Title
3D Morphological Processing for Wheat Spike Phenotypes Using Computed Tomography Images.
Abstract
Wheat is the main food crop today world-wide. In order to improve its yields, researchers are committed to understand the relationships between wheat genotypes and phenotypes. Compared to progressive technology of wheat gene section identification, wheat trait measurement is mostly done manually in a destructive, labor-intensive and time-consuming way. Therefore, this study will be greatly accelerated and promoted if we can automatically discover wheat phenotype in a nondestructive and fast manner. In this paper, we propose a novel pipeline based on 3D morphological processing to detect wheat spike grains and stem nodes from 3D X-ray micro computed tomography (CT) images. We also introduce a set of newly defined 3D phenotypes, including grain aspect ratio, porosity, Grain-to-Grain distance, and grain angle, which are very difficult to be manually measured. The analysis of the associations among these traits would be very helpful for wheat breeding. Experimental results show that our method is able to count grains more accurately than normal human performance. By analyzing the relationships between traits and environment conditions, we find that the Grain-to-Grain distance, aspect ratio and porosity are more likely affected by the genome than environment (only tested temperature and water conditions). We also find that close grains will inhibit grain volume growth and that the aspect ratio 3.5 may be the best for higher yield in wheat breeding.
Year
DOI
Venue
2019
10.3390/rs11091110
REMOTE SENSING
Keywords
Field
DocType
3D morphological processing,3D phenotypes,X-ray micro computed tomography,image analysis,grain and stem detection
Computer vision,Morphological processing,Artificial intelligence,Computed tomography,Geology
Journal
Volume
Issue
Citations 
11
9
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Biao Xiong172.17
Bo Wang222453.43
Sheng-wu Xiong3132.16
Chengde Lin400.34
Xiao-Hui Yuan553475.44