High-Throughput Phenotyping Approach for the Evaluation of Heat Stress in Korean Ginseng (Panax ginseng Meyer) Using a Hyperspectral Reflectance Image
Abstract
:1. Introduction
2. Materials and Methods
2.1. Plant Materials, Environmental Conditions and Heat Treatment
2.2. HSI Systems and Image Acquisition
2.3. Data Extraction
2.4. Multivariate Analysis for Classification
2.4.1. Linear Discriminant Analysis (LDA)
2.4.2. Partial Least Squares Discriminant Analysis (PLS-DA)
2.4.3. Main Wavebands Selection for the Classification
3. Results
3.1. Spectral Profile of Ginseng
3.2. LDA Analysis
3.3. PLS-DA Model Results and Main Wavebands Coefficient
3.3.1. Vis/NIR and SWIR Data Analysis
3.3.2. PLS-DA-Based Images for Heat Stress Detection
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Total | Correct | Accuracy (%) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
BH | AR | AS | BH | AR | AS | BH | AR | AS | Overall | ||||
Vis/ NIR | BPV | Full | Cal * | 251 | 128 | 96 | 231 | 113 | 59 | 92.0 | 88.3 | 61.5 | 80.6 |
Val * | 126 | 64 | 48 | 110 | 57 | 22 | 87.3 | 89.1 | 45.8 | 74.1 | |||
Main | Cal | 251 | 128 | 96 | 229 | 113 | 57 | 91.2 | 88.3 | 59.4 | 79.6 | ||
Val | 126 | 64 | 48 | 108 | 57 | 24 | 85.7 | 89.1 | 50.0 | 74.9 | |||
SPRI | Full | Cal | 251 | 128 | 96 | 218 | 118 | 68 | 86.9 | 92.2 | 70.8 | 83.3 | |
Val | 126 | 64 | 48 | 105 | 58 | 27 | 83.3 | 90.6 | 56.3 | 76.7 | |||
Main | Cal | 251 | 128 | 96 | 230 | 115 | 60 | 91.6 | 89.8 | 62.5 | 81.3 | ||
Val | 126 | 64 | 48 | 117 | 58 | 26 | 92.9 | 90.6 | 54.2 | 79.2 | |||
SWIR | BPV | Full | Cal | 251 | 85 | 113 | 251 | 81 | 97 | 100.0 | 95.3 | 85.8 | 93.7 |
Val | 126 | 42 | 56 | 126 | 38 | 51 | 100.0 | 90.5 | 91.1 | 93.8 | |||
Main | Cal | 251 | 85 | 113 | 251 | 75 | 84 | 100.0 | 88.2 | 74.3 | 87.5 | ||
Val | 126 | 42 | 56 | 126 | 33 | 47 | 100.0 | 78.6 | 83.9 | 87.5 | |||
SPRI | Full | Cal | 251 | 85 | 113 | 250 | 85 | 113 | 99.6 | 100.0 | 100.0 | 99.9 | |
Val | 126 | 42 | 56 | 126 | 42 | 56 | 100.0 | 100.0 | 100.0 | 100.0 | |||
Main | Cal | 251 | 85 | 113 | 250 | 85 | 112 | 99.6 | 100.0 | 99.1 | 99.6 | ||
Val | 126 | 42 | 56 | 125 | 41 | 56 | 99.2 | 97.6 | 100.0 | 98.9 |
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Park, E.; Kim, Y.-S.; Omari, M.K.; Suh, H.-K.; Faqeerzada, M.A.; Kim, M.S.; Baek, I.; Cho, B.-K. High-Throughput Phenotyping Approach for the Evaluation of Heat Stress in Korean Ginseng (Panax ginseng Meyer) Using a Hyperspectral Reflectance Image. Sensors 2021, 21, 5634. https://doi.org/10.3390/s21165634
Park E, Kim Y-S, Omari MK, Suh H-K, Faqeerzada MA, Kim MS, Baek I, Cho B-K. High-Throughput Phenotyping Approach for the Evaluation of Heat Stress in Korean Ginseng (Panax ginseng Meyer) Using a Hyperspectral Reflectance Image. Sensors. 2021; 21(16):5634. https://doi.org/10.3390/s21165634
Chicago/Turabian StylePark, Eunsoo, Yun-Soo Kim, Mohammad Kamran Omari, Hyun-Kwon Suh, Mohammad Akbar Faqeerzada, Moon S. Kim, Insuck Baek, and Byoung-Kwan Cho. 2021. "High-Throughput Phenotyping Approach for the Evaluation of Heat Stress in Korean Ginseng (Panax ginseng Meyer) Using a Hyperspectral Reflectance Image" Sensors 21, no. 16: 5634. https://doi.org/10.3390/s21165634