Literature DB >> 19689905

Quantitative, nondestructive assessment of beech scale (Hemiptera: Cryptococcidae) density using digital image analysis of wax masses.

Stephen A Teale1, Steven Letkowski, George Matusick, Stephen V Stehman, John D Castello.   

Abstract

Beech scale, Cryptococcus fagisuga Lindinger, is a non-native invasive insect associated with beech bark disease. A quantitative method of measuring viable scale density at the levels of the individual tree and localized bark patches was developed. Bark patches (10 cm(2)) were removed at 0, 1, and 2 m above the ground and at the four cardinal directions from 13 trees in northern New York and 12 trees in northern Michigan. Digital photographs of each patch were made, and the wax mass area was measured from two random 1-cm(2) subsamples on each bark patch using image analysis software. Viable scale insects were counted after removing the wax under a dissecting microscope. Separate regression analyses at the whole tree level for the New York and Michigan sites each showed a strong positive relationship of wax mass area with the number of underlying viable scale insects. The relationships for the New York and Michigan data were not significantly different from each other, and when pooling data from the two sites, there was still a significant positive relationship between wax mass area and the number of scale insects. The relationships between viable scale insects and wax mass area were different at the 0-, 1-, and 2-m sampling heights but do not seem to affect the relationship. This method does not disrupt the insect or its interactions with the host tree.

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Year:  2009        PMID: 19689905     DOI: 10.1603/022.038.0434

Source DB:  PubMed          Journal:  Environ Entomol        ISSN: 0046-225X            Impact factor:   2.377


  3 in total

1.  Small-scale intraspecific life history variation in herbivorous spider mites (Tetranychus pacificus) is associated with host plant cultivar.

Authors:  Katherine Scranton; Menelaos Stavrinides; Nicholas J Mills; Perry de Valpine
Journal:  PLoS One       Date:  2013-09-13       Impact factor: 3.240

2.  Automatic Pest Counting from Pheromone Trap Images Using Deep Learning Object Detectors for Matsucoccus thunbergianae Monitoring.

Authors:  Suk-Ju Hong; Il Nam; Sang-Yeon Kim; Eungchan Kim; Chang-Hyup Lee; Sebeom Ahn; Il-Kwon Park; Ghiseok Kim
Journal:  Insects       Date:  2021-04-12       Impact factor: 2.769

3.  Instar Determination of Blattella asahinai (Blattodea: Ectobiidae) From Digital Measurements of the Pronotum Using Gaussian Mixture Modeling and the Number of Cercal Annuli.

Authors:  Madison K Peterson; Arthur G Appel; Xing Ping Hu
Journal:  J Insect Sci       Date:  2019-09-01       Impact factor: 1.857

  3 in total

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