Soil Parameter Detection of Soil Test Kit-Treated Soil Samples through Image Processing with Crop and Fertilizer Recommendation

John Joshua Federis Montañez

Abstract


Standard laboratory soil testing is deemed to be expensive and time-consuming. Utilizing a soil test kit is considered to be a cost-efficient and time-saving way of soil testing. This project study aims to develop a prototype that detects soil parameters (i.e., soil pH, Nitrogen, Phosphorus, and Potassium) and gives crop and fertilizer recommendation after the soil sample underwent soil treatment test kit and its acceptability among possible users. The prototype development primarily used image processing in the detection of the needed parameters that leads towards crop and fertilizer recommendation. In the evaluation of the effectiveness of the prototype, 50 trials were conducted per parameter. All of the said parameters were recorded as highly effective except for Nitrogen Low, which is interpreted as effective only. There were 30 possible users invited to assess the acceptability of the prototype. A survey based on the Technology Acceptance Model was administered to the 30 respondents garnering a 4.85 weighted mean interpreted as excellent. The prototype was proven effective and accepted as a device that can detect soil pH and primary macronutrient levels. It gives the appropriate crop and fertilizer recommendation based on the gathered data.

Keywords


Image Processing; Raspberry Pi; Soil Test Kit; Soil pH and NPK; Technology Acceptance Model

References


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DOI: http://doi.org/10.11591/ijeecs.v24.i1.pp%25p

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