We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
High-Throughput Phenotyping of Seed/Seedling Evaluation Using Digital Image Analysis.
- Authors
Chongyuan Zhang; Yongsheng Si; Lamkey, Jacob; Boydston, Rick A.; Garland-Campbell, Kimberly A.; Sankaran, Sindhuja
- Abstract
Image-based evaluation of phenotypic traits has been applied for plant architecture, seed, canopy growth/vigor, and root characterization. However, such applications using computer vision have not been exploited for the purpose of assessing the coleoptile length and herbicide injury in seeds. In this study, high-throughput phenotyping using digital image analysis was applied to evaluate seed/seedling traits. Images of seeds or seedlings were acquired using a commercial digital camera and analyzed using custom-developed image processing algorithms. Results from two case studies demonstrated that it was possible to use image-based high-throughput phenotyping to assess seeds/seedlings. In the seedling evaluation study, using a color-based detection method, image-based and manual coleoptile length were positively and significantly correlated (p < 0.0001) with reasonable accuracy (r = 0.69-0.91). As well, while using a width-and-color-based detection method, the correlation coefficient was also significant (p < 0.0001, r = 0.89). The improvement of the germination protocol designed for imaging will increase the throughput and accuracy of coleoptile detection using image processing methods. In the herbicide study, using image-based features, differences between injured and uninjured seedlings can be detected. In the presence of the treatment differences, such a technique can be applied for non-biased symptom rating.
- Subjects
IMAGE processing; COLEOPTILES; PLANT roots; SEEDS; SEEDLINGS
- Publication
Agronomy, 2018, Vol 8, Issue 5, p63
- ISSN
2073-4395
- Publication type
Article
- DOI
10.3390/agronomy8050063