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  • 20 MS VIBRATIONAL SPECTROSCOPY 2020 V1 PS CLMM FLM-1 MRM Submit

    Rights statement: 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

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

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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.; Morais, C.L.M.; Martin, F.L.; McAinsh, M.R.

In: Vibrational Spectroscopy, Vol. 111, 103171, 01.11.2020.

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@article{176466551a7849688d72f0ece93793bc,
title = "Attenuated total reflection Fourier-transform infrared spectroscopy coupled with chemometrics directly detects pre- and post-symptomatic changes in tomato plants infected with Botrytis cinerea",
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.",
keywords = "Botrytis cinerea, Chemometrics, Crop biology, Infrared spectroscopy, Pest detection, Sensors, Tomato, Crops, Decision making, Diagnosis, Discriminant analysis, Electromagnetic wave reflection, Food supply, Fourier transform infrared spectroscopy, Spectrometers, Attenuated total reflection Fourier transform infrared spectroscopy, Attenuated total reflections, Biochemical information, Diagnostic potential, Fingerprint spectra, Linear discriminant analysis, Plant-microbe interactions, Solanum lycopersicum, Plants (botany)",
author = "P. Skolik and C.L.M. Morais and F.L. Martin and M.R. McAinsh",
note = "This is the author{\textquoteright}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",
year = "2020",
month = nov,
day = "1",
doi = "10.1016/j.vibspec.2020.103171",
language = "English",
volume = "111",
journal = "Vibrational Spectroscopy",
issn = "0924-2031",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Attenuated total reflection Fourier-transform infrared spectroscopy coupled with chemometrics directly detects pre- and post-symptomatic changes in tomato plants infected with Botrytis cinerea

AU - Skolik, P.

AU - Morais, C.L.M.

AU - Martin, F.L.

AU - McAinsh, M.R.

N1 - 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

PY - 2020/11/1

Y1 - 2020/11/1

N2 - 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.

AB - 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.

KW - Botrytis cinerea

KW - Chemometrics

KW - Crop biology

KW - Infrared spectroscopy

KW - Pest detection

KW - Sensors

KW - Tomato

KW - Crops

KW - Decision making

KW - Diagnosis

KW - Discriminant analysis

KW - Electromagnetic wave reflection

KW - Food supply

KW - Fourier transform infrared spectroscopy

KW - Spectrometers

KW - Attenuated total reflection Fourier transform infrared spectroscopy

KW - Attenuated total reflections

KW - Biochemical information

KW - Diagnostic potential

KW - Fingerprint spectra

KW - Linear discriminant analysis

KW - Plant-microbe interactions

KW - Solanum lycopersicum

KW - Plants (botany)

U2 - 10.1016/j.vibspec.2020.103171

DO - 10.1016/j.vibspec.2020.103171

M3 - Journal article

VL - 111

JO - Vibrational Spectroscopy

JF - Vibrational Spectroscopy

SN - 0924-2031

M1 - 103171

ER -