In recent years, the olive oil sector has experienced growth due to the health benefits associated with olive oil and its increasing demand in international markets. Artificial Neural Networks (ANNs) have emerged as powerful tools in various scientific domains, enhancing both the efficiency and the accuracy of analyses in the olive oil sector. This paper aims to comprehensively review the adoption of ANNs in the assessment of olive oil across production and post-production stages. To achieve this goal, we followed the well-known guidelines of Kitchenham (2004) for performing systematic reviews. This up-to-date review examines literature from the last seven years, analyzing 628 publications and finally selecting 79 primary studies. Through a systematic and comprehensive analysis, this review seeks to provide insights into the current state of research, identify gaps in knowledge, and offer recommendations for future directions in harnessing ANNs to optimize the production and post-production analyses of olive oil.

Artificial neural networks applied to olive oil production and characterization: a systematic review

Lonetti F.;Martelli F.;Resta G.
2025

Abstract

In recent years, the olive oil sector has experienced growth due to the health benefits associated with olive oil and its increasing demand in international markets. Artificial Neural Networks (ANNs) have emerged as powerful tools in various scientific domains, enhancing both the efficiency and the accuracy of analyses in the olive oil sector. This paper aims to comprehensively review the adoption of ANNs in the assessment of olive oil across production and post-production stages. To achieve this goal, we followed the well-known guidelines of Kitchenham (2004) for performing systematic reviews. This up-to-date review examines literature from the last seven years, analyzing 628 publications and finally selecting 79 primary studies. Through a systematic and comprehensive analysis, this review seeks to provide insights into the current state of research, identify gaps in knowledge, and offer recommendations for future directions in harnessing ANNs to optimize the production and post-production analyses of olive oil.
2025
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Istituto di informatica e telematica - IIT
Artificial neural network, Olive oil, Systematic review
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/554743
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