{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T19:00:03Z","timestamp":1778007603339,"version":"3.51.4"},"reference-count":98,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia (FCT)","award":["UIDB\/00066\/2020"],"award-info":[{"award-number":["UIDB\/00066\/2020"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia (FCT)","award":["UIDP\/04035\/2020"],"award-info":[{"award-number":["UIDP\/04035\/2020"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia (FCT)","award":["UIDB\/00239\/2020"],"award-info":[{"award-number":["UIDB\/00239\/2020"]}]},{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia (FCT)","award":["LA\/P\/0092\/2020"],"award-info":[{"award-number":["LA\/P\/0092\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Agronomy"],"abstract":"<jats:p>Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing are propelling the agricultural sector towards the transformative Agriculture 4.0 paradigm. The present systematic literature review employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to explore the usage of Machine Learning in agriculture. The study investigates the foremost applications of Machine Learning, including crop, water, soil, and animal management, revealing its important role in revolutionising traditional agricultural practices. Furthermore, it assesses the substantial impacts and outcomes of Machine Learning adoption and highlights some challenges associated with its integration in agricultural systems. This review not only provides valuable insights into the current landscape of Machine Learning applications in agriculture, but it also outlines promising directions for future research and innovation in this rapidly evolving field.<\/jats:p>","DOI":"10.3390\/agronomy13122976","type":"journal-article","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T03:58:02Z","timestamp":1701403082000},"page":"2976","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":199,"title":["Machine Learning Applications in Agriculture: Current Trends, Challenges, and Future Perspectives"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6192-8409","authenticated-orcid":false,"given":"Sara Oleiro","family":"Ara\u00fajo","sequence":"first","affiliation":[{"name":"UNINOVA\u2014Centre of Technology and Systems (CTS), FCT Campus, Monte de Caparica, 2829-516 Caparica, Portugal"},{"name":"Earth Sciences Department (DCT), School of Sciences and Technology (NOVA-SST), NOVA University of Lisbon, 2829-516 Caparica, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3777-1346","authenticated-orcid":false,"given":"Ricardo Silva","family":"Peres","sequence":"additional","affiliation":[{"name":"UNINOVA\u2014Centre of Technology and Systems (CTS), FCT Campus, Monte de Caparica, 2829-516 Caparica, Portugal"},{"name":"Electrical and Computer Engineering Department (DEEC), School of Sciences and Technology (NOVA-SST), 2829-516 Caparica, Portugal"},{"name":"Intelligent Systems Associate Laboratory (LASI), 4800-058 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7639-7214","authenticated-orcid":false,"given":"Jos\u00e9 Cochicho","family":"Ramalho","sequence":"additional","affiliation":[{"name":"GeoBioSciences, GeoTechnologies and GeoEngineering Unit (GeoBiotec), School of Sciences and Technology (NOVA-SST), 2829-516 Caparica, Portugal"},{"name":"PlantStress and Biodiversity Lab, Forest Research Center (CEF), Associate Laboratory TERRA, School of Agriculture (ISA), University of Lisbon (ULisboa), 2784-505 Oeiras, Portugal"}]},{"given":"Fernando","family":"Lidon","sequence":"additional","affiliation":[{"name":"Earth Sciences Department (DCT), School of Sciences and Technology (NOVA-SST), NOVA University of Lisbon, 2829-516 Caparica, Portugal"},{"name":"GeoBioSciences, GeoTechnologies and GeoEngineering Unit (GeoBiotec), School of Sciences and Technology (NOVA-SST), 2829-516 Caparica, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6348-1847","authenticated-orcid":false,"given":"Jos\u00e9","family":"Barata","sequence":"additional","affiliation":[{"name":"UNINOVA\u2014Centre of Technology and Systems (CTS), FCT Campus, Monte de Caparica, 2829-516 Caparica, Portugal"},{"name":"Electrical and Computer Engineering Department (DEEC), School of Sciences and Technology (NOVA-SST), 2829-516 Caparica, Portugal"},{"name":"Intelligent Systems Associate Laboratory (LASI), 4800-058 Guimar\u00e3es, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ara\u00fajo, S.O., Peres, R.S., Barata, J., Lidon, F., and Ramalho, J.C. 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