Literature DB >> 17066799

Hyperspectral spectrometry as a means to differentiate uninfested and infested winter wheat by greenbug (Hemiptera: Aphididae).

Mustafa Mirik1, Gerald J Michels, Sabina Kassymzhanova-Mirik, Norman C Elliott, Roxanne Bowling.   

Abstract

Although spectral remote sensing techniques have been used to study many ecological variables and biotic and abiotic stresses to agricultural crops over decades, the potential use of these techniques for greenbug, Schizaphis graminum (Rondani) (Hemiptera: Aphididae) infestations and damage to wheat, Triticum aestivum L., under field conditions is unknown. Hence, this research was conducted to investigate: 1) the applicability and feasibility of using a portable narrow-banded (hyperspectral) remote sensing instrument to identify and discern differences in spectral reflection patterns (spectral signatures) of winter wheat canopies with and without greenbug damage; and 2) the relationship between miscellaneous spectral vegetation indices and greenbug density in wheat canopies growing in two fields and under greenhouse conditions. Both greenbug and reflectance data were collected from 0.25-, 0.37-, and 1-m2 plots in one of the fields, greenhouse, and the other field, respectively. Regardless of the growth conditions, greenbug-damaged wheat canopies had higher reflectance in the visible range and less in the near infrared regions of the spectrum when compared with undamaged canopies. In addition to percentage of reflectance comparison, a large number of spectral vegetation indices drawn from the literature were calculated and correlated with greenbug density. Linear regression analyses revealed high relationships (R2 ranged from 0.62 to 0.85) between greenbug density and spectral vegetation indices. These results indicate that hyperspectral remotely sensed data with an appropriate pixel size have the potential to portray greenbug density and discriminate its damage to wheat with repeated accuracy and precision.

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Year:  2006        PMID: 17066799     DOI: 10.1603/0022-0493-99.5.1682

Source DB:  PubMed          Journal:  J Econ Entomol        ISSN: 0022-0493            Impact factor:   2.381


  2 in total

1.  Spectral Signatures of Immature Lucilia sericata (Meigen) (Diptera: Calliphoridae).

Authors:  Jodie-A Warren; T D Pulindu Ratnasekera; David A Campbell; Gail S Anderson
Journal:  Insects       Date:  2017-03-23       Impact factor: 2.769

2.  Detection of Stress in Cotton (Gossypium hirsutum L.) Caused by Aphids Using Leaf Level Hyperspectral Measurements.

Authors:  Tingting Chen; Ruier Zeng; Wenxuan Guo; Xueying Hou; Yubin Lan; Lei Zhang
Journal:  Sensors (Basel)       Date:  2018-08-24       Impact factor: 3.576

  2 in total

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