Nor Hafizah Ngajikin
Universiti Tun Hussien Onn

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A low cost spectroscopy with Raspberry Pi for soil macronutrient monitoring Suhaila Isaak; Yusmeeraz Yusof; Nor Hafizah Ngajikin; Norhafizah Ramli; Chuan Mu Wen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.12775

Abstract

Soil spectroscopy measurement is widely used to determine the macronutrients content in the soil. Spectrometer is costly equipment and commonly used to determine the transmittance, absorbance or reflectance level of various liquids and opaque solids by measuring the intensity of light as a light source passes through a sample chemical substance. This paper is reported on a low cost experimental assessment of soil macronutrient for soil spectroscopy utilizing Raspberry Pi (RPI) module in visible and near-infrared (NIR) wavelength. The sensitivity measurements are mainly due to the concentration level and the intensity of light emitting diode (LED) light source. The work is focusing on the absorbance spectroscopy particularly on linear relationship to determine the Nitrogen (N), Phosphorus (P) and Potassium (K) content level in soil using colour-developing reagent. The development of low cost and portable RPI based spectrophotometer has created new possibilities to measure the concentration level of the existed soil macronutrient within visible and infrared light wavelength of light sources. The absorbance of light was computed based on Beer-Lambert Law. The low cost RPI based spectrometer costs 80% less than the spectrometer available in the market and is capable of recording the absorbance measurements up to 5 samples. The performance of this prototype shows that it is possible to build the spectrometer using open-source software and hardware by considering the limiting factors such as light transfer to the sample, spectral filtering and the sensitivity due to the signal-to-noise ratio.