期刊
BIOSYSTEMS ENGINEERING
卷 153, 期 -, 页码 82-88出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.biosystemseng.2016.11.001
关键词
Pest counting; Sticky trap; Whitefly; Thrips; Two-dimensional Fourier transform
资金
- Chinese-German Centre for Scientific Promotion (Chinesisches-Deutsches Zentrum fuer Wissenschaftsfoerderung) under project of Sib-German Research Group [GZ1272]
- China High-end Foreign Experts Recruitment Program [GDT20141100003]
Although sticky traps are reliable indicators of pest population dynamics but pest counting by humans is time-consuming and menial labour. A novel smart vision algorithm based on two-dimensional Fourier transform (2DFT) spectrum is presented. Rather than directly counting the pests captured on the traps, the novel concept is to treat trapped pests as noise in a two-dimensional (2D) image with 2DFT serving as a specific noise collector. The research objectives included comparing human and 2DFT counting in two proof-of principle tests: (i) simulated pests with various quantities and distributions arrayed on two series of templates using both ordered and random patterns; (ii) sweet potato white flies [Bemisia tabaci (Gennadius), Hemiptera: Aleyrodidae] on yellow sticky traps (YSTs) and western flower thrips [Frankliniella occidentalis (Pergande), Thysanoptera: Thripidae] on blue sticky traps (BSTs). Tests of simulated pests (2-512) on eight templates verified that the 2DFT-based index provides accurate estimates of pests captured on the traps (R-2 = 1), independent of pest distribution pattern. High correlations were obtained from count results of whiteflies on 34 YSTs (R-2 = 0.9994) and thrips on 33 BSTs (R-2 = 0.9989). Measurement errors were addressed. (c) 2016 IAgrE. Published by Elsevier Ltd. All rights reserved.
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