High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield
Canopy temperature in cotton (Gossypium hirsutum) and other crops is related to crop and soil water status. Multiple approaches have been used to measure canopy temperature, depending on the application of the data and available technology. Recent technological advances have made it possible to map...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Smart Agricultural Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375523002204 |
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| author | Jeffrey Siegfried Nithya Rajan Curtis B. Adams Haly Neely Steve Hague Robert Hardin Ronnie Schnell Xiongzhe Han Alex Thomasson |
| author_facet | Jeffrey Siegfried Nithya Rajan Curtis B. Adams Haly Neely Steve Hague Robert Hardin Ronnie Schnell Xiongzhe Han Alex Thomasson |
| author_sort | Jeffrey Siegfried |
| collection | DOAJ |
| description | Canopy temperature in cotton (Gossypium hirsutum) and other crops is related to crop and soil water status. Multiple approaches have been used to measure canopy temperature, depending on the application of the data and available technology. Recent technological advances have made it possible to map canopy temperature using thermal cameras onboard unmanned aerial systems (UAS) at fine spatiotemporal resolution. Using a highly accurate UAS-mounted infrared camera, the objective of this study was to determine relationships of in-season cotton canopy temperature with seed cotton yield and soil moisture. This was accomplished in a two-year field study (2019 and 2020) with three irrigation (0, 40, and 80% ET replacement) and eight cotton variety treatments. Four in-season UAS flights were made per year. Using the approach described herein, it was possible to accurately exclude soil background information in thermal infrared orthomosaics using a simple threshold method without the need for ancillary imagery. This allowed accurate determination of average canopy temperatures across plots. Differences in canopy temperature and seed cotton yields across irrigation levels were largely aligned and, when comparing cotton varieties, there was evidence that canopy temperature identified subtle varietal differences that were not reflected in varietal yield differences. Overall, there were linear relationships between canopy temperature and seed cotton yield that ranged from weak to strong (R2 = 0.39 – 0.72, RMSE = 249.7 – 299.2 kg ha−1), depending on growing conditions. Canopy temperature was generally correlated with soil volumetric water content (VWC), but the relationship was not consistently strong and depended on moisture sensor depth. |
| first_indexed | 2024-03-08T04:50:15Z |
| format | Article |
| id | doaj.art-fedc77eb490b4ea2a3ad9bc9ae77c8b4 |
| institution | Directory Open Access Journal |
| issn | 2772-3755 |
| language | English |
| last_indexed | 2024-04-24T19:49:06Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj.art-fedc77eb490b4ea2a3ad9bc9ae77c8b42024-03-25T04:18:12ZengElsevierSmart Agricultural Technology2772-37552024-03-017100393High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yieldJeffrey Siegfried0Nithya Rajan1Curtis B. Adams2Haly Neely3Steve Hague4Robert Hardin5Ronnie Schnell6Xiongzhe Han7Alex Thomasson8Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, USADepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX, USA; Corresponding author.Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, USA; USDA-Agricultural Research Service, Columbia Plateau Conservation Research Center, Adams, OR, USADepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX, USA; Department of Crop and Soil Sciences, Washington State University, Pullman, WA, USADepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX, USA; Department of Crop, Soil, and Environmental Sciences, Auburn University, Auburn, AL, USADepartment of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, USADepartment of Soil and Crop Sciences, Texas A&M University, College Station, TX, USADepartment of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, USA; Department of Biosystems Engineering, Kangwon National University, Chuncheon, South KoreaDepartment of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, USA; Department of Agricultural and Biological Engineering, Mississippi State University, Starkville, MS, USACanopy temperature in cotton (Gossypium hirsutum) and other crops is related to crop and soil water status. Multiple approaches have been used to measure canopy temperature, depending on the application of the data and available technology. Recent technological advances have made it possible to map canopy temperature using thermal cameras onboard unmanned aerial systems (UAS) at fine spatiotemporal resolution. Using a highly accurate UAS-mounted infrared camera, the objective of this study was to determine relationships of in-season cotton canopy temperature with seed cotton yield and soil moisture. This was accomplished in a two-year field study (2019 and 2020) with three irrigation (0, 40, and 80% ET replacement) and eight cotton variety treatments. Four in-season UAS flights were made per year. Using the approach described herein, it was possible to accurately exclude soil background information in thermal infrared orthomosaics using a simple threshold method without the need for ancillary imagery. This allowed accurate determination of average canopy temperatures across plots. Differences in canopy temperature and seed cotton yields across irrigation levels were largely aligned and, when comparing cotton varieties, there was evidence that canopy temperature identified subtle varietal differences that were not reflected in varietal yield differences. Overall, there were linear relationships between canopy temperature and seed cotton yield that ranged from weak to strong (R2 = 0.39 – 0.72, RMSE = 249.7 – 299.2 kg ha−1), depending on growing conditions. Canopy temperature was generally correlated with soil volumetric water content (VWC), but the relationship was not consistently strong and depended on moisture sensor depth.http://www.sciencedirect.com/science/article/pii/S2772375523002204CottonCrop phenotypingHigh-throughput phenotypingInfrared temperaturePlant phenotypingRemote sensing |
| spellingShingle | Jeffrey Siegfried Nithya Rajan Curtis B. Adams Haly Neely Steve Hague Robert Hardin Ronnie Schnell Xiongzhe Han Alex Thomasson High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield Smart Agricultural Technology Cotton Crop phenotyping High-throughput phenotyping Infrared temperature Plant phenotyping Remote sensing |
| title | High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield |
| title_full | High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield |
| title_fullStr | High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield |
| title_full_unstemmed | High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield |
| title_short | High-accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems (UAS): Evaluating in-season prediction of yield |
| title_sort | high accuracy infrared thermography of cotton canopy temperature by unmanned aerial systems uas evaluating in season prediction of yield |
| topic | Cotton Crop phenotyping High-throughput phenotyping Infrared temperature Plant phenotyping Remote sensing |
| url | http://www.sciencedirect.com/science/article/pii/S2772375523002204 |
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