Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits
Cereals grains are the prime component of the human diet worldwide. To promote food security and sustainability, new approaches to non-chemical weed control are needed. Early vigor cultivars with enhanced weed-competitiveness ability are a potential tool, nonetheless, the introduction of such trait...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/23/3877 |
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| author | Shlomi Aharon Zvi Peleg Eli Argaman Roi Ben-David Ran N. Lati |
| author_facet | Shlomi Aharon Zvi Peleg Eli Argaman Roi Ben-David Ran N. Lati |
| author_sort | Shlomi Aharon |
| collection | DOAJ |
| description | Cereals grains are the prime component of the human diet worldwide. To promote food security and sustainability, new approaches to non-chemical weed control are needed. Early vigor cultivars with enhanced weed-competitiveness ability are a potential tool, nonetheless, the introduction of such trait in breeding may be a long and labor-intensive process. Here, two image-driven plant phenotyping methods were evaluated to facilitate effective and accurate selection for early vigor in cereals. For that purpose, two triticale genotypes differentiating in vigor and growth rate early in the season were selected as model plants: X-1010 (high) and Triticale1 (low). Two modeling approaches, 2-D and 3-D, were applied on the plants offering an evaluation of various morphological growth parameters for the triticale canopy development, under controlled and field conditions. The morphological advantage of X-1010 was observed only at the initial growth stages, which was reflected by significantly higher growth parameter values compared to the Triticale1 genotype. Both modeling approaches were sensitive enough to detect phenotypic differences in growth as early as 21 days after sowing. All growth parameters indicated a faster early growth of X-1010. However, the 2-D related parameter [projected shoot area (PSA)] is the most available one that can be extracted via end user-friendly imaging equipment. PSA provided adequate indication for the triticale early growth under weed-competition conditions and for the improved weed-competition ability. The adequate phenotyping ability for early growth and competition was robust under controlled and field conditions. PSA can be extracted from close and remote sensing platforms, thus, facilitate high throughput screening. Overall, the results of this study may improve cereal breeding for early vigor and weed-competitiveness. |
| first_indexed | 2024-03-10T14:32:51Z |
| format | Article |
| id | doaj.art-39255852fa0e42a5822492511486beaa |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T14:32:51Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-39255852fa0e42a5822492511486beaa2023-11-20T22:26:32ZengMDPI AGRemote Sensing2072-42922020-11-011223387710.3390/rs12233877Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness TraitsShlomi Aharon0Zvi Peleg1Eli Argaman2Roi Ben-David3Ran N. Lati4Department of Plant Pathology and Weed Research, Newe Ya’ar Research Center, Agricultural Research Organization (ARO)-Volcani Center, Ramat Yishay 30095, IsraelThe Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot 7610001, IsraelSoil Erosion Research Station, Ministry of Agriculture and Rural Development, Rishon LeZion 7528809, IsraelInstitute of Plant Sciences, Agriculture Research Organization (ARO)-Volcani Center, Rishon LeZion 7528809, IsraelDepartment of Plant Pathology and Weed Research, Newe Ya’ar Research Center, Agricultural Research Organization (ARO)-Volcani Center, Ramat Yishay 30095, IsraelCereals grains are the prime component of the human diet worldwide. To promote food security and sustainability, new approaches to non-chemical weed control are needed. Early vigor cultivars with enhanced weed-competitiveness ability are a potential tool, nonetheless, the introduction of such trait in breeding may be a long and labor-intensive process. Here, two image-driven plant phenotyping methods were evaluated to facilitate effective and accurate selection for early vigor in cereals. For that purpose, two triticale genotypes differentiating in vigor and growth rate early in the season were selected as model plants: X-1010 (high) and Triticale1 (low). Two modeling approaches, 2-D and 3-D, were applied on the plants offering an evaluation of various morphological growth parameters for the triticale canopy development, under controlled and field conditions. The morphological advantage of X-1010 was observed only at the initial growth stages, which was reflected by significantly higher growth parameter values compared to the Triticale1 genotype. Both modeling approaches were sensitive enough to detect phenotypic differences in growth as early as 21 days after sowing. All growth parameters indicated a faster early growth of X-1010. However, the 2-D related parameter [projected shoot area (PSA)] is the most available one that can be extracted via end user-friendly imaging equipment. PSA provided adequate indication for the triticale early growth under weed-competition conditions and for the improved weed-competition ability. The adequate phenotyping ability for early growth and competition was robust under controlled and field conditions. PSA can be extracted from close and remote sensing platforms, thus, facilitate high throughput screening. Overall, the results of this study may improve cereal breeding for early vigor and weed-competitiveness.https://www.mdpi.com/2072-4292/12/23/3877crop heightcrop volumedronefood securitythree-dimensional modelMVS |
| spellingShingle | Shlomi Aharon Zvi Peleg Eli Argaman Roi Ben-David Ran N. Lati Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits Remote Sensing crop height crop volume drone food security three-dimensional model MVS |
| title | Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits |
| title_full | Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits |
| title_fullStr | Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits |
| title_full_unstemmed | Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits |
| title_short | Image-Based High-Throughput Phenotyping of Cereals Early Vigor and Weed-Competitiveness Traits |
| title_sort | image based high throughput phenotyping of cereals early vigor and weed competitiveness traits |
| topic | crop height crop volume drone food security three-dimensional model MVS |
| url | https://www.mdpi.com/2072-4292/12/23/3877 |
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