Relationship between spectral indices and quality parameters of tifton 85 forage
Autor(a) principal: | |
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Data de Publicação: | 2024 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Caatinga |
Texto Completo: | https://periodicos.ufersa.edu.br/caatinga/article/view/12139 |
Resumo: | Computer vision systems can be an alternative to traditional methods of analyzing the quality of forage crops, allowing the instantaneous, non-destructive monitoring of the crop, with cost reduction. This study aimed to evaluate the quality parameters of Tifton 85 (Cynodon spp.) using digital images, relating spectral indices to the quality parameters of this forage. In the experimental area, four levels of nitrogen fertilization were applied and the analyses were made at different times after the standardization cut (14, 28, 42, and 56 days). The quality parameters evaluated were mineral matter, crude protein, and neutral detergent fiber. From images obtained in the visible (RGB) and near-infrared (RGNIR) spectral regions, spectral indices were generated. Principal component analysis was applied to summarize the information obtained by spectral indices into a single principal component (PC1). PC1 associated with spectral indices was related to forage quality parameters for each cutting time using simple quadratic regression models. The relationships between mineral matter and spectral indices were variable over time. Crude protein and neutral detergent fiber showed the highest relationships with the spectral indices obtained by RGNIR images already at the initial times. Thus, although the RGB images have shown satisfactory results to obtain information about the quality of Tifton 85, the NIR band tends to increase the reliability of the relationships at early times. |
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Relationship between spectral indices and quality parameters of tifton 85 forageRelação entre índices espectrais e parâmetros de qualidade da forrageira tifton 85Cynodon spp. Pastagens. Visão computacional. Imagens digitais.Cynodon spp. Pastures. Computer vision. Digital images.Computer vision systems can be an alternative to traditional methods of analyzing the quality of forage crops, allowing the instantaneous, non-destructive monitoring of the crop, with cost reduction. This study aimed to evaluate the quality parameters of Tifton 85 (Cynodon spp.) using digital images, relating spectral indices to the quality parameters of this forage. In the experimental area, four levels of nitrogen fertilization were applied and the analyses were made at different times after the standardization cut (14, 28, 42, and 56 days). The quality parameters evaluated were mineral matter, crude protein, and neutral detergent fiber. From images obtained in the visible (RGB) and near-infrared (RGNIR) spectral regions, spectral indices were generated. Principal component analysis was applied to summarize the information obtained by spectral indices into a single principal component (PC1). PC1 associated with spectral indices was related to forage quality parameters for each cutting time using simple quadratic regression models. The relationships between mineral matter and spectral indices were variable over time. Crude protein and neutral detergent fiber showed the highest relationships with the spectral indices obtained by RGNIR images already at the initial times. Thus, although the RGB images have shown satisfactory results to obtain information about the quality of Tifton 85, the NIR band tends to increase the reliability of the relationships at early times.Sistemas de visão computacional podem ser uma alternativa aos métodos tradicionais de análise de qualidade de culturas forrageiras, permitindo o monitoramento da lavoura de forma instantânea, não destrutiva, e com redução de custos. Esta pesquisa teve como objetivo avaliar parâmetros de qualidade do capim Tifton 85 (Cynodon spp.) por meio de imagens digitais, relacionando índices espectrais com parâmetros de qualidade desta forrageira. Na área experimental foram aplicados quatro níveis de adubação nitrogenada e as análises foram realizadas em diferentes épocas após o corte de uniformização (14, 28, 42 e 56 dias). Os parâmetros de qualidade avaliados foram a matéria mineral, proteína bruta e fibra em detergente neutro. A partir de imagens obtidas na região espectral do visível (RGB) e do infravermelho próximo (RGNIR), foram gerados índices espectrais. A análise de componentes principais foi aplicada para condensar as informações obtidas pelos índices espectrais em um único componente principal (PC1). Os PC1 associados aos índices espectrais foram relacionados com os parâmetros de qualidade da forrageira para cada época de corte utilizando modelos de regressão quadrática simples. As relações da matéria mineral e os índices espectrais foram variáveis ao longo das épocas. A proteína bruta e fibra em detergente neutro apresentaram as maiores relações com os índices espectrais obtidos pelas imagens RGNIR já nas épocas iniciais. Assim, embora as imagens RGB tenham apresentado resultados satisfatórios para se obter informações sobre a qualidade do Tifton 85, a utilização da banda NIR tende a aumentar a confiabilidade das relações em instantes de tempo precoces.Universidade Federal Rural do Semi-Árido2024-02-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufersa.edu.br/caatinga/article/view/1213910.1590/1983-21252024v3712139rcREVISTA CAATINGA; Vol. 37 (2024); e12139Revista Caatinga; v. 37 (2024); e121391983-21250100-316Xreponame:Revista Caatingainstname:Universidade Federal Rural do Semi-Árido (UFERSA)instacron:UFERSAenghttps://periodicos.ufersa.edu.br/caatinga/article/view/12139/11456Copyright (c) 2024 Revista Caatingainfo:eu-repo/semantics/openAccessSouza, Jhiorranni FreitasCosta, Anderson GomideCarvalho, João Célio Luna deSantos, Lucas Andrade dosSilva, Vinícius PimentelBarros, Murilo Machado de2024-04-22T17:59:19Zoai:ojs.periodicos.ufersa.edu.br:article/12139Revistahttps://periodicos.ufersa.edu.br/index.php/caatinga/indexPUBhttps://periodicos.ufersa.edu.br/index.php/caatinga/oaipatricio@ufersa.edu.br|| caatinga@ufersa.edu.br1983-21250100-316Xopendoar:2024-04-29T09:47:07.524760Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA)true |
dc.title.none.fl_str_mv |
Relationship between spectral indices and quality parameters of tifton 85 forage Relação entre índices espectrais e parâmetros de qualidade da forrageira tifton 85 |
title |
Relationship between spectral indices and quality parameters of tifton 85 forage |
spellingShingle |
Relationship between spectral indices and quality parameters of tifton 85 forage Souza, Jhiorranni Freitas Cynodon spp. Pastagens. Visão computacional. Imagens digitais. Cynodon spp. Pastures. Computer vision. Digital images. |
title_short |
Relationship between spectral indices and quality parameters of tifton 85 forage |
title_full |
Relationship between spectral indices and quality parameters of tifton 85 forage |
title_fullStr |
Relationship between spectral indices and quality parameters of tifton 85 forage |
title_full_unstemmed |
Relationship between spectral indices and quality parameters of tifton 85 forage |
title_sort |
Relationship between spectral indices and quality parameters of tifton 85 forage |
author |
Souza, Jhiorranni Freitas |
author_facet |
Souza, Jhiorranni Freitas Costa, Anderson Gomide Carvalho, João Célio Luna de Santos, Lucas Andrade dos Silva, Vinícius Pimentel Barros, Murilo Machado de |
author_role |
author |
author2 |
Costa, Anderson Gomide Carvalho, João Célio Luna de Santos, Lucas Andrade dos Silva, Vinícius Pimentel Barros, Murilo Machado de |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Souza, Jhiorranni Freitas Costa, Anderson Gomide Carvalho, João Célio Luna de Santos, Lucas Andrade dos Silva, Vinícius Pimentel Barros, Murilo Machado de |
dc.subject.por.fl_str_mv |
Cynodon spp. Pastagens. Visão computacional. Imagens digitais. Cynodon spp. Pastures. Computer vision. Digital images. |
topic |
Cynodon spp. Pastagens. Visão computacional. Imagens digitais. Cynodon spp. Pastures. Computer vision. Digital images. |
description |
Computer vision systems can be an alternative to traditional methods of analyzing the quality of forage crops, allowing the instantaneous, non-destructive monitoring of the crop, with cost reduction. This study aimed to evaluate the quality parameters of Tifton 85 (Cynodon spp.) using digital images, relating spectral indices to the quality parameters of this forage. In the experimental area, four levels of nitrogen fertilization were applied and the analyses were made at different times after the standardization cut (14, 28, 42, and 56 days). The quality parameters evaluated were mineral matter, crude protein, and neutral detergent fiber. From images obtained in the visible (RGB) and near-infrared (RGNIR) spectral regions, spectral indices were generated. Principal component analysis was applied to summarize the information obtained by spectral indices into a single principal component (PC1). PC1 associated with spectral indices was related to forage quality parameters for each cutting time using simple quadratic regression models. The relationships between mineral matter and spectral indices were variable over time. Crude protein and neutral detergent fiber showed the highest relationships with the spectral indices obtained by RGNIR images already at the initial times. Thus, although the RGB images have shown satisfactory results to obtain information about the quality of Tifton 85, the NIR band tends to increase the reliability of the relationships at early times. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-02-02 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufersa.edu.br/caatinga/article/view/12139 10.1590/1983-21252024v3712139rc |
url |
https://periodicos.ufersa.edu.br/caatinga/article/view/12139 |
identifier_str_mv |
10.1590/1983-21252024v3712139rc |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufersa.edu.br/caatinga/article/view/12139/11456 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2024 Revista Caatinga info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2024 Revista Caatinga |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal Rural do Semi-Árido |
publisher.none.fl_str_mv |
Universidade Federal Rural do Semi-Árido |
dc.source.none.fl_str_mv |
REVISTA CAATINGA; Vol. 37 (2024); e12139 Revista Caatinga; v. 37 (2024); e12139 1983-2125 0100-316X reponame:Revista Caatinga instname:Universidade Federal Rural do Semi-Árido (UFERSA) instacron:UFERSA |
instname_str |
Universidade Federal Rural do Semi-Árido (UFERSA) |
instacron_str |
UFERSA |
institution |
UFERSA |
reponame_str |
Revista Caatinga |
collection |
Revista Caatinga |
repository.name.fl_str_mv |
Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA) |
repository.mail.fl_str_mv |
patricio@ufersa.edu.br|| caatinga@ufersa.edu.br |
_version_ |
1797674030349680640 |