Overview of fruit and vegetables quality assessment surveys using soft computing

Articles in Press

Document Type : Systematic literature review

Authors

Dept. Agrotechnology, Aburaihan Campus, University of Tehran, Tehran, Iran

Abstract

Demand for quality products has been increasing for decades and is now increasing. Quality control ensures increased product production using an automated, cost-effective and non-destructive method. In the last few years, significant results have been achieved in various agricultural and food sectors. These achievements are integrated with machine learning techniques in a landscape approach that contrasts with color, texture, shape, spectral analysis of the image of objects. Despite having different programs and many different machine learning techniques, this study only explains the statistical technologies of machine learning with machine vision systems in agriculture due to the wide range of machine learning programs. Two types of machine learning techniques, such as supervised and unsupervised learning, have been used for agriculture. In this research, software solutions rely on image processing techniques such as: artificial neural networks, genetic algorithm, deep learning and fuzzy logic for automatic detection as well as classification of different degrees of fruit. There is also more reference to the study and description of product classification methods that using the mentioned algorithms and their relationship with the software can be a big step in quality classification of products.

Keywords

Main Subjects

Soft Computing Journal

Articles in Press, Accepted Manuscript
Available Online from 23 July 2024

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History

  • Receive Date: 10 October 2022
  • Revise Date: 10 December 2023
  • Accept Date: 22 January 2024

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