{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T16:00:31Z","timestamp":1779379231018,"version":"3.53.1"},"reference-count":45,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T00:00:00Z","timestamp":1575590400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["CAPES\/Print (p: 88881.311850\/2018-01)"],"award-info":[{"award-number":["CAPES\/Print (p: 88881.311850\/2018-01)"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005667","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa e Inova\u00e7\u00e3o do Estado de Santa Catarina","doi-asserted-by":"publisher","award":["2017TR1762"],"award-info":[{"award-number":["2017TR1762"]}],"id":[{"id":"10.13039\/501100005667","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["313887\/2018-7"],"award-info":[{"award-number":["313887\/2018-7"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The traditional method of measuring nitrogen content in plants is a time-consuming and labor-intensive task. Spectral vegetation indices extracted from unmanned aerial vehicle (UAV) images and machine learning algorithms have been proved effective in assisting nutritional analysis in plants. Still, this analysis has not considered the combination of spectral indices and machine learning algorithms to predict nitrogen in tree-canopy structures. This paper proposes a new framework to infer the nitrogen content in citrus-tree at a canopy-level using spectral vegetation indices processed with the random forest algorithm. A total of 33 spectral indices were estimated from multispectral images acquired with a UAV-based sensor. Leaf samples were gathered from different planting-fields and the leaf nitrogen content (LNC) was measured in the laboratory, and later converted into the canopy nitrogen content (CNC). To evaluate the robustness of the proposed framework, we compared it with other machine learning algorithms. We used 33,600 citrus trees to evaluate the performance of the machine learning models. The random forest algorithm had higher performance in predicting CNC than all models tested, reaching an R2 of 0.90, MAE of 0.341 g\u00b7kg\u22121 and MSE of 0.307 g\u00b7kg\u22121. We demonstrated that our approach is able to reduce the need for chemical analysis of the leaf tissue and optimizes citrus orchard CNC monitoring.<\/jats:p>","DOI":"10.3390\/rs11242925","type":"journal-article","created":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T10:41:44Z","timestamp":1575628904000},"page":"2925","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":131,"title":["Predicting Canopy Nitrogen Content in Citrus-Trees Using Random Forest Algorithm Associated to Spectral Vegetation Indices from UAV-Imagery"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0258-536X","authenticated-orcid":false,"given":"Lucas","family":"Prado Osco","sequence":"first","affiliation":[{"name":"Faculty of Engineering, Architecture, and Urbanism and Geography, Federal University of Mato Grosso do Sul, Av. Costa e Silva, Campo Grande 79070-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6633-2903","authenticated-orcid":false,"given":"Ana Paula","family":"Marques Ramos","sequence":"additional","affiliation":[{"name":"Environmental and Regional Development, University of Western S\u00e3o Paulo, R. Jos\u00e9 Bongiovani, 700-Cidade Universit\u00e1ria, Presidente Prudente 19050-920, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danilo","family":"Roberto Pereira","sequence":"additional","affiliation":[{"name":"Environmental and Regional Development, University of Western S\u00e3o Paulo, R. Jos\u00e9 Bongiovani, 700-Cidade Universit\u00e1ria, Presidente Prudente 19050-920, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"\u00c9rika","family":"Akemi Saito Moriya","sequence":"additional","affiliation":[{"name":"Department of Cartographic Science, S\u00e3o Paulo State University, Presidente Prudente 19060-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0516-0567","authenticated-orcid":false,"given":"Nilton","family":"Nobuhiro Imai","sequence":"additional","affiliation":[{"name":"Department of Cartographic Science, S\u00e3o Paulo State University, Presidente Prudente 19060-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4471-0886","authenticated-orcid":false,"given":"Edson","family":"Takashi Matsubara","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Federal University of Mato Grosso do Sul, Av. Costa e Silva, Campo Grande 79070-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nayara","family":"Estrabis","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Architecture, and Urbanism and Geography, Federal University of Mato Grosso do Sul, Av. Costa e Silva, Campo Grande 79070-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2901-7773","authenticated-orcid":false,"given":"Maur\u00edcio","family":"de Souza","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Architecture, and Urbanism and Geography, Federal University of Mato Grosso do Sul, Av. Costa e Silva, Campo Grande 79070-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9096-6866","authenticated-orcid":false,"given":"Jos\u00e9","family":"Marcato Junior","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Architecture, and Urbanism and Geography, Federal University of Mato Grosso do Sul, Av. Costa e Silva, Campo Grande 79070-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8815-6653","authenticated-orcid":false,"given":"Wesley Nunes","family":"Gon\u00e7alves","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Architecture, and Urbanism and Geography, Federal University of Mato Grosso do Sul, Av. Costa e Silva, Campo Grande 79070-900, Brazil"},{"name":"Faculty of Computer Science, Federal University of Mato Grosso do Sul, Av. Costa e Silva, Campo Grande 79070-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7899-0049","authenticated-orcid":false,"given":"Jonathan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Geography and Environmental Management and Department of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0564-7818","authenticated-orcid":false,"given":"Veraldo","family":"Liesenberg","sequence":"additional","affiliation":[{"name":"Forest Engineering Department, Santa Catarina State University (UDESC), Av. Luiz de Cam\u00f5es, 2090-Conta Dinheiro, Lages 88520-000, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9","family":"Eduardo Creste","sequence":"additional","affiliation":[{"name":"Agronomy Development, University of Western S\u00e3o Paulo, R. Jos\u00e9 Bongiovani, 700-Cidade Universit\u00e1ria, Presidente Prudente 19050-920, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Huang, S., Miao, Y., Yuan, F., Cao, Q., Ye, H., Lenz-Wiedemann, V.I.S., and Bareth, G. (2019). In-season diagnosis of rice nitrogen status using proximal fluorescence canopy sensor at different growth stages. Remote Sens., 11.","DOI":"10.3390\/rs11161847"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Cui, B., Zhao, Q., Huang, W., Song, X., Ye, H., and Zhou, X. (2019). A new integrated vegetation index for the estimation of winter wheat leaf chlorophyll content. Remote Sens., 11.","DOI":"10.3390\/rs11080974"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Zhang, K., Ge, X., Shen, P., Li, W., Liu, X., Cao, Q., and Tian, Y. (2019). 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