Abstract
There are many factors and ways to increase the quality and quantity of paddy yields. One of the factors that can affect the quality of paddy is the amount of fertilizer used. The optimum amount of fertilizer for any field in any year cannot be determined with absolute certainty, thus in this project, we aim to find the optimum amount of nitrogen fertilizer required in paddy fields. Problems that are characterized by uncertainty can be solved by using fuzzy expert system. We develop fuzzy expert system prototype that utilizes Mamdani-style inference where the combination of nitrogen fertilizer data contain factors and rules, would produce results based on user’s input. The data which were in form of paddy fields images were captured by an Unmanned Aerial Vehicle (UAV) or commonly known as drone and variables applied in fuzzy rules are obtained from a thorough analysis made with team of agriculture experts from Malaysian Agricultural Research and Development Institute (MARDI).
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Acknowledgement
The authors would like to thank Research Management Centre of Universiti Teknologi MARA and REI 19/2015 in supporting the research.
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Abd Razak, M.S., Abdul-Rahman, S., Mutalib, S., Abd Aziz, Z. (2017). Nitrogen Fertilizer Recommender for Paddy Fields. In: Mohamed, A., Berry, M., Yap, B. (eds) Soft Computing in Data Science. SCDS 2017. Communications in Computer and Information Science, vol 788. Springer, Singapore. https://doi.org/10.1007/978-981-10-7242-0_20
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DOI: https://doi.org/10.1007/978-981-10-7242-0_20
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