Production of Disease-Free Olive Seedlings with Artificial Intelligence and Biotechnological Methods

S. Galatali, M. A. Balci, O. Akguller and E. Kaya

European Journal of Biology and Biotechnology, 2021, vol. 2, issue 3, 79-84

Abstract: It is an inevitable fact that the applications of machine learning and artificial intelligence technologies in agricultural biotechnology approaches, whose applications are increasing rapidly in almost every field, will have an important place in determining the future fate of agriculture. Applications in which artificial intelligence is adapted to biotechnological processes such as breeding, in vitro culture studies, germplasm preservation, disease-free plant production, genetic transformation, and other genetic analyzes are becoming increasingly common. In the current study is highlighted the potential benefits between artificial intelligence and agricultural technologies. As with many plant species, viral diseases have negative effects on fruit yield, life span, and quality of olive varieties, which are important in economy. Elimination of viruses from the plant with traditional methods is quite laborious, takes a lot of time, and often fails to produce successful results. However, new protocols have been developed to eliminate persistent pathogens. These protocols include techniques such as heat application (thermotherapy), chemical therapy (chemotherapy), tissue culture methods (meristem culture). When these techniques are applied alone or together, it may be possible to obtain anti-virus plants. Artificial intelligence technology will make it possible to benefit from the method to be used in the most efficient way by revealing which of these biotechnological methods can be used in the most effective and optimal conditions, and the possible advantages and disadvantages as a result of comparing with others.

Keywords: Artificial Intelligence; biotechnology; Olea europaea L.; plant viruses (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejbio0:v:2:y:2021:i:3:id:17172

DOI: 10.24018/ejbio.2021.2.3.172

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