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Title: Remote sensing evaluation of two-spotted spider mite damage on greenhouse cotton

Author
item Martin, Daniel - Dan
item Latheef, Mohamed - Ab

Submitted to: Journal of Visualized Experiments
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/24/2016
Publication Date: 4/28/2017
Citation: Martin, D.E., Latheef, M.A. 2017. Remote sensing evaluation of two-spotted spider mite damage on greenhouse cotton. Journal of Visualized Experiments. doi:10.3791/54314.
DOI: https://doi.org/10.3791/54314

Interpretive Summary: Greenhouse studies were conducted on the use of a handheld multispectral optical sensor for detecting and quantifying spider mite damage on cotton, which replaced the traditional methods of subjectively estimate spider mite damage by eye. The work measured cotton damage from low, medium, and high infestations of spider mites over the course of 14 days. The optical sensor successfully and objectively differentiated between different infestation levels. As a result, this sensor will be an important tool for entomologists to use to objectively evaluate acaracide treatments for the control of spider mites.

Technical Abstract: Two-spotted spider mite, Tetranychus urticae Koch, is a polyphagous pest which occurs on a variety of field and horticultural crops. It often becomes an early season pest of cotton in damaging proportions from being a late season innocuous pest in the mid-southern United States. Evaluation of acaricides is important for maintaining efficacy and to prevent resistance to the currently available arsenal of chemicals and newly developed control agents. Enumeration of spider mites for efficacy evaluations is laborious and time consuming. Therefore, subjective visual damage rating is commonly used to assess density of spider mites. The NDVI (Normalized Difference Vegetation Index) is the most widely used statistic to describe the spectral reflectance characteristics of vegetation canopy to assess plant stress and health consequent to spider mite infestations. We evaluated a ground-based multispectral optical sensor as a remote sensing technique to assess numerical damage on greenhouse grown cotton in lieu of manual enumeration. Results demonstrated that a multispectral optical sensor is an effective tool in distinguishing varying levels of infestation caused by T. urticae on early season cotton. This remote sensing technique may be used in lieu of a visual rating to evaluate insecticide treatments.