Development of Crop Reflectance Sensor for Precision Agriculture

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Abstract
Precision agriculture is one of the emerging technologies that is promising to solve the problem of food insecurity worldwide. These focus on collecting, analyzing, and taking actions based on data available from the crop and its environment. Building low-cost and reliable plant health-related sensors is critical and helpful in the agriculture industry. This study builds a leaf reflectance sensor comprising a white LED source and an S1133 photodiode detector. The angle between the source and detector varied from 30°, 45°, 60°, and 90° to determine the angle at which it would have an optimal reflectance value. The white LED source was connected to a 3-volt and 0.3-ampere power supply, while the S1133 photodiode detector was connected to an oscilloscope to measure the response voltage. Different green intensities were used using an RGB color scheme that imitates the color of the leaf that characterizes its health status. Reflectance intensities were calibrated using white standard reflectance. The result shows that the 45° angle between the source and detector gives the highest R-squared value (R2 = 0.958). This study provides an overview of the effects of varying detection angles for crop reflectance sensors that can be used to assess plant health status and help improve crop yield in the agricultural sector.
Funding Information
  • De La Salle University (04FR1TAY23-1TAY24)

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