SoilMATe: Soil macronutrients and pH level assessment for rice plant through digital image processing using artificial neural network
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Article
Source Title
Journal of Telecommunication, Electronic and Computer Engineering
Volume
9
Issue
2-5
First Page
145
Last Page
149
Publication Date
1-1-2017
Abstract
In this study, digital image processing technique was used to efficiently identify the Macronutrients and pH level of Soil in the farmland of Philippines: (1) Nitrogen, (2) Phosphorus, (3) Potassium and (4) pH. The composition of the system is made of four sections namely, image acquisition, image processing, training system, and result. The Artificial neural network was applied in this study for its features that make it well suited in offering fast and accurate performance for the image processing. The system will base on 448 captured image data, 70% for training, 15% for testing and 15% for validation. Based on the result, the program will generate a report in printed form. Overall, this study identifies the soil macronutrient and pH level of the soil and gives fertilizer recommendation for inbred rice plant and was proven 98.33% accurate.
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Recommended Citation
Arago, N. M., Orillo, J. F., Haban, J., Juan, J., Puno, J., Quijano, J., & Tuazon, G. (2017). SoilMATe: Soil macronutrients and pH level assessment for rice plant through digital image processing using artificial neural network. Journal of Telecommunication, Electronic and Computer Engineering, 9 (2-5), 145-149. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/3917
Disciplines
Manufacturing
Keywords
Soil acidity; Soils—Testing; Image processing—Digital techniques; Neural networks (Computer science)
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