Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy
Abstract
:1. Introduction
2. Materials and Methods
2.1. Cannabis Samples
2.2. Chromatographic Reference Measurements
2.3. NIR Spectroscopy
2.3.1. Spectrometer Modules
2.3.2. NIR Data Set
2.4. Chemometric Data Evaluation
2.4.1. Preprocessing of NIR Spectral Data
2.4.2. Partial Least Squares Methods (PLS-R, PLS-DA, iPLS)
3. Results
3.1. Design of a Portable NIR-Based Sensor for Classification of Cannabis Samples
- Little to no sample preparation before the measurement.
- Non-destructive measurement of the sample.
- Measurement must be possible through a transparent plastic bag.
- Measurement time < 20 s.
- Sensor startup time < 60 s.
- Data evaluation directly on the device (no cloud computing).
- Visual indicator of the classification result on the device.
- Possibility for one-handed operation.
- Connection to a smartphone where measurement reports can be created and saved.
3.1.1. Choosing the Most Suitable Non-Destructive Measurement Technology
3.1.2. Electrical Design
- Green color indicates that the measured sample contains less than the threshold value of THC.
- Red color indicates that the sample contains more than the threshold value of THC.
- Yellow color means that the measurement outcome is uncertain.
3.1.3. Mechanical Sensor Design
3.1.4. Conducting a Measurement
3.2. Measurement Results
3.2.1. PLS-DA Model Calibration
3.2.2. PLS-DA Model Validation
4. Discussion and Conclusions
5. Patents
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Samples | Correct Classifications | Wrong Classifications | Uncertain Predictions |
---|---|---|---|
All measured samples | 70.4% | 19.0% | 10.6% |
Excluding uncertain predictions * | 78.7% | 21.3% | - |
Class 1 samples (≤0.4 wt% THC) | 79.1% | 20.9% | - |
Class 2 samples (>0.4 wt% THC) | 78.6% | 21.4% | - |
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Zimmerleiter, R.; Greibl, W.; Meininger, G.; Duswald, K.; Hannesschläger, G.; Gattinger, P.; Rohm, M.; Fuczik, C.; Holzer, R.; Brandstetter, M. Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy. Sensors 2024, 24, 3188. https://doi.org/10.3390/s24103188
Zimmerleiter R, Greibl W, Meininger G, Duswald K, Hannesschläger G, Gattinger P, Rohm M, Fuczik C, Holzer R, Brandstetter M. Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy. Sensors. 2024; 24(10):3188. https://doi.org/10.3390/s24103188
Chicago/Turabian StyleZimmerleiter, Robert, Wolfgang Greibl, Gerold Meininger, Kristina Duswald, Günther Hannesschläger, Paul Gattinger, Matthias Rohm, Christian Fuczik, Robert Holzer, and Markus Brandstetter. 2024. "Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy" Sensors 24, no. 10: 3188. https://doi.org/10.3390/s24103188
APA StyleZimmerleiter, R., Greibl, W., Meininger, G., Duswald, K., Hannesschläger, G., Gattinger, P., Rohm, M., Fuczik, C., Holzer, R., & Brandstetter, M. (2024). Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy. Sensors, 24(10), 3188. https://doi.org/10.3390/s24103188