Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2012 |
| Outros Autores: | , , , , , |
| Tipo de documento: | Artigo |
| Idioma: | por |
| Título da fonte: | Revista Eletrônica Competências Digitais para Agricultura Familiar |
| Texto Completo: | https://owl.tupa.unesp.br/recodaf/index.php/recodaf/article/view/178 |
Resumo: | Abstract: The aim was to evaluate an RGB image for identify grain yield potential in maize before physiological maturity in a semi-arid region. A randomized complete block design with two replications was employed, to access 50 maize genotypes. Two drone flights were conducted at different time points, specifically 27 and 46 days after planting (DAP), at flight heights of 40, 60, and 80 meters. A total of 29 vegetation indices were used in the analysis. Analysis of variance revealed genetic variability among the genotypes, enabling the selection of promising materials. By assessing the repeatability of vegetation indices, the optimal flight date was determined. Temporal BLUP (Best Linear Unbiased Prediction) allowed for the categorization of materials as high or low performers, considering the mean grain yield, and identified the most productive materials during the vegetative phenological stage of the crop. It is recommended, to conduct flights at 27 DAP at an height of 80 meters. The TGI (Triangular Greenness Index) and Green indices proved to be indicative of early predictions of material productivity. It is suggested to maintain the experimental area free from biotic and abiotic interferences and to conduct additional flights, thus optimizing aerial image phenotyping. |
| id |
UNESP-30_4c2760ce349dda9283a102c33d864148 |
|---|---|
| oai_identifier_str |
oai:codaf.tupa.unesp.br:8082:article/178 |
| network_acronym_str |
UNESP-30 |
| network_name_str |
Revista Eletrônica Competências Digitais para Agricultura Familiar |
| repository_id_str |
|
| spelling |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stageProtocolo de procesamiento de imágenes aéreas RGB para la identificación de potenciales genotipos de maíz en estado vegetativoProtocolo de processamento de imagens RGB aéreas para identificação de genótipos potenciais de milho em fase vegetativaPlant breedingVegetation indicesPlant breeding. Vegetation indices. Zea mays L.Melhoramento de plantasÍndices de vegetaçãoZea mays LMejoramiento vegetalÍndices de vegetaciónZea mays lAbstract: The aim was to evaluate an RGB image for identify grain yield potential in maize before physiological maturity in a semi-arid region. A randomized complete block design with two replications was employed, to access 50 maize genotypes. Two drone flights were conducted at different time points, specifically 27 and 46 days after planting (DAP), at flight heights of 40, 60, and 80 meters. A total of 29 vegetation indices were used in the analysis. Analysis of variance revealed genetic variability among the genotypes, enabling the selection of promising materials. By assessing the repeatability of vegetation indices, the optimal flight date was determined. Temporal BLUP (Best Linear Unbiased Prediction) allowed for the categorization of materials as high or low performers, considering the mean grain yield, and identified the most productive materials during the vegetative phenological stage of the crop. It is recommended, to conduct flights at 27 DAP at an height of 80 meters. The TGI (Triangular Greenness Index) and Green indices proved to be indicative of early predictions of material productivity. It is suggested to maintain the experimental area free from biotic and abiotic interferences and to conduct additional flights, thus optimizing aerial image phenotyping.Resumen: El objetivo fue evaluar un protocolo de imágenes RGB para identificar la productividad del grano de maíz antes de la madurez fisiológica en una región semiárida. Se utilizó DBC, con dos repeticiones para evaluar 50 genotipos de maíz. Se realizaron dos vuelos en diferentes fechas, 27 y 46 días después de la siembra (DAP) con alturas de 40, 60 y 80 m. Se utilizaron 29 índices de vegetación. El análisis de varianza destacó la variabilidad genética entre genotipos, lo que permitió la selección de materiales prometedores. Con la repetibilidad de los índices de vegetación se determinó la mejor fecha para el vuelo. Las estimaciones del BLUP temporal permitieron categorizar los materiales como de alto o bajo rendimiento, considerando la productividad promedio del grano y la distinción de los materiales más productivos durante la etapa fenológica vegetativa del cultivo. Por ello se recomienda realizar vuelos a las 27 DAP, a una altura de 80 m. Los índices TGI y Vegetación verde resultaron indicativos para la predicción temprana del potencial productivo de los materiales. Se recomienda mantener el área experimental libre de interferencias bióticas y abióticas y realizar vuelos adicionales, optimizando así el fenotipado mediante imágenes aéreas.Resumo: Objetivou-se avaliar um protocolo de imagens RGB, para identificação da produtividade de grãos do milho antes da maturidade fisiológica em região semiárida. Utilizou-se o DBC, com duas repetições para avaliar 50 genótipos de milho. Realizou-se dois voos em diferentes datas, 27 e 46 dias após o plantio (DAP) com alturas de 40, 60 e 80 m. Utilizou-se 29 índices de vegetação. A análise de variância evidenciou a variabilidade genética entre os genótipos, permitindo a seleção de materiais promissores. Com as repetibilidades dos índices de vegetação, determinou-se a melhor data para voo. As estimativas dos BLUP temporais, permitiram categorizar os materiais como sendo de alto ou baixo desempenho, considerando a média da produtividade de grãos e a distinção dos materiais mais produtivos durante o estágio fenológico vegetativo da cultura. Recomenda-se, portanto, a realização de voos com 27 DAP, a uma altura de 80 m. Os índices de vegetação TGI e Green demonstraram ser indicativos para previsão precoce do potencial produtivo dos materiais. Indica-se manter a área experimental livre de interferências bióticas e abióticas e conduzir voos adicionais, otimizando assim a fenotipagem por imagens aéreas.Universidade Estadual Paulista2012-12-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPaper peer-reviewedapplication/pdfhttps://owl.tupa.unesp.br/recodaf/index.php/recodaf/article/view/178Electronic Journal Digital Skills for Family Farming; Vol. 9 No. 2 (2023): Electronic Journal Digital Skills for Family Farming; 149-173Revista Electrónica Competencias Digitales para Agricultura Familiar; Vol. 9 Núm. 2 (2023): Revista Electrónica Competencias Digitales para Agricultura Familiar; 149-173Revista Eletrônica Competências Digitais para Agricultura Familiar; v. 9 n. 2 (2023): Revista Competências Digitais para Agricultura Familiar; 149-1732448-0452reponame:Revista Eletrônica Competências Digitais para Agricultura Familiarinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporhttps://owl.tupa.unesp.br/recodaf/index.php/recodaf/article/view/178/404http://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessNascimento Santos, BarbaraCosta Aragão, Nartênia SusaneRodrigues Barreto, Mário SérgioRocha Azevedo Santos, HenriqueSouza Santos, Jacilene FranciscaFlorentino Cordeiro Junior, José JairoFerreira de Oliveira, Gustavo Hugo2024-02-10T12:55:06Zoai:codaf.tupa.unesp.br:8082:article/178Revistahttp://owl.tupa.unesp.br/recodaf/index.php/recodafPUBhttp://owl.tupa.unesp.br/recodaf/index.php/recodaf/oai||fernando@rodrigues.pro.br2448-04522448-0452opendoar:2024-02-10T12:55:06Revista Eletrônica Competências Digitais para Agricultura Familiar - Universidade Estadual Paulista (UNESP)false |
| dc.title.none.fl_str_mv |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage Protocolo de procesamiento de imágenes aéreas RGB para la identificación de potenciales genotipos de maíz en estado vegetativo Protocolo de processamento de imagens RGB aéreas para identificação de genótipos potenciais de milho em fase vegetativa |
| title |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage |
| spellingShingle |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage Nascimento Santos, Barbara Plant breeding Vegetation indices Plant breeding. Vegetation indices. Zea mays L. Melhoramento de plantas Índices de vegetação Zea mays L Mejoramiento vegetal Índices de vegetación Zea mays l |
| title_short |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage |
| title_full |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage |
| title_fullStr |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage |
| title_full_unstemmed |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage |
| title_sort |
Aerial RGB image processing protocol for identifying potential maize genotypes in the vegetative stage |
| author |
Nascimento Santos, Barbara |
| author_facet |
Nascimento Santos, Barbara Costa Aragão, Nartênia Susane Rodrigues Barreto, Mário Sérgio Rocha Azevedo Santos, Henrique Souza Santos, Jacilene Francisca Florentino Cordeiro Junior, José Jairo Ferreira de Oliveira, Gustavo Hugo |
| author_role |
author |
| author2 |
Costa Aragão, Nartênia Susane Rodrigues Barreto, Mário Sérgio Rocha Azevedo Santos, Henrique Souza Santos, Jacilene Francisca Florentino Cordeiro Junior, José Jairo Ferreira de Oliveira, Gustavo Hugo |
| author2_role |
author author author author author author |
| dc.contributor.author.fl_str_mv |
Nascimento Santos, Barbara Costa Aragão, Nartênia Susane Rodrigues Barreto, Mário Sérgio Rocha Azevedo Santos, Henrique Souza Santos, Jacilene Francisca Florentino Cordeiro Junior, José Jairo Ferreira de Oliveira, Gustavo Hugo |
| dc.subject.por.fl_str_mv |
Plant breeding Vegetation indices Plant breeding. Vegetation indices. Zea mays L. Melhoramento de plantas Índices de vegetação Zea mays L Mejoramiento vegetal Índices de vegetación Zea mays l |
| topic |
Plant breeding Vegetation indices Plant breeding. Vegetation indices. Zea mays L. Melhoramento de plantas Índices de vegetação Zea mays L Mejoramiento vegetal Índices de vegetación Zea mays l |
| description |
Abstract: The aim was to evaluate an RGB image for identify grain yield potential in maize before physiological maturity in a semi-arid region. A randomized complete block design with two replications was employed, to access 50 maize genotypes. Two drone flights were conducted at different time points, specifically 27 and 46 days after planting (DAP), at flight heights of 40, 60, and 80 meters. A total of 29 vegetation indices were used in the analysis. Analysis of variance revealed genetic variability among the genotypes, enabling the selection of promising materials. By assessing the repeatability of vegetation indices, the optimal flight date was determined. Temporal BLUP (Best Linear Unbiased Prediction) allowed for the categorization of materials as high or low performers, considering the mean grain yield, and identified the most productive materials during the vegetative phenological stage of the crop. It is recommended, to conduct flights at 27 DAP at an height of 80 meters. The TGI (Triangular Greenness Index) and Green indices proved to be indicative of early predictions of material productivity. It is suggested to maintain the experimental area free from biotic and abiotic interferences and to conduct additional flights, thus optimizing aerial image phenotyping. |
| publishDate |
2012 |
| dc.date.none.fl_str_mv |
2012-12-31 |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Paper peer-reviewed |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
https://owl.tupa.unesp.br/recodaf/index.php/recodaf/article/view/178 |
| url |
https://owl.tupa.unesp.br/recodaf/index.php/recodaf/article/view/178 |
| dc.language.iso.fl_str_mv |
por |
| language |
por |
| dc.relation.none.fl_str_mv |
https://owl.tupa.unesp.br/recodaf/index.php/recodaf/article/view/178/404 |
| dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0 info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0 |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista |
| publisher.none.fl_str_mv |
Universidade Estadual Paulista |
| dc.source.none.fl_str_mv |
Electronic Journal Digital Skills for Family Farming; Vol. 9 No. 2 (2023): Electronic Journal Digital Skills for Family Farming; 149-173 Revista Electrónica Competencias Digitales para Agricultura Familiar; Vol. 9 Núm. 2 (2023): Revista Electrónica Competencias Digitales para Agricultura Familiar; 149-173 Revista Eletrônica Competências Digitais para Agricultura Familiar; v. 9 n. 2 (2023): Revista Competências Digitais para Agricultura Familiar; 149-173 2448-0452 reponame:Revista Eletrônica Competências Digitais para Agricultura Familiar instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
| instname_str |
Universidade Estadual Paulista (UNESP) |
| instacron_str |
UNESP |
| institution |
UNESP |
| reponame_str |
Revista Eletrônica Competências Digitais para Agricultura Familiar |
| collection |
Revista Eletrônica Competências Digitais para Agricultura Familiar |
| repository.name.fl_str_mv |
Revista Eletrônica Competências Digitais para Agricultura Familiar - Universidade Estadual Paulista (UNESP) |
| repository.mail.fl_str_mv |
||fernando@rodrigues.pro.br |
| _version_ |
1797239941102567424 |