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

John Carlo Puno, Edwin Sybingco, Elmer Dadios, Ira Valenzuela, Joel Cuello

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationHNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538609101
DOIs
StatePublished - Jul 2 2017
Event9th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2017 - Manila, Philippines
Duration: Nov 29 2017Dec 1 2017

Publication series

NameHNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management
Volume2018-January

Other

Other9th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2017
CountryPhilippines
CityManila
Period11/29/1712/1/17

Keywords

  • Artificial Neural Network
  • Digital Image Processing
  • MATLAB
  • Nutrients
  • Soil

ASJC Scopus subject areas

  • Ecological Modeling
  • Management, Monitoring, Policy and Law
  • Computer Networks and Communications
  • Computer Science Applications
  • Human-Computer Interaction
  • Information Systems
  • Control and Optimization
  • Artificial Intelligence

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