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Title: Prediction of soil nitrogen content using E-nose and radial basis function
Authors: Jigme Norbu
Theerapat Pobkrut
Treenet Thepudom
Thinley Namgyel
Teerayut Chaiyasit
Yu Thazin
Teerakiat Kerdcharoen
Mahidol University
Keywords: Computer Science;Engineering;Mathematics
Issue Date: 18-Jan-2019
Citation: ECTI-CON 2018 - 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology. (2019), 309-312
Abstract: © 2018 IEEE Existing soil nutrient determining methods are still a concern as most of them entail arduous field sampling followed by rigorous testing procedures, both of which are time consuming and expensive. Conversely, farmers require cheap and instant information about the soil nutrient management for quick decision making or they will have to risk their crop. Electronic nose (E-nose) is an emerging technology that has potential application in monitoring of soil nutrient abundance. In this work, e-nose coupled with Radial Basis Function (RBF) is employed to determine the amount of nitrogen (N) which is one of the main nutrients in the soil. The results demonstrate that not only does the e-nose clearly discriminate the odors of soil with different N concentration, but also can evidently predict the total N content with accuracy of 96.2% using RBF. Hence, e-nose and RBF network could be a promising alternative to conventional soil testing methods.
Appears in Collections:Scopus 2019

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