Name
Abstract | ||
|---|---|---|
Plant Phenotyping consists in characterizing their morphometric pa-rameters which allows correlating them to genotype expression, modulated by their environment. Particularly, nutrition and environment of plants impact significantly roots and symbiotic nodules growths. Under conditions of low mineral nitrogen in soil, legumes have the ability to fix atmospheric nitrogen symbiotically in nodules which are organs formed on the roots of the host plant. The observation of nodules and the evaluation of their characteristics are quite difficult manually, and commercial software provide currently time consuming and no accurate results. This paper proposes a fast and automated image processing technique using the skeletonization technique to determine very accurately nodule parameters, such as their number, location and size on the primary root. The results obtained will be used for the determination of other root parameters including dynamic follow of root architecture. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-23117-4_12 | CAIP |
Keywords | Field | DocType |
Phenotyping, Nodules detection, Skeletonization, Imagery, Automatic | Plant phenotyping,Computer vision,Pattern recognition,Computer science,Image processing,Commercial software,Skeletonization,Artificial intelligence | Conference |
Volume | ISSN | Citations |
9257 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simeng Han | 1 | 0 | 0.34 |
| Frederic Cointault | 2 | 16 | 4.79 |
| Christophe Salon | 3 | 0 | 0.34 |
| Jean-Claude Simon | 4 | 7 | 1.56 |