Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses
The persistence and productivity of forage grasses, important sources for feed production, are threatened by climate change-induced drought. Breeding programs are in search of new drought tolerant forage grass varieties, but those programs still rely on time-consuming and less consistent visual scor...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/1/147 |
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| author | Tom De Swaef Wouter H. Maes Jonas Aper Joost Baert Mathias Cougnon Dirk Reheul Kathy Steppe Isabel Roldán-Ruiz Peter Lootens |
| author_facet | Tom De Swaef Wouter H. Maes Jonas Aper Joost Baert Mathias Cougnon Dirk Reheul Kathy Steppe Isabel Roldán-Ruiz Peter Lootens |
| author_sort | Tom De Swaef |
| collection | DOAJ |
| description | The persistence and productivity of forage grasses, important sources for feed production, are threatened by climate change-induced drought. Breeding programs are in search of new drought tolerant forage grass varieties, but those programs still rely on time-consuming and less consistent visual scoring by breeders. In this study, we evaluate whether Unmanned Aerial Vehicle (UAV) based remote sensing can complement or replace this visual breeder score. A field experiment was set up to test the drought tolerance of genotypes from three common forage types of two different species: <i>Festuca arundinacea</i>, diploid <i>Lolium perenne</i> and tetraploid <i>Lolium perenne</i>. Drought stress was imposed by using mobile rainout shelters. UAV flights with RGB and thermal sensors were conducted at five time points during the experiment. Visual-based indices from different colour spaces were selected that were closely correlated to the breeder score. Furthermore, several indices, in particular <i>H</i> and <i>NDLab</i>, from the HSV (Hue Saturation Value) and CIELab (Commission Internationale de l’éclairage) colour space, respectively, displayed a broad-sense heritability that was as high or higher than the visual breeder score, making these indices highly suited for high-throughput field phenotyping applications that can complement or even replace the breeder score. The thermal-based Crop Water Stress Index <i>CWSI</i> provided complementary information to visual-based indices, enabling the analysis of differences in ecophysiological mechanisms for coping with reduced water availability between species and ploidy levels. All species/types displayed variation in drought stress tolerance, which confirms that there is sufficient variation for selection within these groups of grasses. Our results confirmed the better drought tolerance potential of <i>Festuca arundinacea</i>, but also showed which <i>Lolium perenne</i> genotypes are more tolerant. |
| first_indexed | 2024-03-10T13:28:51Z |
| format | Article |
| id | doaj.art-38a32203e1ca49689b88c0704276ab32 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T13:28:51Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-38a32203e1ca49689b88c0704276ab322023-11-21T08:27:21ZengMDPI AGRemote Sensing2072-42922021-01-0113114710.3390/rs13010147Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage GrassesTom De Swaef0Wouter H. Maes1Jonas Aper2Joost Baert3Mathias Cougnon4Dirk Reheul5Kathy Steppe6Isabel Roldán-Ruiz7Peter Lootens8Plant Sciences Unit, Research Institute for Agriculture, Fisheries and Food (ILVO), 9090 Melle, BelgiumUAV Research Centre (URC), Department of Plants and Crops, Ghent University, 9000 Ghent, BelgiumPlant Sciences Unit, Research Institute for Agriculture, Fisheries and Food (ILVO), 9090 Melle, BelgiumPlant Sciences Unit, Research Institute for Agriculture, Fisheries and Food (ILVO), 9090 Melle, BelgiumSustainable Crop Production, Department of Plants and Crops, Ghent University, 9000 Ghent, BelgiumSustainable Crop Production, Department of Plants and Crops, Ghent University, 9000 Ghent, BelgiumLaboratory of Plant Ecology, Department of Plants and Crops, Ghent University, 9000 Ghent, BelgiumPlant Sciences Unit, Research Institute for Agriculture, Fisheries and Food (ILVO), 9090 Melle, BelgiumPlant Sciences Unit, Research Institute for Agriculture, Fisheries and Food (ILVO), 9090 Melle, BelgiumThe persistence and productivity of forage grasses, important sources for feed production, are threatened by climate change-induced drought. Breeding programs are in search of new drought tolerant forage grass varieties, but those programs still rely on time-consuming and less consistent visual scoring by breeders. In this study, we evaluate whether Unmanned Aerial Vehicle (UAV) based remote sensing can complement or replace this visual breeder score. A field experiment was set up to test the drought tolerance of genotypes from three common forage types of two different species: <i>Festuca arundinacea</i>, diploid <i>Lolium perenne</i> and tetraploid <i>Lolium perenne</i>. Drought stress was imposed by using mobile rainout shelters. UAV flights with RGB and thermal sensors were conducted at five time points during the experiment. Visual-based indices from different colour spaces were selected that were closely correlated to the breeder score. Furthermore, several indices, in particular <i>H</i> and <i>NDLab</i>, from the HSV (Hue Saturation Value) and CIELab (Commission Internationale de l’éclairage) colour space, respectively, displayed a broad-sense heritability that was as high or higher than the visual breeder score, making these indices highly suited for high-throughput field phenotyping applications that can complement or even replace the breeder score. The thermal-based Crop Water Stress Index <i>CWSI</i> provided complementary information to visual-based indices, enabling the analysis of differences in ecophysiological mechanisms for coping with reduced water availability between species and ploidy levels. All species/types displayed variation in drought stress tolerance, which confirms that there is sufficient variation for selection within these groups of grasses. Our results confirmed the better drought tolerance potential of <i>Festuca arundinacea</i>, but also showed which <i>Lolium perenne</i> genotypes are more tolerant.https://www.mdpi.com/2072-4292/13/1/147UAVRGB camerathermal cameradrought toleranceforage grassHSV |
| spellingShingle | Tom De Swaef Wouter H. Maes Jonas Aper Joost Baert Mathias Cougnon Dirk Reheul Kathy Steppe Isabel Roldán-Ruiz Peter Lootens Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses Remote Sensing UAV RGB camera thermal camera drought tolerance forage grass HSV |
| title | Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses |
| title_full | Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses |
| title_fullStr | Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses |
| title_full_unstemmed | Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses |
| title_short | Applying RGB- and Thermal-Based Vegetation Indices from UAVs for High-Throughput Field Phenotyping of Drought Tolerance in Forage Grasses |
| title_sort | applying rgb and thermal based vegetation indices from uavs for high throughput field phenotyping of drought tolerance in forage grasses |
| topic | UAV RGB camera thermal camera drought tolerance forage grass HSV |
| url | https://www.mdpi.com/2072-4292/13/1/147 |
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