Macabiog, R.E.N., Fadchar, N.A. and Cruz, J.C.D. (2020) Soil NPK Levels Characterization Using near Infrared and Artificial Neural Network. 2020 16th IEEE International Colloquium on Signal Processing & Its Applications (CSPA), Langkawi, 28-29 February 2020, 141-145.
https://doi.org/10.1109/cspa48992.2020.9068717

has been cited by the following article:

• TITLE: Evaluation of the Influence of Geometric Parameters on the Accuracy of a Visible Near Infrared (VNIR) Spectroscopy-Based Nitrogen Phosphorus Potassium (NPK) Soil Sensor

  AUTHORS: Mangeh Elsie Jaja, Valery Nkemeni, Pierre Tsafack, Pierre Brosselard

  KEYWORDS: Sensors, Optical Sensing Techniques, Visible Near Infrared Spectroscopy, Geometric Parameters

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.15 No.7, July 21, 2025

  ABSTRACT: Optimal sensor geometry is crucial for minimizing external light interference, as optical sensing relies on light transmission, which is susceptible to ambient light disruption. This study investigates the influence of geometric parameters on the accuracy of optical sensors used for detecting soil macronutrients. The geometric configuration—specifically the alignment of the photodiode and LEDs was determined using the law of reflection, focusing on parameters such as path length (x), angles of incidence (θi) and reflection (θr), and component distances (d1, d2, and D). Experimental analysis revealed that the optimal values for x, D, and θr were 2 cm, 7 cm, and 60˚, respectively. At these settings, the sensor achieved minimal error, with RMSE values of 2.1, 0.1, and 1.6 for Nitrogen, Phosphorus, and Potassium concentration measurements, respectively.