Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement
Wheat was one of the first grain crops domesticated by humans and remains among the major contributors to the global calorie and protein budget. The rapidly expanding world population demands further enhancement of yield and performance of wheat. Phenotypic information has historically been instrume...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/10/9/1287 |
| _version_ | 1797555130726350848 |
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| author | Cody S. Bekkering Jin Huang Li Tian |
| author_facet | Cody S. Bekkering Jin Huang Li Tian |
| author_sort | Cody S. Bekkering |
| collection | DOAJ |
| description | Wheat was one of the first grain crops domesticated by humans and remains among the major contributors to the global calorie and protein budget. The rapidly expanding world population demands further enhancement of yield and performance of wheat. Phenotypic information has historically been instrumental in wheat breeding for improved traits. In the last two decades, a steadily growing collection of tools and imaging software have given us the ability to quantify shoot, root, and seed traits with progressively increasing accuracy and throughput. This review discusses challenges and advancements in image analysis platforms for wheat phenotyping at the organ level. Perspectives on how these collective phenotypes can inform basic research on understanding wheat physiology and breeding for wheat improvement are also provided. |
| first_indexed | 2024-03-10T16:42:10Z |
| format | Article |
| id | doaj.art-9d98d8b48ac84376a11a311dcbd91e55 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T16:42:10Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-9d98d8b48ac84376a11a311dcbd91e552023-11-20T11:55:16ZengMDPI AGAgronomy2073-43952020-08-01109128710.3390/agronomy10091287Image-Based, Organ-Level Plant Phenotyping for Wheat ImprovementCody S. Bekkering0Jin Huang1Li Tian2Department of Plant Sciences, University of California, Davis, CA 95616, USADepartment of Plant Sciences, University of California, Davis, CA 95616, USADepartment of Plant Sciences, University of California, Davis, CA 95616, USAWheat was one of the first grain crops domesticated by humans and remains among the major contributors to the global calorie and protein budget. The rapidly expanding world population demands further enhancement of yield and performance of wheat. Phenotypic information has historically been instrumental in wheat breeding for improved traits. In the last two decades, a steadily growing collection of tools and imaging software have given us the ability to quantify shoot, root, and seed traits with progressively increasing accuracy and throughput. This review discusses challenges and advancements in image analysis platforms for wheat phenotyping at the organ level. Perspectives on how these collective phenotypes can inform basic research on understanding wheat physiology and breeding for wheat improvement are also provided.https://www.mdpi.com/2073-4395/10/9/1287wheatphenotypephenotypingphenephenomicsshoot |
| spellingShingle | Cody S. Bekkering Jin Huang Li Tian Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement Agronomy wheat phenotype phenotyping phene phenomics shoot |
| title | Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement |
| title_full | Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement |
| title_fullStr | Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement |
| title_full_unstemmed | Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement |
| title_short | Image-Based, Organ-Level Plant Phenotyping for Wheat Improvement |
| title_sort | image based organ level plant phenotyping for wheat improvement |
| topic | wheat phenotype phenotyping phene phenomics shoot |
| url | https://www.mdpi.com/2073-4395/10/9/1287 |
| work_keys_str_mv | AT codysbekkering imagebasedorganlevelplantphenotypingforwheatimprovement AT jinhuang imagebasedorganlevelplantphenotypingforwheatimprovement AT litian imagebasedorganlevelplantphenotypingforwheatimprovement |