Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies
Abstract Soil acidity (pH <5.5) limits agricultural production due to aluminum (Al) toxicity. The primary target of Al toxicity is the plant root. However, symptoms can be observed on the shoots. This study aims to determine the potential use of chlorophyll fluorescence imaging, multispectral ima...
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| Format: | Article |
| Language: | English |
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Wiley
2024-07-01
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| Series: | Plant Direct |
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| Online Access: | https://doi.org/10.1002/pld3.623 |
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| _version_ | 1841558654496538624 |
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| author | Lóránt Szőke Brigitta Tóth Tomislav Javornik Boris Lazarević |
| author_facet | Lóránt Szőke Brigitta Tóth Tomislav Javornik Boris Lazarević |
| author_sort | Lóránt Szőke |
| collection | DOAJ |
| description | Abstract Soil acidity (pH <5.5) limits agricultural production due to aluminum (Al) toxicity. The primary target of Al toxicity is the plant root. However, symptoms can be observed on the shoots. This study aims to determine the potential use of chlorophyll fluorescence imaging, multispectral imaging, and 3D multispectral scanning technology to quantify the effects of Al toxicity on corn. Corn seedlings were grown for 13 days in nutrient solutions (pH 4.0) with four Al treatments: 50, 100, 200, and 400 μM and a control (0 μM AlCl3 L−1). During the experiment, four measurements were performed: four (MT1), six (MT2), 11 (MT3), and 13 (MT4) days after the application of Al treatments. The most sensitive traits affected by Al toxicity were the reduction of plant growth and increased reflectance in the visible wavelength (affected at MT1). The reflectance of red wavelengths increased more significantly compared to near‐infrared and green wavelengths, leading to a decrease in the normalized difference vegetation index and the Green Leaf Index. The most sensitive chlorophyll fluorescence traits, effective quantum yield of PSII, and photochemical quenching coefficient were affected after prolonged Al exposure (MT3). This study demonstrates the usability of selected phenotypic traits in remote sensing studies to map Al‐toxic soils and in high‐throughput phenotyping studies to screen Al‐tolerant genotypes. |
| format | Article |
| id | doaj-art-ba650054859b47d6bdb2610ce1506bad |
| institution | Kabale University |
| issn | 2475-4455 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Plant Direct |
| spelling | doaj-art-ba650054859b47d6bdb2610ce1506bad2025-01-06T07:21:54ZengWileyPlant Direct2475-44552024-07-0187n/an/a10.1002/pld3.623Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologiesLóránt Szőke0Brigitta Tóth1Tomislav Javornik2Boris Lazarević3Department of Plant Nutrition University of Zagreb Faculty of Agriculture Zagreb CroatiaInstitute of Food Science, Faculty of Agricultural and Food Sciences and Environmental Management University of Debrecen Debrecen HungaryCentre of Excellence for Biodiversity and Molecular Plant Breeding University of Zagreb Zagreb CroatiaDepartment of Plant Nutrition University of Zagreb Faculty of Agriculture Zagreb CroatiaAbstract Soil acidity (pH <5.5) limits agricultural production due to aluminum (Al) toxicity. The primary target of Al toxicity is the plant root. However, symptoms can be observed on the shoots. This study aims to determine the potential use of chlorophyll fluorescence imaging, multispectral imaging, and 3D multispectral scanning technology to quantify the effects of Al toxicity on corn. Corn seedlings were grown for 13 days in nutrient solutions (pH 4.0) with four Al treatments: 50, 100, 200, and 400 μM and a control (0 μM AlCl3 L−1). During the experiment, four measurements were performed: four (MT1), six (MT2), 11 (MT3), and 13 (MT4) days after the application of Al treatments. The most sensitive traits affected by Al toxicity were the reduction of plant growth and increased reflectance in the visible wavelength (affected at MT1). The reflectance of red wavelengths increased more significantly compared to near‐infrared and green wavelengths, leading to a decrease in the normalized difference vegetation index and the Green Leaf Index. The most sensitive chlorophyll fluorescence traits, effective quantum yield of PSII, and photochemical quenching coefficient were affected after prolonged Al exposure (MT3). This study demonstrates the usability of selected phenotypic traits in remote sensing studies to map Al‐toxic soils and in high‐throughput phenotyping studies to screen Al‐tolerant genotypes.https://doi.org/10.1002/pld3.623Al toxicitychlorophyll fluorescencecornspectral reflectancevegetation indices |
| spellingShingle | Lóránt Szőke Brigitta Tóth Tomislav Javornik Boris Lazarević Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies Plant Direct Al toxicity chlorophyll fluorescence corn spectral reflectance vegetation indices |
| title | Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies |
| title_full | Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies |
| title_fullStr | Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies |
| title_full_unstemmed | Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies |
| title_short | Quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies |
| title_sort | quantifying aluminum toxicity effects on corn phenotype using advanced imaging technologies |
| topic | Al toxicity chlorophyll fluorescence corn spectral reflectance vegetation indices |
| url | https://doi.org/10.1002/pld3.623 |
| work_keys_str_mv | AT lorantszoke quantifyingaluminumtoxicityeffectsoncornphenotypeusingadvancedimagingtechnologies AT brigittatoth quantifyingaluminumtoxicityeffectsoncornphenotypeusingadvancedimagingtechnologies AT tomislavjavornik quantifyingaluminumtoxicityeffectsoncornphenotypeusingadvancedimagingtechnologies AT borislazarevic quantifyingaluminumtoxicityeffectsoncornphenotypeusingadvancedimagingtechnologies |