A Portable in-situ near-infrared LEDs-based soil nitrogen sensor using artificial neural network

• Main Authors: Nur Aisyah Syafinaz, Suarin, Chia, Kim Seng, Siti Fatimah Zaharah, Mohd Fuzi
• Format: Article
• Language: English
• Published: Penerbit UTHM 2018
• Subjects: QA76 Computer software; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/29825/1/A%20portable%20in-situ%20near-infrared%20LEDs-based%20soil.pdf; http://umpir.ump.edu.my/id/eprint/29825/; https://doi.org/10.30880/ijie.2018.10.04.013; https://doi.org/10.30880/ijie.2018.10.04.013

Monitoring soil Nitrogen content for palm oil cultivation is paramount to produce high-quality palm oil. This study aims to investigate the feasibility of a proposed portable near-infrared (NIR) light emitting diodes (LEDs)-based soil Nitrogen sensor in predicting the soil Nitrogen content using artificial neural network (ANN). First, soil samples that collected from a local oil palm plantation were scanned using the developed sensor and then followed by a conventional method, i.e. Kjeldahl analysis to measure the actual soil Nitrogen content. ANN was used for C hemometric analysis to develop a predictive model to in-situ predict the soil Nitrogen content using the near infrared light . The performance of ANN was validated using leave one out cross-validation. Results indicate that ANN with one hundred hidden neurons achieved the best accuracy with a root mean square error of cross-validation of 0.031%. This finding suggests that the proposed portable sensor coupled with ANN is promising to satisfactorily predict soil Nitrogen content.