The use of spectroscopic techniques to monitor plant health is becoming increasingly popular in precision agriculture. In this paper, we present a potential application of the Hamamatsu C12880MA spectrophotometer to study leaf surface reflectance in the spectral range from 350 nm to 850 nm. This instrument was placed near a black cloth to reduce the ambient noise and the leaves placed on the surface and they are illuminated by a lamp. This light is polarized by a polarizer located on Hamamatsu, and the reflected signal is collected by the C12880MA spectrophotometer connected to the ARDUINO UNO R4 microcontroller. From reflectance analyses, through a machine learning MLP (Multi-Layer Perceptron) model, it is possible to trace back to the corresponding pantone color of the leaf, which in turn can provide us with indications about its health status.
Leccisi, M., Fina, F., Leccese, F. (2025). A Low-Cost Portable Spectrophotometer for Precision Agriculture based on Hamamatsu C12880MA. In Conference Proceedings - 2025 IEEE International Workshop on Metrology for Agriculture and Forestry, MetroAgriFor 2025 (pp.342-347). Institute of Electrical and Electronics Engineers Inc. [10.1109/MetroAgriFor66923.2025.11512345].
A Low-Cost Portable Spectrophotometer for Precision Agriculture based on Hamamatsu C12880MA
Leccisi M.Writing – Original Draft Preparation
;Fina F.Validation
;Leccese F.
Conceptualization
2025-01-01
Abstract
The use of spectroscopic techniques to monitor plant health is becoming increasingly popular in precision agriculture. In this paper, we present a potential application of the Hamamatsu C12880MA spectrophotometer to study leaf surface reflectance in the spectral range from 350 nm to 850 nm. This instrument was placed near a black cloth to reduce the ambient noise and the leaves placed on the surface and they are illuminated by a lamp. This light is polarized by a polarizer located on Hamamatsu, and the reflected signal is collected by the C12880MA spectrophotometer connected to the ARDUINO UNO R4 microcontroller. From reflectance analyses, through a machine learning MLP (Multi-Layer Perceptron) model, it is possible to trace back to the corresponding pantone color of the leaf, which in turn can provide us with indications about its health status.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
