Bonfring International Journal of Software Engineering and Soft Computing

Impact Factor: 0.375 | International Scientific Indexing(ISI) calculate based on International Citation Report(ICR)


Detection of Moisture Content of Fruits Using ANN

Shweta Kammar, Bhagat G. Inamdar and S.B. Kulkarni


Abstract:

Percentage of moisture is an essential quality factor to detect the freshness of the fruit. Moisture Content (MC) has real impact on the mass of fruit. Proposed method is used to get texture parameters that imply the fruit?s density. The MC of a fruit can be measured using statistical approach. To measure this, few texture parameters are analyzed from different views. In this light, artificial neural network (ANN) is used to get the loss moisture content as an error by considering the determined texture parameters as input. ANN estimates the moisture content of fruit with higher accuracy.

Keywords: MC-Moisture Content, ANN-Artificial neural network, freshness.

Volume: 6 | Issue: Special Issue on Advances in Computer Science and Engineering and Workshop on Big Data Analytics Editors: Dr.S.B. Kulkarni, Dr.U.P. Kulkarni, Dr.S.M. Joshi and J.V. Vadavi

Pages: 27-31

Issue Date: October , 2016

DOI: 10.9756/BIJSESC.8237

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