) were recorded to identify specific key emission frequencies. Verification of recorded events and association to actual feeding activities was achieved through mass measurements over 24 h for a series of replicates. The measurements identified variable peak event emission frequencies across the replicate sample set ranging in frequency from 16.4 to 26.5 kHz. A positive correlation between the number of events recorded and the measured mass loss of the cowpea seed was observed. The procedure and verification reported in this work provide an improved basis for laboratory-based monitoring of single larval feeding. From the rich dataset captured, additional analysis can be carried out to identify new key variables of hidden bruchid larval activity.

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Year:  2018        PMID: 29659900     DOI: 10.1093/jee/toy086

Source DB:  PubMed          Journal:  J Econ Entomol        ISSN: 0022-0493            Impact factor:   2.381


  1 in total

1.  Automated Applications of Acoustics for Stored Product Insect Detection, Monitoring, and Management.

Authors:  Richard Mankin; David Hagstrum; Min Guo; Panagiotis Eliopoulos; Anastasia Njoroge
Journal:  Insects       Date:  2021-03-19       Impact factor: 2.769

  1 in total

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