Preliminary Studies on Detection of Fusarium Basal Rot Infection in Onions and Shallots Using Electronic Nose
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sample Preparation
2.2. Electronic Nose Measurements
2.3. Data Analysis
3. Results
3.1. Visual Examination of the Fusarium Basal Rot Symptoms
3.2. Sensor Array Responses
3.3. PCA
3.4. Classification of the Samples
- Classify samples with onion bulbs in terms of the proportion of infected to healthy bulbs (3 classes), i.e., non-infected (0%), mildly diseased (20–40% infected bulbs), and severe diseased (60–100% infected bulbs);
- Differentiate among samples containing non-infected (0%) and infected (100%) onion and shallot bulbs (two classes);
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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No | Producent’s Designation | General Description |
---|---|---|
1 | W1C | aromatic compounds |
2 | W5S | broad range of compounds, nitrogen oxides |
3 | W3C | ammonia, aromatic compounds |
4 | W6S | Hydrogen |
5 | W5C | alkenes, aromatic compounds |
6 | W1S | methane, broad range of compounds |
7 | W1W | sulphur-organic compounds |
8 | W2S | alcohols, broad range of organic compounds |
9 | W2W | aromatic compounds, sulphur organic compounds |
10 | W3S | alkenes, aliphatic organic compounds |
3 Class Classification | 2 Class Classification | |||||
---|---|---|---|---|---|---|
Accuracy | Recall | F1 Score | Accuracy | Recall | F1 Score | |
LDA | 89.60% | 0.90 | 0.92 | 93.80% | 0.88 | 0.93 |
LDA 5 sensors | 66.70% | 0.67 | 0.74 | 90.60% | 0.81 | 0.90 |
SVM linear | 79.20% | 0.79 | 0.84 | 87.50% | 0.75 | 0.86 |
SVM optimized | 87.50% | 0.83 | 0.87 | 96.90% | 0.94 | 0.97 |
k-NN optimized | 89.60% | 0.90 | 0.92 | 93.80% | 0.88 | 0.93 |
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Labanska, M.; van Amsterdam, S.; Jenkins, S.; Clarkson, J.P.; Covington, J.A. Preliminary Studies on Detection of Fusarium Basal Rot Infection in Onions and Shallots Using Electronic Nose. Sensors 2022, 22, 5453. https://doi.org/10.3390/s22145453
Labanska M, van Amsterdam S, Jenkins S, Clarkson JP, Covington JA. Preliminary Studies on Detection of Fusarium Basal Rot Infection in Onions and Shallots Using Electronic Nose. Sensors. 2022; 22(14):5453. https://doi.org/10.3390/s22145453
Chicago/Turabian StyleLabanska, Malgorzata, Sarah van Amsterdam, Sascha Jenkins, John P. Clarkson, and James A. Covington. 2022. "Preliminary Studies on Detection of Fusarium Basal Rot Infection in Onions and Shallots Using Electronic Nose" Sensors 22, no. 14: 5453. https://doi.org/10.3390/s22145453
APA StyleLabanska, M., van Amsterdam, S., Jenkins, S., Clarkson, J. P., & Covington, J. A. (2022). Preliminary Studies on Detection of Fusarium Basal Rot Infection in Onions and Shallots Using Electronic Nose. Sensors, 22(14), 5453. https://doi.org/10.3390/s22145453