Challenging Issues in Automated Oil Palm Fruit Grading

Gaurang S Patkar, Anjaneyulu G.S.G.N, Chandra Mouli P.V.S.S.R


Late advancement in Agriculture segment utilizing Image preparing and fuzzy logic methods has empowered ranchers to expand the yield of harvest and served the nourishment needs of the whole people. Look into in horticulture is pointed towards increment in the profitability, quality and lessening the likelihood of blunder presented by people. The biggest oil palm creation is in Malaysia and Indonesia and they send out palm oil to different nations on the planet. The most outrageous enthusiasm for palm oil is in India. This came to fruition India into Palm Oil advancement and era in various states . With a specific end goal to expand the efficiency of palm oil organic products, palm oil industry and in addition analysts utilizes different machine-vision systems to review the natural products. Tragically, the information caught and prepared is confronted with restricted learning and accuracy. There are a few difficulties required with the outline and usage of palm oil organic product reviewing. This paper introduces an outline of different Image handling and fuzzy logic methods, distinguishes and addresses testing issues in computerized palm natural product evaluating.


Elaeis guineensis, Fresh fruit bunches, Fuzzy Logic, Mesocarp, Neural Network

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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