Using Geospatial Information to Map Yield Gain from the Use of Azospirillum brasilense in Furrow

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Autor(es): dc.contributorUnversidade Federal de Uberlândia-
Autor(es): dc.contributorLallemand Soluções Biológicas LTDA-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorMartins, George Deroco-
Autor(es): dc.creatorXavier, Laura Cristina Moura-
Autor(es): dc.creatorde Oliveira, Guilherme Pereira-
Autor(es): dc.creatorde Lourdes Bueno Trindade Gallo, Maria-
Autor(es): dc.creatorde Abreu Júnior, Carlos Alberto Matias-
Autor(es): dc.creatorVieira, Bruno Sérgio-
Autor(es): dc.creatorMarques, Douglas José-
Autor(es): dc.creatorda Silva, Filipe Vieira-
Data de aceite: dc.date.accessioned2025-08-21T23:20:44Z-
Data de disponibilização: dc.date.available2025-08-21T23:20:44Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-03-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/agronomy13030808-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/248678-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/248678-
Descrição: dc.descriptionThe application of biological products in agricultural crops has become increasingly prominent. The growth-promoting bacterium Azospirillum brasilense has been used as an alternative to promote greater yield in maize crops. In the context of precision agriculture, interpreting geospatial data has allowed for monitoring the effect of the application of products that increase the yield of corn crops. The objective of this work was to evaluate the potential of Kriging techniques and spectral models through images in estimating the gain in yield of maize crop after applying A. brasilense. Analyses were carried out in two commercial areas treated with A. brasilense. The results revealed that models of yield prediction by Kriging with a high volume of training data estimated the yield gain with a root-mean-square error deviation (RMSE%), mean absolute percentage error (MAPE%), and R2 to be 6.67, 5.42, and 0.88, respectively. For spectral models with a low volume of training data, yield gain was estimated with RMSE%, MAPE%, and R2 to be 9.3, 7.71, and 0.80, respectively. The results demonstrate the potential to map the spatial distribution of productivity gains in corn crops following the application of A. brasilense.-
Descrição: dc.descriptionInstutute of Geography Unversidade Federal de Uberlândia, BR-MG-
Descrição: dc.descriptionPost Graduate Program in Agriculture and Geospatial Information Institute of Agrarian Sciences Unversidade Federal de Uberlândia, BR-MG-
Descrição: dc.descriptionLallemand Soluções Biológicas LTDA, BR-MG-
Descrição: dc.descriptionCartography Departament Faculdade de Ciências e Tecnologia Universidade Estadual Paulista-
Descrição: dc.descriptionInstitute of Agrarian Sciences Unversidade Federal de Uberlândia, MG-
Descrição: dc.descriptionCartography Departament Faculdade de Ciências e Tecnologia Universidade Estadual Paulista-
Idioma: dc.languageen-
Relação: dc.relationAgronomy-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectbiological product-
Palavras-chave: dc.subjectgeospatial data analysis-
Palavras-chave: dc.subjectyield gain distribution map-
Título: dc.titleUsing Geospatial Information to Map Yield Gain from the Use of Azospirillum brasilense in Furrow-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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