3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism
Abstract
:1. Introduction
2. Materials and Methods
2.1. Image Acquisition and Analysis
2.2. Plant Segmentation and Parameter Extraction
2.3. Minirhizotron Experiments
2.4. Statistical Analysis
3. Results
3.1. O. Cumana Parasitism Dynamics: Minirhizotron Experiments
3.2. 3-D Reconstruction and Internode Estimation
3.3. Morphological Analysis for O. Cumana Detection
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Parameter | Estimate | SE |
---|---|---|
a | 6.62 | 0.42 |
x0 | 1000.18 | 34.69 |
b | −6.37 | 1.17 |
R2 | 0.98 | |
p | <0.0001 | |
RMSE | 0.32 |
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Lati, R.N.; Filin, S.; Elnashef, B.; Eizenberg, H. 3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism. Sensors 2019, 19, 1569. https://doi.org/10.3390/s19071569
Lati RN, Filin S, Elnashef B, Eizenberg H. 3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism. Sensors. 2019; 19(7):1569. https://doi.org/10.3390/s19071569
Chicago/Turabian StyleLati, Ran Nisim, Sagi Filin, Bashar Elnashef, and Hanan Eizenberg. 2019. "3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism" Sensors 19, no. 7: 1569. https://doi.org/10.3390/s19071569