Use of machine learning for olive cultivation: A review

Le résumé fourni par la source

Together with the globalization and climate change, rapid technological developments are also driving research into agriculture. Considering the current state of the world's population, agricultural sustainability is one of the key factors for minimizing food waste and shortages. Thanks to technology improvements, smart agricultural practices can produce a range of chances in this context, promoting the notion of regional goods being producible in different regions. In this study, studies were carried out in the field of machine learning of the cultivation of olive fruit. There are detailed analyses of the existing studies based on the year, region and methodologies used. While commonly referred to be a Mediterranean product in literature, it may flourish with same quality anywhere with a technological tweak. Furthermore, apart from emphasizing the significance of machine learning in optimizing product quality, it is anticipated that various forms of learning will be more effectively controlled with social and governmental support.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.