Hyperspectral imaging for agricultural applications provides a solution for non-destructive, large-area crop monitoring. However, current products are bulky and expensive due to complicated optics and electronics. A linear variable filter was developed for implementation into a prototype hyperspectral imaging camera that demonstrates good spectral performance between 450 and 900 nm. Equipped with a feature extraction and classification algorithm, the proposed system can be used to determine potato plant health with ∼88% accuracy. This algorithm was also capable of species identification and is demonstrated as being capable of differentiating between rocket, lettuce, and spinach. Results are promising for an entry-level, low-cost hyperspectral imaging solution for agriculture applications.
Song, S., Gibson, D., Ahmadzadeh, S., Chu, H. O., Warden, B., Overend, R., MacFarlane, F., Murray, P., Marshall, S., Aitkenhead, M., Bienkowski, D., & Allison, R. (2020). Low-cost hyper-spectral imaging system using a linear variable bandpass filter for agritech applications. Applied Optics, 59(5), A167-A175. https://doi.org/10.1364/AO.378269