Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging
Abstract Developing the resilient crops of the future will require access to a broad set of tools. While advances in sequencing and marker technologies have facilitated marker‐trait associations and the ability to predict the phenotype of an individual from its genotypic information, other tools suc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Plant Phenome Journal |
| Online Access: | https://doi.org/10.1002/ppj2.20044 |
| _version_ | 1797976287147458560 |
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| author | Dorothy D. Sweet Sara B. Tirado Nathan M. Springer Candice N. Hirsch Cory D. Hirsch |
| author_facet | Dorothy D. Sweet Sara B. Tirado Nathan M. Springer Candice N. Hirsch Cory D. Hirsch |
| author_sort | Dorothy D. Sweet |
| collection | DOAJ |
| description | Abstract Developing the resilient crops of the future will require access to a broad set of tools. While advances in sequencing and marker technologies have facilitated marker‐trait associations and the ability to predict the phenotype of an individual from its genotypic information, other tools such as high‐throughput phenotyping are still in their infancy. Advances in sensors, aeronautics, and computing have enabled progress. Here, we review current platforms and sensors available for top‐down field phenotyping with a focus on unoccupied aerial vehicles (UAVs) and red, green, blue sensors. We also review the ability and effectiveness of extracting traits from images captured using combinations of these platforms and sensors. Improvements in trait standardization and extraction software are expected to increase the use of high‐throughput phenotyping in the coming years and further facilitate crop improvement. |
| first_indexed | 2024-04-11T04:48:36Z |
| format | Article |
| id | doaj.art-306ef6940a3f4f139ed18b867a70ed38 |
| institution | Directory Open Access Journal |
| issn | 2578-2703 |
| language | English |
| last_indexed | 2024-04-11T04:48:36Z |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Plant Phenome Journal |
| spelling | doaj.art-306ef6940a3f4f139ed18b867a70ed382022-12-27T06:00:36ZengWileyPlant Phenome Journal2578-27032022-01-0151n/an/a10.1002/ppj2.20044Opportunities and challenges in phenotyping row crops using drone‐based RGB imagingDorothy D. Sweet0Sara B. Tirado1Nathan M. Springer2Candice N. Hirsch3Cory D. Hirsch4Dep. of Agronomy and Plant Genetics Univ. of Minnesota Saint Paul MN 55108 USADep. of Agronomy and Plant Genetics Univ. of Minnesota Saint Paul MN 55108 USADep. of Plant and Microbial Biology Univ. of Minnesota Saint Paul MN 55108 USADep. of Agronomy and Plant Genetics Univ. of Minnesota Saint Paul MN 55108 USADep. of Plant Pathology Univ. of Minnesota Saint Paul MN 55108 USAAbstract Developing the resilient crops of the future will require access to a broad set of tools. While advances in sequencing and marker technologies have facilitated marker‐trait associations and the ability to predict the phenotype of an individual from its genotypic information, other tools such as high‐throughput phenotyping are still in their infancy. Advances in sensors, aeronautics, and computing have enabled progress. Here, we review current platforms and sensors available for top‐down field phenotyping with a focus on unoccupied aerial vehicles (UAVs) and red, green, blue sensors. We also review the ability and effectiveness of extracting traits from images captured using combinations of these platforms and sensors. Improvements in trait standardization and extraction software are expected to increase the use of high‐throughput phenotyping in the coming years and further facilitate crop improvement.https://doi.org/10.1002/ppj2.20044 |
| spellingShingle | Dorothy D. Sweet Sara B. Tirado Nathan M. Springer Candice N. Hirsch Cory D. Hirsch Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging Plant Phenome Journal |
| title | Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging |
| title_full | Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging |
| title_fullStr | Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging |
| title_full_unstemmed | Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging |
| title_short | Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging |
| title_sort | opportunities and challenges in phenotyping row crops using drone based rgb imaging |
| url | https://doi.org/10.1002/ppj2.20044 |
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