{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:58:44Z","timestamp":1776301124779,"version":"3.50.1"},"reference-count":113,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T00:00:00Z","timestamp":1643328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"La Caixa \/ BPI \/ FCT","award":["PD20-00011"],"award-info":[{"award-number":["PD20-00011"]}]},{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["UIDB\/00151\/2020"],"award-info":[{"award-number":["UIDB\/00151\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Deep Learning has been successfully applied to image recognition, speech recognition, and natural language processing in recent years. Therefore, there has been an incentive to apply it in other fields as well. The field of agriculture is one of the most important fields in which the application of deep learning still needs to be explored, as it has a direct impact on human well-being. In particular, there is a need to explore how deep learning models can be used as a tool for optimal planting, land use, yield improvement, production\/disease\/pest control, and other activities. The vast amount of data received from sensors in smart farms makes it possible to use deep learning as a model for decision-making in this field. In agriculture, no two environments are exactly alike, which makes testing, validating, and successfully implementing such technologies much more complex than in most other industries. This paper reviews some recent scientific developments in the field of deep learning that have been applied to agriculture, and highlights some challenges and potential solutions using deep learning algorithms in agriculture. The results in this paper indicate that by employing new methods from deep learning, higher performance in terms of accuracy and lower inference time can be achieved, and the models can be made useful in real-world applications. Finally, some opportunities for future research in this area are suggested.<\/jats:p>","DOI":"10.3390\/rs14030638","type":"journal-article","created":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T01:43:27Z","timestamp":1643420607000},"page":"638","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":83,"title":["A Review of the Challenges of Using Deep Learning Algorithms to Support Decision-Making in Agricultural Activities"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2319-8211","authenticated-orcid":false,"given":"Khadijeh","family":"Alibabaei","sequence":"first","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST Center for Mechanical and Aerospace Science and Technologies, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-1709","authenticated-orcid":false,"given":"Pedro D.","family":"Gaspar","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST Center for Mechanical and Aerospace Science and Technologies, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7540-3854","authenticated-orcid":false,"given":"T\u00e2nia M.","family":"Lima","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST Center for Mechanical and Aerospace Science and Technologies, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0672-4408","authenticated-orcid":false,"given":"Rebeca M.","family":"Campos","sequence":"additional","affiliation":[{"name":"Linking Landscape, Environment, Agriculture and Food (LEAF), Instituto Superior de Agronomia, Universidade de Lisboa, 1349-017 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7201-0548","authenticated-orcid":false,"given":"In\u00eas","family":"Gir\u00e3o","sequence":"additional","affiliation":[{"name":"Center of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, 1600-276 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0392-1246","authenticated-orcid":false,"given":"Jorge","family":"Monteiro","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST Center for Mechanical and Aerospace Science and Technologies, University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"SpaceWay, R. Pedro Nunes, 3030-199 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2456-1200","authenticated-orcid":false,"given":"Carlos M.","family":"Lopes","sequence":"additional","affiliation":[{"name":"Linking Landscape, Environment, Agriculture and Food (LEAF), Instituto Superior de Agronomia, Universidade de Lisboa, 1349-017 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,28]]},"reference":[{"key":"ref_1","unstructured":"Oppermann, R., and Paracchini, M. (2012). HNV Farming\u2013Central to European Cultural Landscapes and Biodiversity. High Nature Value Farming in Europe: 35 European Countries\u2014Experiences and Perspectives, Verlag Regionalkultur."},{"key":"ref_2","unstructured":"Vermesan, O., and Friess, P. (2016). Internet of Food and Farm 2020. 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