Automated Visual Identification of Foliage Chlorosis in Lettuce Grown in Aquaponic Systems
Abstract
:1. Introduction
2. Related Work
3. Research Methodology
3.1. Data Preparation
3.2. Image Segmentation
3.2.1. HSV Color Space
3.2.2. Image Hue Thresholding
3.3. Foliage Color Detection Model Development
3.4. Ontology Model
3.5. Cloud-Based Application
4. Results and Discussion
- True Positive (TP) = 58. Thus, 58 plants were healthy, and the model correctly classified them healthy as well.
- True Negative (TN) = 57. Thus, 57 plants were unhealthy, and the model correctly classified them unhealthy as well.
- False Positive (FP) = 3. Thus, 3 plants were unhealthy, but the model incorrectly classified them as healthy.
- False Negative (FN) = 2. Thus, 2 plants were healthy, but the model incorrectly classified them as unhealthy.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
References
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Class | N (Truth) | N (Classified) | Accuracy | Precision | Recall | F1-Score |
---|---|---|---|---|---|---|
Q = 1 | 60 | 61 | 0.95 | 0.95 | 0.97 | 0.96 |
Q = 0 | 60 | 59 | 0.95 | 0.97 | 0.95 | 0.96 |
Average | - | - | 0.95 | 0.96 | 0.96 | 0.96 |
Methods | Techniques and Parameters Used | Average Accuracy | Average Precision | Average Recall | Average F1-Score |
---|---|---|---|---|---|
Yang et al. [18] | SVM (support vector machine) and a* (CIELAB color space), G (green from RGB color space), and H (hue from HSV color space) | 0.91 | 0.92 | 0.93 | 0.925 |
Maity et al. [19] | Otsu’s method and k-means clustering technique | 0.92 | 0.93 | 0.93 | 0.93 |
Yang et al. [20] | HSV (hue, saturation, and value) color space and decision tree method | 0.89 | 0.91 | 0.90 | 0.905 |
Luna-Benoso et al. [21] | Otsu’s method, SVM, k-NN (k-nearest neighbor) and MLP (multi-layer perceptron) | 0.90 | 0.91 | 0.91 | 0.91 |
Hasan et al. [25] | L*a*b* color histogram, k-NN, and random forest | 0.94 | 0.95 | 0.94 | 0.945 |
- | Proposed model | 0.95 | 0.96 | 0.96 | 0.96 |
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Abbasi, R.; Martinez, P.; Ahmad, R. Automated Visual Identification of Foliage Chlorosis in Lettuce Grown in Aquaponic Systems. Agriculture 2023, 13, 615. https://doi.org/10.3390/agriculture13030615
Abbasi R, Martinez P, Ahmad R. Automated Visual Identification of Foliage Chlorosis in Lettuce Grown in Aquaponic Systems. Agriculture. 2023; 13(3):615. https://doi.org/10.3390/agriculture13030615
Chicago/Turabian StyleAbbasi, Rabiya, Pablo Martinez, and Rafiq Ahmad. 2023. "Automated Visual Identification of Foliage Chlorosis in Lettuce Grown in Aquaponic Systems" Agriculture 13, no. 3: 615. https://doi.org/10.3390/agriculture13030615