Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping
Safflower (<i>Carthamus tinctorius</i> L.) is a highly adaptable but underutilized oilseed crop capable of growing in marginal environments, with crucial agronomical, commercial, and industrial uses. Considerable research is still needed to develop commercially relevant varieties, requir...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/13/3/620 |
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| author | Emily Thoday-Kennedy Bikram Banerjee Joe Panozzo Pankaj Maharjan David Hudson German Spangenberg Matthew Hayden Surya Kant |
| author_facet | Emily Thoday-Kennedy Bikram Banerjee Joe Panozzo Pankaj Maharjan David Hudson German Spangenberg Matthew Hayden Surya Kant |
| author_sort | Emily Thoday-Kennedy |
| collection | DOAJ |
| description | Safflower (<i>Carthamus tinctorius</i> L.) is a highly adaptable but underutilized oilseed crop capable of growing in marginal environments, with crucial agronomical, commercial, and industrial uses. Considerable research is still needed to develop commercially relevant varieties, requiring effective, high-throughput digital phenotyping to identify key selection traits. In this study, field trials comprising a globally diverse collection of 350 safflower genotypes were conducted during 2017–2019. Crop traits assessed included phenology, grain yield, and oil quality, as well as unmanned aerial vehicle (UAV) multispectral data for estimating vegetation indices. Phenotypic traits and crop performance were highly dependent on environmental conditions, especially rainfall. High-performing genotypes had intermediate growth and phenology, with spineless genotypes performing similarly to spiked genotypes. Phenology parameters were significantly correlated to height, with significantly weak interaction with yield traits. The genotypes produced total oil content values ranging from 20.6–41.07%, oleic acid values ranging 7.57–74.5%, and linoleic acid values ranging from 17.0–83.1%. Multispectral data were used to model crop height, NDVI and EVI changes, and crop yield. NDVI data identified the start of flowering and dissected genotypes according to flowering class, growth pattern, and yield estimation. Overall, UAV-multispectral derived data are applicable to phenotyping key agronomical traits in large collections suitable for safflower breeding programs. |
| first_indexed | 2024-03-11T07:04:52Z |
| format | Article |
| id | doaj.art-a6623f6a28644e629f72dc11cecf28f9 |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-11T07:04:52Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-a6623f6a28644e629f72dc11cecf28f92023-11-17T09:01:04ZengMDPI AGAgriculture2077-04722023-03-0113362010.3390/agriculture13030620Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal PhenotypingEmily Thoday-Kennedy0Bikram Banerjee1Joe Panozzo2Pankaj Maharjan3David Hudson4German Spangenberg5Matthew Hayden6Surya Kant7Agriculture Victoria, Grains Innovation Park, 110 Natimuk Rd., Horsham, VIC 3400, AustraliaAgriculture Victoria, Grains Innovation Park, 110 Natimuk Rd., Horsham, VIC 3400, AustraliaAgriculture Victoria, Grains Innovation Park, 110 Natimuk Rd., Horsham, VIC 3400, AustraliaAgriculture Victoria, Grains Innovation Park, 110 Natimuk Rd., Horsham, VIC 3400, AustraliaGO Resources Pty Ltd., 15 Sutherland Street, Brunswick, VIC 3056, AustraliaSchool of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, AustraliaSchool of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, AustraliaAgriculture Victoria, Grains Innovation Park, 110 Natimuk Rd., Horsham, VIC 3400, AustraliaSafflower (<i>Carthamus tinctorius</i> L.) is a highly adaptable but underutilized oilseed crop capable of growing in marginal environments, with crucial agronomical, commercial, and industrial uses. Considerable research is still needed to develop commercially relevant varieties, requiring effective, high-throughput digital phenotyping to identify key selection traits. In this study, field trials comprising a globally diverse collection of 350 safflower genotypes were conducted during 2017–2019. Crop traits assessed included phenology, grain yield, and oil quality, as well as unmanned aerial vehicle (UAV) multispectral data for estimating vegetation indices. Phenotypic traits and crop performance were highly dependent on environmental conditions, especially rainfall. High-performing genotypes had intermediate growth and phenology, with spineless genotypes performing similarly to spiked genotypes. Phenology parameters were significantly correlated to height, with significantly weak interaction with yield traits. The genotypes produced total oil content values ranging from 20.6–41.07%, oleic acid values ranging 7.57–74.5%, and linoleic acid values ranging from 17.0–83.1%. Multispectral data were used to model crop height, NDVI and EVI changes, and crop yield. NDVI data identified the start of flowering and dissected genotypes according to flowering class, growth pattern, and yield estimation. Overall, UAV-multispectral derived data are applicable to phenotyping key agronomical traits in large collections suitable for safflower breeding programs.https://www.mdpi.com/2077-0472/13/3/620EVIfloweringhigh-throughput phenotypingNDVIoil profilesafflower |
| spellingShingle | Emily Thoday-Kennedy Bikram Banerjee Joe Panozzo Pankaj Maharjan David Hudson German Spangenberg Matthew Hayden Surya Kant Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping Agriculture EVI flowering high-throughput phenotyping NDVI oil profile safflower |
| title | Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping |
| title_full | Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping |
| title_fullStr | Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping |
| title_full_unstemmed | Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping |
| title_short | Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping |
| title_sort | dissecting physiological and agronomic diversity in safflower populations using proximal phenotyping |
| topic | EVI flowering high-throughput phenotyping NDVI oil profile safflower |
| url | https://www.mdpi.com/2077-0472/13/3/620 |
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