Artificial Neural Networks in Fruits: A Comprehensive Review

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Sumit Goyal 1,*

1. IDA, New Delhi, India

* Corresponding author.


Received: 2 Jan. 2014 / Revised: 4 Feb. 2014 / Accepted: 7 Mar. 2014 / Published: 8 Apr. 2014

Index Terms

Artificial neural networks (ANN), machine learning, backpropagation, fruits, neurocomputing, soft computing


This review discusses the application of artificial neural networks (ANN) modeling in fruits. It covers all fruits in which ANN modeling has been applied. ANN is quite a new and easy computational modeling approach used for prediction, which has become popular and accepted by food industry, researchers, scientists and students. ANNs have been applied in almost every field of science and technology, viz., speech synthesis & recognition, pattern classification, adaptive interfaces between humans & complex physical systems, clustering, function approximation, image data compression, non-linear system modeling, associative memory, combinatorial optimization, control and several others, as they have proved valuable tools for obtaining the required output. ANN provides an exciting alternative method for solving a variety of problems in different areas of science and engineering. The aim of this communication is to discover the recent advances of ANN technology implemented in fruits, and discuss the critical role that ANN plays in predictive modelling.

Cite This Paper

Sumit Goyal,"Artificial Neural Networks in Fruits: A Comprehensive Review", IJIGSP, vol.6, no.5, pp.53-63, 2014. DOI: 10.5815/ijigsp.2014.05.07


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