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Detection of Fungal Diseases in Lettuce by VIR-NIR Spectroscopy in Aquaponics
One of the main challenges facing the development of aquaponics is disease control, due on one hand to the fact that plants cannot be treated with chemicals because they can lead to mortality in cultured fish. The aim of this study was to apply the visible–near-infrared spectroscopy and vegetation i...
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Published in: | Microorganisms (Basel) 2023-09, Vol.11 (9), p.2348 |
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creator | Sirakov, Ivaylo Velichkova, Katya Dinev, Toncho Slavcheva-Sirakova, Desislava Valkova, Elica Yorgov, Dimitar Veleva, Petya Atanasov, Vasil Atanassova, Stefka |
description | One of the main challenges facing the development of aquaponics is disease control, due on one hand to the fact that plants cannot be treated with chemicals because they can lead to mortality in cultured fish. The aim of this study was to apply the visible–near-infrared spectroscopy and vegetation index approach to test aquaponically cultivated lettuce (Lactuca sativa L.) infected with different fungal pathogens (Aspergillus niger, Fusarium oxysporum, and Alternaria alternata). The lettuces on the third leaf formation were placed in tanks (with dimensions 1 m/0.50 m/0.35 m) filled up with water from the aquaponics system every second day. In this study, we included reference fungal strains Aspergillus niger NBIMCC 3252, Fusarium oxysporum NBIMCC 125, and Alternaria alternata NBIMCC 109. Diffuse reflectance spectra of the leaves of lettuce were measured directly on the plants using a USB4000 spectrometer in the 450–1100 nm wavelength range. In near-infrared spectral range, the reflectance values of infected leaves are lower than those of the control, which indicates that some changes in cell structures occurred as a result of the fungal infection. All three investigated pathogens had a statistically significant effect on leaf water content and water band index. Vegetative indices such as Chlorophyll Absorption in Reflectance Index (CARI), Modified chlorophyll absorption in reflectance index (MCARI), Plant Senescence Reflectance Index (PSRI), Red Edge Index (REI2), Red Edge Index (REI3), and Water band index (WBI) were found to be effective in distinguishing infected plants from healthy ones, with WBI demonstrating the greatest reliability. |
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All three investigated pathogens had a statistically significant effect on leaf water content and water band index. Vegetative indices such as Chlorophyll Absorption in Reflectance Index (CARI), Modified chlorophyll absorption in reflectance index (MCARI), Plant Senescence Reflectance Index (PSRI), Red Edge Index (REI2), Red Edge Index (REI3), and Water band index (WBI) were found to be effective in distinguishing infected plants from healthy ones, with WBI demonstrating the greatest reliability.</description><identifier>ISSN: 2076-2607</identifier><identifier>EISSN: 2076-2607</identifier><identifier>DOI: 10.3390/microorganisms11092348</identifier><identifier>PMID: 37764192</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Absorption ; Agricultural research ; Alternaria alternata ; Aquaculture ; Aquaponics ; Aspergillus niger ; Chlorophyll ; Data analysis ; Diagnosis ; Disease control ; Disease prevention ; Diseases and pests ; Flowers & plants ; Fruits ; Fungal diseases ; Fungal diseases of plants ; Fungi ; Fusarium oxysporum ; Infections ; Infrared spectra ; Infrared spectroscopy ; Leaves ; Lettuce ; Lettuces ; Microorganisms ; Moisture content ; Near infrared radiation ; Optics ; pathogen detection ; Pathogens ; plant health ; Plants (botany) ; prevention ; Reflectance ; Senescence ; Spectrum analysis ; Statistical analysis ; Vegetables ; Vegetation ; Vegetation index ; Water content</subject><ispartof>Microorganisms (Basel), 2023-09, Vol.11 (9), p.2348</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. 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The aim of this study was to apply the visible–near-infrared spectroscopy and vegetation index approach to test aquaponically cultivated lettuce (Lactuca sativa L.) infected with different fungal pathogens (Aspergillus niger, Fusarium oxysporum, and Alternaria alternata). The lettuces on the third leaf formation were placed in tanks (with dimensions 1 m/0.50 m/0.35 m) filled up with water from the aquaponics system every second day. In this study, we included reference fungal strains Aspergillus niger NBIMCC 3252, Fusarium oxysporum NBIMCC 125, and Alternaria alternata NBIMCC 109. Diffuse reflectance spectra of the leaves of lettuce were measured directly on the plants using a USB4000 spectrometer in the 450–1100 nm wavelength range. In near-infrared spectral range, the reflectance values of infected leaves are lower than those of the control, which indicates that some changes in cell structures occurred as a result of the fungal infection. All three investigated pathogens had a statistically significant effect on leaf water content and water band index. Vegetative indices such as Chlorophyll Absorption in Reflectance Index (CARI), Modified chlorophyll absorption in reflectance index (MCARI), Plant Senescence Reflectance Index (PSRI), Red Edge Index (REI2), Red Edge Index (REI3), and Water band index (WBI) were found to be effective in distinguishing infected plants from healthy ones, with WBI demonstrating the greatest reliability.</description><subject>Absorption</subject><subject>Agricultural research</subject><subject>Alternaria alternata</subject><subject>Aquaculture</subject><subject>Aquaponics</subject><subject>Aspergillus niger</subject><subject>Chlorophyll</subject><subject>Data analysis</subject><subject>Diagnosis</subject><subject>Disease control</subject><subject>Disease prevention</subject><subject>Diseases and pests</subject><subject>Flowers & plants</subject><subject>Fruits</subject><subject>Fungal diseases</subject><subject>Fungal diseases of plants</subject><subject>Fungi</subject><subject>Fusarium oxysporum</subject><subject>Infections</subject><subject>Infrared spectra</subject><subject>Infrared spectroscopy</subject><subject>Leaves</subject><subject>Lettuce</subject><subject>Lettuces</subject><subject>Microorganisms</subject><subject>Moisture content</subject><subject>Near infrared radiation</subject><subject>Optics</subject><subject>pathogen detection</subject><subject>Pathogens</subject><subject>plant health</subject><subject>Plants (botany)</subject><subject>prevention</subject><subject>Reflectance</subject><subject>Senescence</subject><subject>Spectrum analysis</subject><subject>Statistical analysis</subject><subject>Vegetables</subject><subject>Vegetation</subject><subject>Vegetation index</subject><subject>Water content</subject><issn>2076-2607</issn><issn>2076-2607</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkl-P1CAUxRujcTfrfgXTxBdfunKhQPtkJruuTjJqsv55JZReRiYtdKE1mW8v42zUMQsPkMu5P8LhFMVLIFeMteTN6EwMIW61d2lMAKSlrG6eFOeUSFFRQeTTf_ZnxWVKO5JHC6zh8Lw4Y1KKGlp6Xny8wRnN7IIvgy1vF7_VQ3njEuqEqXS-3OA8LwbLbl9-X99Vn9Z35Zcpd8SQTJj2B8nqftFT8M6kF8Uzq4eElw_rRfHt9t3X6w_V5vP79fVqUxnO2VwZyTTRAqkWgGBqTgGZtNDUwtLeCKOBcdkYrglwRCSU8A4ElY3sWtJRdlGsj9w-6J2aoht13KugnfpdyNYoHWdnBlSsNo2l2vaGmppi1wnsO6uFANZabtvMentkTUs3Ym_Qz1EPJ9DTE-9-qG34qYDw7CNlmfD6gRDD_YJpVqNLBodBewxLUrSRBGrKmiZLX_0n3YUl-uxVVom25jWR8FeVPwOV8zbki80BqlZSQgNAxcGEq0dUefaYAxI8WpfrJw3i2JDTk1JE--eRQNQhWOrxYLFfrCXBzQ</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Sirakov, Ivaylo</creator><creator>Velichkova, Katya</creator><creator>Dinev, Toncho</creator><creator>Slavcheva-Sirakova, Desislava</creator><creator>Valkova, Elica</creator><creator>Yorgov, Dimitar</creator><creator>Veleva, Petya</creator><creator>Atanasov, Vasil</creator><creator>Atanassova, Stefka</creator><general>MDPI AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7T7</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>P64</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8319-0310</orcidid><orcidid>https://orcid.org/0000-0002-7005-7569</orcidid><orcidid>https://orcid.org/0000-0002-8405-3382</orcidid><orcidid>https://orcid.org/0000-0003-1797-9879</orcidid></search><sort><creationdate>20230901</creationdate><title>Detection of Fungal Diseases in Lettuce by VIR-NIR Spectroscopy in Aquaponics</title><author>Sirakov, Ivaylo ; Velichkova, Katya ; Dinev, Toncho ; Slavcheva-Sirakova, Desislava ; Valkova, Elica ; Yorgov, Dimitar ; Veleva, Petya ; Atanasov, Vasil ; Atanassova, Stefka</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c553t-c73a0a6e2a61e1c4521e37f1846f2dc6ca13578c5a015eee0205b162787b90b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Absorption</topic><topic>Agricultural research</topic><topic>Alternaria alternata</topic><topic>Aquaculture</topic><topic>Aquaponics</topic><topic>Aspergillus niger</topic><topic>Chlorophyll</topic><topic>Data analysis</topic><topic>Diagnosis</topic><topic>Disease control</topic><topic>Disease prevention</topic><topic>Diseases and pests</topic><topic>Flowers & plants</topic><topic>Fruits</topic><topic>Fungal diseases</topic><topic>Fungal diseases of plants</topic><topic>Fungi</topic><topic>Fusarium oxysporum</topic><topic>Infections</topic><topic>Infrared spectra</topic><topic>Infrared spectroscopy</topic><topic>Leaves</topic><topic>Lettuce</topic><topic>Lettuces</topic><topic>Microorganisms</topic><topic>Moisture content</topic><topic>Near infrared radiation</topic><topic>Optics</topic><topic>pathogen detection</topic><topic>Pathogens</topic><topic>plant health</topic><topic>Plants (botany)</topic><topic>prevention</topic><topic>Reflectance</topic><topic>Senescence</topic><topic>Spectrum analysis</topic><topic>Statistical analysis</topic><topic>Vegetables</topic><topic>Vegetation</topic><topic>Vegetation index</topic><topic>Water content</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sirakov, Ivaylo</creatorcontrib><creatorcontrib>Velichkova, Katya</creatorcontrib><creatorcontrib>Dinev, Toncho</creatorcontrib><creatorcontrib>Slavcheva-Sirakova, Desislava</creatorcontrib><creatorcontrib>Valkova, Elica</creatorcontrib><creatorcontrib>Yorgov, Dimitar</creatorcontrib><creatorcontrib>Veleva, Petya</creatorcontrib><creatorcontrib>Atanasov, Vasil</creatorcontrib><creatorcontrib>Atanassova, Stefka</creatorcontrib><collection>CrossRef</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Biological Sciences</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Microorganisms (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sirakov, Ivaylo</au><au>Velichkova, Katya</au><au>Dinev, Toncho</au><au>Slavcheva-Sirakova, Desislava</au><au>Valkova, Elica</au><au>Yorgov, Dimitar</au><au>Veleva, Petya</au><au>Atanasov, Vasil</au><au>Atanassova, Stefka</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection of Fungal Diseases in Lettuce by VIR-NIR Spectroscopy in Aquaponics</atitle><jtitle>Microorganisms (Basel)</jtitle><date>2023-09-01</date><risdate>2023</risdate><volume>11</volume><issue>9</issue><spage>2348</spage><pages>2348-</pages><issn>2076-2607</issn><eissn>2076-2607</eissn><abstract>One of the main challenges facing the development of aquaponics is disease control, due on one hand to the fact that plants cannot be treated with chemicals because they can lead to mortality in cultured fish. 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All three investigated pathogens had a statistically significant effect on leaf water content and water band index. Vegetative indices such as Chlorophyll Absorption in Reflectance Index (CARI), Modified chlorophyll absorption in reflectance index (MCARI), Plant Senescence Reflectance Index (PSRI), Red Edge Index (REI2), Red Edge Index (REI3), and Water band index (WBI) were found to be effective in distinguishing infected plants from healthy ones, with WBI demonstrating the greatest reliability.</abstract><cop>Basel</cop><pub>MDPI AG</pub><pmid>37764192</pmid><doi>10.3390/microorganisms11092348</doi><orcidid>https://orcid.org/0000-0001-8319-0310</orcidid><orcidid>https://orcid.org/0000-0002-7005-7569</orcidid><orcidid>https://orcid.org/0000-0002-8405-3382</orcidid><orcidid>https://orcid.org/0000-0003-1797-9879</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Absorption Agricultural research Alternaria alternata Aquaculture Aquaponics Aspergillus niger Chlorophyll Data analysis Diagnosis Disease control Disease prevention Diseases and pests Flowers & plants Fruits Fungal diseases Fungal diseases of plants Fungi Fusarium oxysporum Infections Infrared spectra Infrared spectroscopy Leaves Lettuce Lettuces Microorganisms Moisture content Near infrared radiation Optics pathogen detection Pathogens plant health Plants (botany) prevention Reflectance Senescence Spectrum analysis Statistical analysis Vegetables Vegetation Vegetation index Water content |
title | Detection of Fungal Diseases in Lettuce by VIR-NIR Spectroscopy in Aquaponics |
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