Determination of soil nutrients and pH level using image processing and artificial neural network

College

Gokongwei College of Engineering

Department/Unit

Manufacturing Engineering and Management

Document Type

Conference Proceeding

Source Title

HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management

Volume

2018-January

First Page

1

Last Page

6

Publication Date

7-2-2017

Abstract

In this study, image processing and artificial neural network was used to efficiently identify the nutrients and pH level of soil with the use of Soil Test Kit (STK) and Rapid Soil Testing (RST) of the Bureau of Soils and Water Management: (1) pH, (2) Nitrogen, (3) Phosphorus, (4) Potassium, (5) Zinc, (6) Calcium, and (7) Magnesium. The composition of the system is made of five sections namely soil testing, image capturing, image processing, training system for neural network, and result. The use of Artificial Neural Network is to hasten the performance of image processing in giving accurate result. The system will base on captured image data, 70% for training, 15% for testing and 15% for validation as default of neural network tool of MATLAB. Based on the result, the program will show the qualitative level of soil nutrients and pH. Overall, this study identifies the soil nutrient and pH level of the soil and was proven accurate. © 2017 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2017.8269472

Disciplines

Environmental Engineering | Manufacturing

Keywords

Soils—Testing; Soil acidity; Image processing—Digital techniques; Neural networks (Computer science)

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