| Autor: |
Xiao Feng, Zhiqi Wang, Zhiwei Zeng, Yuhao Zhou, Yunting Lan, Wei Zou, Hao Gong, Long Qi |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Frontiers in Plant Science, Vol 14 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1664-462X |
| DOI: |
10.3389/fpls.2023.1213486 |
| Popis: |
Measurements of rice physical traits, such as length, width, and percentage of filled/unfilled grains, are essential steps of rice breeding. A new approach for measuring the physical traits of rice grains for breeding purposes was presented in this study, utilizing image processing techniques. Backlight photography was used to capture a grayscale image of a group of rice grains, which was then analyzed using a clustering algorithm to differentiate between filled and unfilled grains based on their grayscale values. The impact of backlight intensity on the accuracy of the method was also investigated. The results show that the proposed method has excellent accuracy and high efficiency. The mean absolute percentage error of the method was 0.24% and 1.36% in calculating the total number of grain particles and distinguishing the number of filled grains, respectively. The grain size was also measured with a little margin of error. The mean absolute percentage error of grain length measurement was 1.11%, while the measurement error of grain width was 4.03%. The method was found to be highly accurate, non-destructive, and cost-effective when compared to conventional methods, making it a promising approach for characterizing physical traits for crop breeding. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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