Artificial intelligence and machine learning applications in agricultural supply chain: a critical commentary

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dc.authorid0000-0003-0067-1835
dc.contributor.authorAylak, Batin Latif
dc.date.accessioned2022-01-06T11:42:45Z
dc.date.available2022-01-06T11:42:45Z
dc.date.issued2021
dc.departmentTAÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractIntegration of AI and ML technologies in the agricultural supply chain (ASC) is revolutionalizing, the domain by bringing in robust monitoring and prediction as well as quick decision-making abilities. A comprehensive literature analysis of the applications of artificial intelligence methods and machine learning algorithms in the agricultural supply chain is demonstrated in this study. In order to solve complicated challenges confronted by various areas of the agricultural supply chain, this literature analysis addresses different significant works that machine learning and artificial intelligence methods are used. Different AI and ML applications were suggested for the following areas of agriculture belonging to different phases: (i) crop yield prediction, prediction of soil properties and irrigation management; (ii) weather prediction, disease detection and weed detection, (iii) demand management and production planning, (iv) transportation, storage, inventory and retailing. In order to remain unbiased and objective, different studies from different journals were analyzed for each phase. It is observed that the majority of these studies focus on crop yield and soil properties prediction. It is also inferred that artificial neural networks, support vector machines, utilization of unmanned aerial vehicles, and remote sensors are fairly popular in the agriculture discipline.
dc.identifier.citationAylak, B. L. (2021). Artificial Intelligence And Machine Learning Applications In Agricultural Supply Chain: A Critical Commentary. Fresenius Environmental Bulletin, 30(7 A), 8905-8916.
dc.identifier.endpage8916en_US
dc.identifier.issn1018-4619
dc.identifier.issn1610-2304
dc.identifier.issue7Aen_US
dc.identifier.startpage8905en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12846/617
dc.identifier.volume30en_US
dc.identifier.wosWOS:000678352300010
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.institutionauthorAylak, Batin Latif
dc.language.isoen
dc.publisherFresenius Environmental Bulletin
dc.relation.ispartofFresenius Environmental Bulletin
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAgricultural Supply Chainen_US
dc.subjectMachine Learningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectTarımsal Tedarik Zincirien_US
dc.subjectMakine Öğrenmeen_US
dc.subjectYapay Zekaen_US
dc.titleArtificial intelligence and machine learning applications in agricultural supply chain: a critical commentary
dc.typeArticle

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