Attenuated total reflection Fourier-transform infrared spectroscopy coupled with chemometrics directly detects pre- and post-symptomatic changes in tomato plants infected with Botrytis cinerea

Skolik, P. and Morais, C.L.M. and Martin, F.L. and McAinsh, M.R. (2020) Attenuated total reflection Fourier-transform infrared spectroscopy coupled with chemometrics directly detects pre- and post-symptomatic changes in tomato plants infected with Botrytis cinerea. Vibrational Spectroscopy, 111: 103171. ISSN 0924-2031

[thumbnail of 20 MS VIBRATIONAL SPECTROSCOPY 2020 V1 PS CLMM FLM-1 MRM Submit]

Text (20 MS VIBRATIONAL SPECTROSCOPY 2020 V1 PS CLMM FLM-1 MRM Submit)
20_MS_VIBRATIONAL_SPECTROSCOPY_2020_V1_PS_CLMM_FLM_1_MRM_Submit.docx - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.
Download (114kB)

Abstract

Sensor-based detection of pests and pathogens in a high throughput and non-destructive manner is essential for mitigating crop loss. Infrared (IR) sensors in the form of vibrational spectroscopy provide both biochemical information about disease, as well as a large number of variables for chemometrics. This approach is highly adaptable to most biological systems including interactions between plants and their environments. Fast-acting necrotrophic fungal pathogens present a specific group of pests with adverse effects on food production and supply and are therefore pertinent to food security. Botrytis cinerea and Solanum lycopersicum are models for the study of fungal and crop biology respectively. Herein we use a compact mid-IR spectrometer with attenuated total reflection (ATR) attachment to measure the plant-microbe interaction between S. lycopersicum and B. cinerea on leaves, in vivo of intact plants. Chemometric models including exploratory principal component analysis (PCA) solely, and as a classifier in combination with linear discriminant analysis (PCA-LDA) are applied. Fingerprint spectra (1800−900 cm−1) were excellent discriminators of plant disease in both visually symptomatic as well pre-symptomatic plants. Major biochemical alterations in leaf tissue as a result of infection are discussed. Diagnostic potential for automatic decision-making platforms is shown by high accuracy rates of 100 % for detecting plant disease at various stages of progression.

Item Type:

Journal Article

Journal or Publication Title:

Vibrational Spectroscopy

Additional Information:

This is the author’s version of a work that was accepted for publication in Vibrational Spectroscopy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Vibrational Spectroscopy, 111, 2020 DOI: 10.1016/j.vibspec.2020.103171

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/1600/1607

Subjects:

?? botrytis cinereachemometricscrop biologyinfrared spectroscopypest detectionsensorstomatocropsdecision makingdiagnosisdiscriminant analysiselectromagnetic wave reflectionfood supplyfourier transform infrared spectroscopyspectrometersattenuated total reflec ??

Departments:

Faculty of Science and Technology > Lancaster Environment Centre

ID Code:

149036

Deposited By:

ep_importer_pure

Deposited On:

13 Nov 2020 11:10

Refereed?:

Yes

Published?:

Published