Use of machine learning for olive cultivation: A review

Authors : Dilan Sarpkaya, Müge Kesici Baysoy, Zeynep Tacercaba, Fatih Kahraman, Gül Tekin Temur

Pages : 453-470

Doi:10.20479/bursauludagziraat.1589035

View : 60 | Download : 193

Publication Date : 2025-12-01

Article Type : Review Paper

Abstract :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.
Keywords : olive cultivation, machine learning, olive yield, akıllı tarım, zeytin yetiştiriciliği, makine öğrenmesi, zeytin verimi

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