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Differentiation of mixed soil-borne fungi in the genus level using infrared spectroscopy and multivariate analysis
Early detection of soil-borne pathogens, which have a negative effect on almost all agricultural crops, is crucial for effective targeting with the most suitable antifungal agents and thus preventing and/or reducing their severity. They are responsible for severe diseases in various plants, leading...
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Published in: | Journal of photochemistry and photobiology. B, Biology Biology, 2018-03, Vol.180, p.155-165 |
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creator | Huleihel, M. Shufan, E. Tsror, L. Sharaha, U. Lapidot, I. Mordechai, S. Salman, A. |
description | Early detection of soil-borne pathogens, which have a negative effect on almost all agricultural crops, is crucial for effective targeting with the most suitable antifungal agents and thus preventing and/or reducing their severity. They are responsible for severe diseases in various plants, leading in many cases to substantial economic losses. In this study, infrared (IR) spectroscopic method, which is known as sensitive, accurate and rapid, was used to discriminate between different fungi in a mixture was evaluated. Mixed and pure samples of Colletotrichum, Verticillium, Rhizoctonia, and Fusarium genera were measured using IR microscopy. Our spectral results showed that the best differentiation between pure and mixed fungi was obtained in the 675–1800 cm−1 wavenumber region. Principal components analysis (PCA), followed by linear discriminant analysis (LDA) as a linear classifier, was performed on the spectra of the measured classes. Our results showed that it is possible to differentiate between mixed-calculated categories of phytopathogens with high success rates (~100%) when the mixing percentage range is narrow (40–60) in the genus level; when the mixing percentage range is wide (10–90), the success rate exceeded 85%. Also, in the measured mixed categories of phytopathogens it is possible to differentiate between the different categories with ~100% success rate.
•IR spectroscopy has the potential to detect fungus in mixed samples.•It is possible to evaluate the fungi in mixture by calculations.•The 675–1800 cm−1 region gave the best differentiation among pure and mixed fungi. |
doi_str_mv | 10.1016/j.jphotobiol.2018.02.007 |
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•IR spectroscopy has the potential to detect fungus in mixed samples.•It is possible to evaluate the fungi in mixture by calculations.•The 675–1800 cm−1 region gave the best differentiation among pure and mixed fungi.</description><subject>Agricultural economics</subject><subject>Antifungal agents</subject><subject>Categories</subject><subject>Colletotrichum</subject><subject>Differentiation</subject><subject>Discriminant analysis</subject><subject>Economic impact</subject><subject>Fourier transforms</subject><subject>FTIR-microscopy</subject><subject>Fungi</subject><subject>Fungicides</subject><subject>Fusarium</subject><subject>Genera</subject><subject>Infrared analysis</subject><subject>Infrared spectroscopy</subject><subject>LDA</subject><subject>Microscopy</subject><subject>Multivariate analysis</subject><subject>PCA</subject><subject>Plant diseases</subject><subject>Principal components analysis</subject><subject>Rhizoctonia</subject><subject>Soil microorganisms</subject><subject>Verticillium</subject><subject>Wavelengths</subject><issn>1011-1344</issn><issn>1873-2682</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFkU-P1SAUxYlx4owzfgVD4sZN64VCaZc6_k0mcTOzJpTevqFpoUL74vv20rxREzfCAgK_cw_cQwhlUDJg9buxHJfHsIbOhankwJoSeAmgnpEr1qiq4HXDn-c9MFawSohL8jKlEfKQtXpBLnkrqgpkdUXiRzcMGNGvzqwueBoGOruf2NMU3FR0IXqkw-YPjjpP10ekB_RbohMecaJbcv6QL4Zo4i5Z0K4xJBuWEzW-p_M2re5oYq6N-cBMp-TSDbkYzJTw1dN6TR4-f7q__Vrcff_y7fb9XWEF8LXokbdWtCA7qwRX2DFmFEPW90zJQRkJaISpjWCtslK2wqLsjLBcNvvsqmvy9lx3ieHHhmnVs0sWp8l4DFvSHIC1DGoJGX3zDzqGLeb37lQtskXFm0w1Z8rmP6aIg16im008aQZ6z0WP-m8ues9FA9c5lyx9_WSwdTP2f4S_g8jAhzOAuSNHh1En69Bb7F3MTdV9cP93-QXffqWS</recordid><startdate>201803</startdate><enddate>201803</enddate><creator>Huleihel, M.</creator><creator>Shufan, E.</creator><creator>Tsror, L.</creator><creator>Sharaha, U.</creator><creator>Lapidot, I.</creator><creator>Mordechai, S.</creator><creator>Salman, A.</creator><general>Elsevier B.V</general><general>Elsevier BV</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>7TK</scope><scope>7U7</scope><scope>C1K</scope><scope>7X8</scope></search><sort><creationdate>201803</creationdate><title>Differentiation of mixed soil-borne fungi in the genus level using infrared spectroscopy and multivariate analysis</title><author>Huleihel, M. ; Shufan, E. ; Tsror, L. ; Sharaha, U. ; Lapidot, I. ; Mordechai, S. ; Salman, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c402t-de29c4905bc7427eb11a71e1dd175f7a50ea4a6a4197c5594ce5ba4c2585858b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Agricultural economics</topic><topic>Antifungal agents</topic><topic>Categories</topic><topic>Colletotrichum</topic><topic>Differentiation</topic><topic>Discriminant analysis</topic><topic>Economic impact</topic><topic>Fourier transforms</topic><topic>FTIR-microscopy</topic><topic>Fungi</topic><topic>Fungicides</topic><topic>Fusarium</topic><topic>Genera</topic><topic>Infrared analysis</topic><topic>Infrared spectroscopy</topic><topic>LDA</topic><topic>Microscopy</topic><topic>Multivariate analysis</topic><topic>PCA</topic><topic>Plant diseases</topic><topic>Principal components analysis</topic><topic>Rhizoctonia</topic><topic>Soil microorganisms</topic><topic>Verticillium</topic><topic>Wavelengths</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huleihel, M.</creatorcontrib><creatorcontrib>Shufan, E.</creatorcontrib><creatorcontrib>Tsror, L.</creatorcontrib><creatorcontrib>Sharaha, U.</creatorcontrib><creatorcontrib>Lapidot, I.</creatorcontrib><creatorcontrib>Mordechai, S.</creatorcontrib><creatorcontrib>Salman, A.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of photochemistry and photobiology. B, Biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huleihel, M.</au><au>Shufan, E.</au><au>Tsror, L.</au><au>Sharaha, U.</au><au>Lapidot, I.</au><au>Mordechai, S.</au><au>Salman, A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Differentiation of mixed soil-borne fungi in the genus level using infrared spectroscopy and multivariate analysis</atitle><jtitle>Journal of photochemistry and photobiology. B, Biology</jtitle><addtitle>J Photochem Photobiol B</addtitle><date>2018-03</date><risdate>2018</risdate><volume>180</volume><spage>155</spage><epage>165</epage><pages>155-165</pages><issn>1011-1344</issn><eissn>1873-2682</eissn><abstract>Early detection of soil-borne pathogens, which have a negative effect on almost all agricultural crops, is crucial for effective targeting with the most suitable antifungal agents and thus preventing and/or reducing their severity. They are responsible for severe diseases in various plants, leading in many cases to substantial economic losses. In this study, infrared (IR) spectroscopic method, which is known as sensitive, accurate and rapid, was used to discriminate between different fungi in a mixture was evaluated. Mixed and pure samples of Colletotrichum, Verticillium, Rhizoctonia, and Fusarium genera were measured using IR microscopy. Our spectral results showed that the best differentiation between pure and mixed fungi was obtained in the 675–1800 cm−1 wavenumber region. Principal components analysis (PCA), followed by linear discriminant analysis (LDA) as a linear classifier, was performed on the spectra of the measured classes. Our results showed that it is possible to differentiate between mixed-calculated categories of phytopathogens with high success rates (~100%) when the mixing percentage range is narrow (40–60) in the genus level; when the mixing percentage range is wide (10–90), the success rate exceeded 85%. Also, in the measured mixed categories of phytopathogens it is possible to differentiate between the different categories with ~100% success rate.
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subjects | Agricultural economics Antifungal agents Categories Colletotrichum Differentiation Discriminant analysis Economic impact Fourier transforms FTIR-microscopy Fungi Fungicides Fusarium Genera Infrared analysis Infrared spectroscopy LDA Microscopy Multivariate analysis PCA Plant diseases Principal components analysis Rhizoctonia Soil microorganisms Verticillium Wavelengths |
title | Differentiation of mixed soil-borne fungi in the genus level using infrared spectroscopy and multivariate analysis |
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