Portable, In-field, Multispectral Imaging Sensor for Real-time Detection of Insect Viral-Vectors

Bruce Grieve; Charles Veys; Dingle Jose; John Colvin; Joachim Nwezeobi

doi:10.1109/ICSENS.2017.8234206

Portable, In-field, Multispectral Imaging Sensor for Real-time Detection of Insect Viral-Vectors

Bruce Grieve
, Charles Veys
, Dingle Jose
, John Colvin
, Joachim Nwezeobi

University of Greenwich

Research output: Contribution to conference › Paper › peer-review

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Abstract

The paper introduces a multispectral imaging system and data-processing approach for speciation of the insect viral vectors (whitefly) responsible for the transmission of Mosaic and Brown Streak viruses in Sub-Saharan African cassava. The trial results for four species of whitefly, on two plant leaf types (cassava & aubergine), are reported as well as the methodology applied. This indicates that a correct classification could be achieved in 85-95% of cases. The engineering design for an infield, handheld, variant of the technology is discussed alongside the learning gained from this initial study.

Original language	English
Pages	990-992
Number of pages	3
DOIs	https://doi.org/10.1109/ICSENS.2017.8234206
Publication status	Published - 6 Nov 2017
Event	IEEE Sensors 2017 Conference - SEC, Glasgow, United Kingdom Duration: 29 Oct 2017 → 1 Nov 2017

Conference

Conference	IEEE Sensors 2017 Conference
Country/Territory	United Kingdom
City	Glasgow
Period	29/10/17 → 1/11/17

Keywords

multispectral
MSI
hyperspectral
real-time
imaging
virus
brown streak disease
mosaic virus
insect
cassava
Bemisia tabaci
begomoviruses

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10.1109/ICSENS.2017.8234206

IEEE-SENSORS-2017_Proceedings_p990-992Final published version, 1.05 MB

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title = "Portable, In-field, Multispectral Imaging Sensor for Real-time Detection of Insect Viral-Vectors",

abstract = "The paper introduces a multispectral imaging system and data-processing approach for speciation of the insect viral vectors (whitefly) responsible for the transmission of Mosaic and Brown Streak viruses in Sub-Saharan African cassava. The trial results for four species of whitefly, on two plant leaf types (cassava \& aubergine), are reported as well as the methodology applied. This indicates that a correct classification could be achieved in 85-95\% of cases. The engineering design for an infield, handheld, variant of the technology is discussed alongside the learning gained from this initial study.",

keywords = "multispectral, MSI, hyperspectral, real-time, imaging, virus, brown streak disease, mosaic virus, insect, cassava, Bemisia tabaci, begomoviruses",

author = "Bruce Grieve and Charles Veys and Dingle Jose and John Colvin and Joachim Nwezeobi",

year = "2017",

month = nov,

day = "6",

doi = "10.1109/ICSENS.2017.8234206",

language = "English",

pages = "990--992",

note = "IEEE Sensors 2017 Conference ; Conference date: 29-10-2017 Through 01-11-2017",

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AU - Grieve, Bruce

AU - Veys, Charles

AU - Jose, Dingle

AU - Colvin, John

AU - Nwezeobi, Joachim

PY - 2017/11/6

Y1 - 2017/11/6

N2 - The paper introduces a multispectral imaging system and data-processing approach for speciation of the insect viral vectors (whitefly) responsible for the transmission of Mosaic and Brown Streak viruses in Sub-Saharan African cassava. The trial results for four species of whitefly, on two plant leaf types (cassava & aubergine), are reported as well as the methodology applied. This indicates that a correct classification could be achieved in 85-95% of cases. The engineering design for an infield, handheld, variant of the technology is discussed alongside the learning gained from this initial study.

AB - The paper introduces a multispectral imaging system and data-processing approach for speciation of the insect viral vectors (whitefly) responsible for the transmission of Mosaic and Brown Streak viruses in Sub-Saharan African cassava. The trial results for four species of whitefly, on two plant leaf types (cassava & aubergine), are reported as well as the methodology applied. This indicates that a correct classification could be achieved in 85-95% of cases. The engineering design for an infield, handheld, variant of the technology is discussed alongside the learning gained from this initial study.

KW - multispectral

KW - MSI

KW - hyperspectral

KW - real-time

KW - imaging

KW - virus

KW - brown streak disease

KW - mosaic virus

KW - insect

KW - cassava

KW - Bemisia tabaci

KW - begomoviruses

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DO - 10.1109/ICSENS.2017.8234206

M3 - Paper

SP - 990

EP - 992

T2 - IEEE Sensors 2017 Conference

Y2 - 29 October 2017 through 1 November 2017

ER -

Portable, In-field, Multispectral Imaging Sensor for Real-time Detection of Insect Viral-Vectors

Abstract

Conference

Keywords

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