Utilization of Spectral Indices for High-Throughput Phenotyping
The conventional plant breeding evaluation of large sets of plant phenotypes with precision and speed is very challenging. Thus, consistent, automated, multifaceted, and high-throughput phenotyping (HTP) technologies are becoming increasingly significant as tools to aid conventional breeding program...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Plants |
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| Online Access: | https://www.mdpi.com/2223-7747/11/13/1712 |
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| author | Rupesh Tayade Jungbeom Yoon Liny Lay Abdul Latif Khan Youngnam Yoon Yoonha Kim |
| author_facet | Rupesh Tayade Jungbeom Yoon Liny Lay Abdul Latif Khan Youngnam Yoon Yoonha Kim |
| author_sort | Rupesh Tayade |
| collection | DOAJ |
| description | The conventional plant breeding evaluation of large sets of plant phenotypes with precision and speed is very challenging. Thus, consistent, automated, multifaceted, and high-throughput phenotyping (HTP) technologies are becoming increasingly significant as tools to aid conventional breeding programs to develop genetically improved crops. With rapid technological advancement, various vegetation indices (VIs) have been developed. These VI-based imaging approaches, linked with artificial intelligence and a variety of remote sensing applications, provide high-throughput evaluations, particularly in the field of precision agriculture. VIs can be used to analyze and predict different quantitative and qualitative aspects of vegetation. Here, we provide an overview of the various VIs used in agricultural research, focusing on those that are often employed for crop or vegetation evaluation, because that has a linear relationship to crop output, which is frequently utilized in crop chlorophyll, health, moisture, and production predictions. In addition, the following aspects are here described: the importance of VIs in crop research and precision agriculture, their utilization in HTP, recent photogrammetry technology, mapping, and geographic information system software integrated with unmanned aerial vehicles and its key features. Finally, we discuss the challenges and future perspectives of HTP technologies and propose approaches for the development of new tools to assess plants’ agronomic traits and data-driven HTP resolutions for precision breeding. |
| first_indexed | 2024-03-09T12:39:39Z |
| format | Article |
| id | doaj.art-377672f0d03149388f32b73ff2c773c0 |
| institution | Directory Open Access Journal |
| issn | 2223-7747 |
| language | English |
| last_indexed | 2024-03-09T12:39:39Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Plants |
| spelling | doaj.art-377672f0d03149388f32b73ff2c773c02023-11-30T22:19:30ZengMDPI AGPlants2223-77472022-06-011113171210.3390/plants11131712Utilization of Spectral Indices for High-Throughput PhenotypingRupesh Tayade0Jungbeom Yoon1Liny Lay2Abdul Latif Khan3Youngnam Yoon4Yoonha Kim5Department of Applied Biosciences, Kyungpook National University, Daegu 41566, KoreaHorticultural and Herbal Crop Environment Division, National Institute of Horticultural and Herbal Science, Rural Development Administration, Wanju 55365, KoreaDepartment of Applied Biosciences, Kyungpook National University, Daegu 41566, KoreaDepartment of Engineering Technology, University of Houston, Texas, TX 77204, USACrop Production Technology Research Division, National Institute of Crop Science, Rural Development Administration, Miryang 50424, KoreaDepartment of Applied Biosciences, Kyungpook National University, Daegu 41566, KoreaThe conventional plant breeding evaluation of large sets of plant phenotypes with precision and speed is very challenging. Thus, consistent, automated, multifaceted, and high-throughput phenotyping (HTP) technologies are becoming increasingly significant as tools to aid conventional breeding programs to develop genetically improved crops. With rapid technological advancement, various vegetation indices (VIs) have been developed. These VI-based imaging approaches, linked with artificial intelligence and a variety of remote sensing applications, provide high-throughput evaluations, particularly in the field of precision agriculture. VIs can be used to analyze and predict different quantitative and qualitative aspects of vegetation. Here, we provide an overview of the various VIs used in agricultural research, focusing on those that are often employed for crop or vegetation evaluation, because that has a linear relationship to crop output, which is frequently utilized in crop chlorophyll, health, moisture, and production predictions. In addition, the following aspects are here described: the importance of VIs in crop research and precision agriculture, their utilization in HTP, recent photogrammetry technology, mapping, and geographic information system software integrated with unmanned aerial vehicles and its key features. Finally, we discuss the challenges and future perspectives of HTP technologies and propose approaches for the development of new tools to assess plants’ agronomic traits and data-driven HTP resolutions for precision breeding.https://www.mdpi.com/2223-7747/11/13/1712hyperspectral imagevegetation indiceshigh-throughput phenotypingremote sensingunmanned aerial vehicles |
| spellingShingle | Rupesh Tayade Jungbeom Yoon Liny Lay Abdul Latif Khan Youngnam Yoon Yoonha Kim Utilization of Spectral Indices for High-Throughput Phenotyping Plants hyperspectral image vegetation indices high-throughput phenotyping remote sensing unmanned aerial vehicles |
| title | Utilization of Spectral Indices for High-Throughput Phenotyping |
| title_full | Utilization of Spectral Indices for High-Throughput Phenotyping |
| title_fullStr | Utilization of Spectral Indices for High-Throughput Phenotyping |
| title_full_unstemmed | Utilization of Spectral Indices for High-Throughput Phenotyping |
| title_short | Utilization of Spectral Indices for High-Throughput Phenotyping |
| title_sort | utilization of spectral indices for high throughput phenotyping |
| topic | hyperspectral image vegetation indices high-throughput phenotyping remote sensing unmanned aerial vehicles |
| url | https://www.mdpi.com/2223-7747/11/13/1712 |
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