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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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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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 -