CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/1809-4430-Eng.Agric.v39nep33-40/2019 http://hdl.handle.net/11449/186852 |
Resumo: | Active optical sensors have been widely used for the spatial and temporal monitoring of peanut culture because they are accurate, non-destructive methods for rapidly obtaining data. The objective of this study was to determine the optimal stage of crop growth for collecting sensor readings based on correlations between quality indicators. In addition, we compared vegetation indices (Normalized Difference Vegetation Index [NDVI], Normalized Difference Red-Edge Index, [NDRE], and Inverse Ratio Vegetation Index, [IRVI]) by monitoring temporal variability in the peanut crop in order to determine which of them obtained the best reading quality throughout the process. The experiment was performed on the 2016/17 crop in the agricultural area of the municipality of Dumont in the state of Sao Paulo, Brazil. The experimental design was based on the basic assumptions of statistical quality control and contained 63 sample points in a 30 x 30 m grid. The parameters were evaluated at 30, 45, 60, 75, and 119 days after sowing (DAS) using proximal sensing with GreenSeeker and OptRX sensors. We found that 45 and 60 DAS were the optimal times for monitoring peanut crop variability. For spatiotemporal monitoring of the culture with control charts, NDRE showed the best readings throughout the process when compared to NDVI and IRVI. |
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CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGESremote sensingArachis hypogaea L.control chartsprecision agricultureActive optical sensors have been widely used for the spatial and temporal monitoring of peanut culture because they are accurate, non-destructive methods for rapidly obtaining data. The objective of this study was to determine the optimal stage of crop growth for collecting sensor readings based on correlations between quality indicators. In addition, we compared vegetation indices (Normalized Difference Vegetation Index [NDVI], Normalized Difference Red-Edge Index, [NDRE], and Inverse Ratio Vegetation Index, [IRVI]) by monitoring temporal variability in the peanut crop in order to determine which of them obtained the best reading quality throughout the process. The experiment was performed on the 2016/17 crop in the agricultural area of the municipality of Dumont in the state of Sao Paulo, Brazil. The experimental design was based on the basic assumptions of statistical quality control and contained 63 sample points in a 30 x 30 m grid. The parameters were evaluated at 30, 45, 60, 75, and 119 days after sowing (DAS) using proximal sensing with GreenSeeker and OptRX sensors. We found that 45 and 60 DAS were the optimal times for monitoring peanut crop variability. For spatiotemporal monitoring of the culture with control charts, NDRE showed the best readings throughout the process when compared to NDVI and IRVI.Sao Paulo State Univ Unesp, Sch Agr & Vet Sci, Jaboticabal, SP, BrazilFed Inst Educ Sci & Technol Rondonia IFRO, Colorado Do Oeste, RO, BrazilFarroupilha Fed Inst Educ Sci & Technol IFFar, Jaguari, RS, BrazilSao Paulo State Univ Unesp, Sch Agr & Vet Sci, Jaboticabal, SP, BrazilSoc Brasil Engenharia AgricolaUniversidade Estadual Paulista (Unesp)Fed Inst Educ Sci & Technol Rondonia IFROFarroupilha Fed Inst Educ Sci & Technol IFFarCarneiro, Franciele M. [UNESP]Furlani, Carlos E. A. [UNESP]Zerbato, Cristiano [UNESP]Menezes, Patricia C. de [UNESP]Girio, Lucas A. da S. [UNESP]2019-10-06T08:13:06Z2019-10-06T08:13:06Z2019-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article33-40application/pdfhttp://dx.doi.org/10.1590/1809-4430-Eng.Agric.v39nep33-40/2019Engenharia Agricola. Jaboticabal: Soc Brasil Engenharia Agricola, v. 39, p. 33-40, 2019.0100-6916http://hdl.handle.net/11449/18685210.1590/1809-4430-Eng.Agric.v39nep33-40/2019S0100-69162019000800033WOS:000484853000004S0100-69162019000800033.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEngenharia Agricolainfo:eu-repo/semantics/openAccess2024-06-06T15:18:43Zoai:repositorio.unesp.br:11449/186852Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-06T15:18:43Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES |
title |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES |
spellingShingle |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES Carneiro, Franciele M. [UNESP] remote sensing Arachis hypogaea L. control charts precision agriculture |
title_short |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES |
title_full |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES |
title_fullStr |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES |
title_full_unstemmed |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES |
title_sort |
CORRELATIONS AMONG VEGETATION INDICES AND PEANUT TRAITS DURING DIFFERENT CROP DEVELOPMENT STAGES |
author |
Carneiro, Franciele M. [UNESP] |
author_facet |
Carneiro, Franciele M. [UNESP] Furlani, Carlos E. A. [UNESP] Zerbato, Cristiano [UNESP] Menezes, Patricia C. de [UNESP] Girio, Lucas A. da S. [UNESP] |
author_role |
author |
author2 |
Furlani, Carlos E. A. [UNESP] Zerbato, Cristiano [UNESP] Menezes, Patricia C. de [UNESP] Girio, Lucas A. da S. [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Fed Inst Educ Sci & Technol Rondonia IFRO Farroupilha Fed Inst Educ Sci & Technol IFFar |
dc.contributor.author.fl_str_mv |
Carneiro, Franciele M. [UNESP] Furlani, Carlos E. A. [UNESP] Zerbato, Cristiano [UNESP] Menezes, Patricia C. de [UNESP] Girio, Lucas A. da S. [UNESP] |
dc.subject.por.fl_str_mv |
remote sensing Arachis hypogaea L. control charts precision agriculture |
topic |
remote sensing Arachis hypogaea L. control charts precision agriculture |
description |
Active optical sensors have been widely used for the spatial and temporal monitoring of peanut culture because they are accurate, non-destructive methods for rapidly obtaining data. The objective of this study was to determine the optimal stage of crop growth for collecting sensor readings based on correlations between quality indicators. In addition, we compared vegetation indices (Normalized Difference Vegetation Index [NDVI], Normalized Difference Red-Edge Index, [NDRE], and Inverse Ratio Vegetation Index, [IRVI]) by monitoring temporal variability in the peanut crop in order to determine which of them obtained the best reading quality throughout the process. The experiment was performed on the 2016/17 crop in the agricultural area of the municipality of Dumont in the state of Sao Paulo, Brazil. The experimental design was based on the basic assumptions of statistical quality control and contained 63 sample points in a 30 x 30 m grid. The parameters were evaluated at 30, 45, 60, 75, and 119 days after sowing (DAS) using proximal sensing with GreenSeeker and OptRX sensors. We found that 45 and 60 DAS were the optimal times for monitoring peanut crop variability. For spatiotemporal monitoring of the culture with control charts, NDRE showed the best readings throughout the process when compared to NDVI and IRVI. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-06T08:13:06Z 2019-10-06T08:13:06Z 2019-09-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1590/1809-4430-Eng.Agric.v39nep33-40/2019 Engenharia Agricola. Jaboticabal: Soc Brasil Engenharia Agricola, v. 39, p. 33-40, 2019. 0100-6916 http://hdl.handle.net/11449/186852 10.1590/1809-4430-Eng.Agric.v39nep33-40/2019 S0100-69162019000800033 WOS:000484853000004 S0100-69162019000800033.pdf |
url |
http://dx.doi.org/10.1590/1809-4430-Eng.Agric.v39nep33-40/2019 http://hdl.handle.net/11449/186852 |
identifier_str_mv |
Engenharia Agricola. Jaboticabal: Soc Brasil Engenharia Agricola, v. 39, p. 33-40, 2019. 0100-6916 10.1590/1809-4430-Eng.Agric.v39nep33-40/2019 S0100-69162019000800033 WOS:000484853000004 S0100-69162019000800033.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Engenharia Agricola |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
33-40 application/pdf |
dc.publisher.none.fl_str_mv |
Soc Brasil Engenharia Agricola |
publisher.none.fl_str_mv |
Soc Brasil Engenharia Agricola |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1803650193800822784 |