Spectral assessment of two-spotted spider mite damage levels in the leaves of greenhouse-grown pepper and bean

Ittai Herrmann, Michael Berenstein, Tarin Paz-Kagan, Amit Sade, Arnon Karnieli*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

The two-spotted spider mite (Tetranychus urticae Koch; TSSM) feeds on the under-surface of leaves, piercing the chloroplast-containing cells and affecting pigments as well as leaf structure. This damage could be spectrally detectable in the visible and near-infrared spectral regions. The aim was to spectrally explore the ability to assess TSSM damage levels in greenhouse-grown pepper (Capsicum annuum) and bean (Phaseolus vulgaris) leaves. Several vegetation indices (VIs) provided the ability to classify early TSSM damage using a one-way analysis of variance. Hyperspectral (400–1000 nm) and multispectral (five common bands) data were analysed and cross-validated independently by partial least squares-discriminant analysis models. These analyses resulted in 100% and 95% success in identifying early damage with hyperspectral data reflected from pepper and bean leaves, respectively, and in 92% with multispectral data reflected from pepper leaves. Although the TSSM activity occurred on the underside of leaves their damage can be spectrally detected by reflected data from the upper side. Early TSSM damage identification to greenhouse pepper and bean leaves, that their sole damage was by TSSM, can be obtained by VIs, hyperspectral data, and multispectral data. This study shows that by using sub leaf spatial resolution early damage by TSSM can be spectrally detected. It can be potentially applied for greenhouses as well as fields as an early detection method for TSSM management.

Original languageEnglish
Pages (from-to)72-85
Number of pages14
JournalBiosystems Engineering
Volume157
DOIs
StatePublished - 1 May 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 IAgrE

Keywords

  • Integrated pest management
  • Partial least squares-discriminant analysis (PLS-DA)
  • Spectral analysis
  • Two-spotted spider mite
  • Vegetation indices

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