Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-26T03:46:57.708Z Has data issue: false hasContentIssue false

An optical method for automatic classification and recording of a suction trap catch

Published online by Cambridge University Press:  10 July 2009

S.E. Hobbs*
Affiliation:
Cranfield Institute of Technology, UK
G. Hodges
Affiliation:
Cranfield Institute of Technology, UK
*
Dr Stephen Hobbs, Environment and Space Group, Department of Aerospace Science, College of Aeronautics, Cranfield Institute of Technology, Cranfield, Bedford MK43 OAL, UK.

Abstract

A simple optical method for automatic recording and classification of a suction trap catch is described. The insects are illuminated against a dark background as they pass through a detection volume, and the amount of scattered light is used to measure insect size. The design centres on the detection volume, which is a volume through which the insects are made to pass, and within which they may be detected. The design is approached in four stages: 1. Delivery of insects to the detection volume. 2. Illumination of the detection volume. 3. Collection and detection of scattered light. 4. Signal analysis. The analysis could also be applied to related techniques. Results with a prototype demonstrate that classification into broad size categories is straight-forward (e.g. approximately three classes spanning body lengths of 2–7 mm), despite uncertainties of insect reflectivity, aspect and trajectory. Applications of the method are discussed, along with a brief mention of alternative techniques.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1993

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aldridge, H.D.J.N. (1991) Vertical flight in the greater horsehoe bat Rhinolophus ferrumequinum. Journal of Experimental Biology 157, 183204.CrossRefGoogle Scholar
Burt, P.J.A. (1992) An investigation into the influence of the wind on the distribution of insects at low levels in the atmosphere. PhD thesis, Cranfield Institute of Technology, UK.Google Scholar
Hedges, T.J. (1988) The temporal distribution of botanical and other coarse aerosol particles in the atmosphere close to the ground. PhD thesis, Cranfield Institute of Technology, UK.Google Scholar
Hodges, G. (1989) An investigation into categorizing insects using information from an optical remote sensing device. MSc thesis, Cranfield Institute of Technology, UK.Google Scholar
Kraszewski, A.W., Nelson, S.O. & You, T.S. (1989) Sensing dielectric properties of arbitrarily shaped biological objects with a microwave resonator. Paper D-7, pp. 187190, in Proceedings of the 1989 IEEE MTT-S International Microwave Symposium, Volume 1, held13–15 June 1989,Long Beach, California, USA.(Institution of Electrical and Electronics Engineers, IEEE catalog no. 89CH2725–0).Google Scholar
Sapirstein, H.D., Neuman, M., Wright, E.H., Shwedyk, E. & Bushuk, W. (1987) An instrumental system for cereal grain classification using digital image analysis. Journal of Cereal Science 6, 313.CrossRefGoogle Scholar
Tillet, K.D., Onyango, C.M., Davis, J.A. & Marchant, J.A. (1989) Image analysis for biological objects. pp. 207211 in Proceedings of the 3rd International Conference on Image Analysis and its Applications, held atWarwick University,July 1989.(Institute of Electrical Engineers conference publication no. 307).Google Scholar