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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
19/08/2021 |
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Data da última atualização: |
19/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
COSTA, W. G. da; BARBOSA, I. de P.; SOUZA, J. E. de; CRUZ, C. D.; NASCIMENTO, M.; OLIVEIRA, A. C. B. de. |
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Afiliação: |
WEVERTON GOMES DA COSTA, UFV; IVAN DE PAIVA BARBOSA, UFV; JACQUELINE ENEQUIO DE SOUZA, UFV; COSME DAMIÃO CRUZ, UFV; MOYSÉS NASCIMENTO, UFV; ANTONIO CARLOS BAIAO DE OLIVEIRA, CNPCa. |
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Título: |
Machine learning and statistics to qualify environments through multi-traits in Coffea arabica. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
PLoS One, v. 16, n. 1, : e0245298, 2021. |
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DOI: |
https://doi.org/10.1371/journal.pone.0245298 |
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Idioma: |
Inglês |
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Conteúdo: |
Several factors such as genotype, environment, and post-harvest processing can affect the responses of important traits in the coffee production chain. Determining the influence of these factors is of great relevance, as they can be indicators of the characteristics of the coffee produced. The most efficient models choice to be applied should take into account the variety of information and the particularities of each biological material. This study was developed to evaluate statistical and machine learning models that would better discriminate environments through multi-traits of coffee genotypes and identify the main agronomic and beverage quality traits responsible for the variation of the environments. For that, 31 morpho-agronomic and post-harvest traits were evaluated, from field experiments installed in three municipalities in the Matas de Minas region, in the State of Minas Gerais, Brazil. Two types of post-harvest processing were evaluated: natural and pulped. The apparent error rate was estimated for each method. The Multilayer Perceptron and Radial Basis Function networks were able to discriminate the coffee samples in multi-environment more efficiently than the other methods, identifying differences in multi-traits responses according to the production sites and type of post-harvest processing. The local factors did not present specific traits that favored the severity of diseases and differentiated vegetative vigor. Sensory traits acidity and fragrance/aroma score also made little contribution to the discrimination process, indicating that acidity and fragrance/aroma are characteristic of coffee produced and all coffee samples evaluated are of the special type in the Mata of Minas region. The main traits responsible for the differentiation of production sites are plant height, fruit size, and bean production. The sensory trait "Body" is the main one to discriminate the form of post-harvest processing. MenosSeveral factors such as genotype, environment, and post-harvest processing can affect the responses of important traits in the coffee production chain. Determining the influence of these factors is of great relevance, as they can be indicators of the characteristics of the coffee produced. The most efficient models choice to be applied should take into account the variety of information and the particularities of each biological material. This study was developed to evaluate statistical and machine learning models that would better discriminate environments through multi-traits of coffee genotypes and identify the main agronomic and beverage quality traits responsible for the variation of the environments. For that, 31 morpho-agronomic and post-harvest traits were evaluated, from field experiments installed in three municipalities in the Matas de Minas region, in the State of Minas Gerais, Brazil. Two types of post-harvest processing were evaluated: natural and pulped. The apparent error rate was estimated for each method. The Multilayer Perceptron and Radial Basis Function networks were able to discriminate the coffee samples in multi-environment more efficiently than the other methods, identifying differences in multi-traits responses according to the production sites and type of post-harvest processing. The local factors did not present specific traits that favored the severity of diseases and differentiated vegetative vigor. Sensory traits acidity and fragrance/aroma sco... Mostrar Tudo |
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Thesagro: |
Análise Estatística; Cadeia Produtiva; Café; Genótipo; Pós-Colheita; Processamento. |
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Thesaurus Nal: |
Coffea arabica var. arabica; Genotype-environment interaction; Postharvest systems; Statistical analysis; Statistical models. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/225351/1/Machine-learning-and-statistics-to-qualify.pdf
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Marc: |
LEADER 02940naa a2200325 a 4500
001 2133732
005 2021-08-19
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1371/journal.pone.0245298$2DOI
100 1 $aCOSTA, W. G. da
245 $aMachine learning and statistics to qualify environments through multi-traits in Coffea arabica.$h[electronic resource]
260 $c2021
520 $aSeveral factors such as genotype, environment, and post-harvest processing can affect the responses of important traits in the coffee production chain. Determining the influence of these factors is of great relevance, as they can be indicators of the characteristics of the coffee produced. The most efficient models choice to be applied should take into account the variety of information and the particularities of each biological material. This study was developed to evaluate statistical and machine learning models that would better discriminate environments through multi-traits of coffee genotypes and identify the main agronomic and beverage quality traits responsible for the variation of the environments. For that, 31 morpho-agronomic and post-harvest traits were evaluated, from field experiments installed in three municipalities in the Matas de Minas region, in the State of Minas Gerais, Brazil. Two types of post-harvest processing were evaluated: natural and pulped. The apparent error rate was estimated for each method. The Multilayer Perceptron and Radial Basis Function networks were able to discriminate the coffee samples in multi-environment more efficiently than the other methods, identifying differences in multi-traits responses according to the production sites and type of post-harvest processing. The local factors did not present specific traits that favored the severity of diseases and differentiated vegetative vigor. Sensory traits acidity and fragrance/aroma score also made little contribution to the discrimination process, indicating that acidity and fragrance/aroma are characteristic of coffee produced and all coffee samples evaluated are of the special type in the Mata of Minas region. The main traits responsible for the differentiation of production sites are plant height, fruit size, and bean production. The sensory trait "Body" is the main one to discriminate the form of post-harvest processing.
650 $aCoffea arabica var. arabica
650 $aGenotype-environment interaction
650 $aPostharvest systems
650 $aStatistical analysis
650 $aStatistical models
650 $aAnálise Estatística
650 $aCadeia Produtiva
650 $aCafé
650 $aGenótipo
650 $aPós-Colheita
650 $aProcessamento
700 1 $aBARBOSA, I. de P.
700 1 $aSOUZA, J. E. de
700 1 $aCRUZ, C. D.
700 1 $aNASCIMENTO, M.
700 1 $aOLIVEIRA, A. C. B. de
773 $tPLoS One$gv. 16, n. 1, : e0245298, 2021.
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Registro original: |
Embrapa Café (CNPCa) |
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Registro Completo
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
11/05/1997 |
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Data da última atualização: |
28/07/2023 |
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Autoria: |
MAGALHÃES, A. F. de J.; SOUZA, L. F. da S. |
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Afiliação: |
ANTONIA FÔNSECA DE JESUS MAGALHÃES, CNPMF; LUIZ FRANCISCO DA SILVA SOUZA. |
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Título: |
Estudo da relação N/S em solos de Tabuleiro do Recôncavo da Bahia. |
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Ano de publicação: |
1983 |
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Fonte/Imprenta: |
Cruz das Almas: Embrapa Mandioca e Fruticultura, 1983. |
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Páginas: |
19 p. |
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Série: |
(Embrapa Mandioca e Fruticultura. Boletim de Pesquisa, 3). |
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ISSN: |
0101-5117 |
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Idioma: |
Português |
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Notas: |
Memória. |
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Conteúdo: |
Foram realiazados 18 ensaios em casa de vegetação visando definir a melhor relação N/S para os solos de "tabuleiro" do Recôncavo em áreas representativas dos municípios de Amélia Rodrigues, Cachoeira, Conceição do Almeida (IBF e EEFT), Cruz das Almas, Feira de Santana; Jaguaripe, Muritiba e Santo Antonio de Jesus. Foram usadas duas plantas indicadoras (Sorghum vulgare Pers. E Medicago sativa L.) testando em onze tratamentos os efeitos de oito relações N/S. Dos resultados obtidos concluiu-se que uma relação N/S = 8 foi a mais indicada para estes solos. |
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Palavras-Chave: |
Bahia; Brasil; Fertilizantes; Solos. |
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Thesagro: |
Enxofre; Mandioca; Nitrogênio; Solo. |
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Categoria do assunto: |
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P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/81327/1/Estudo-da-relacao-Antonia-Magalhaes-Boletim-de-Pesquisa-3-1983.pdf
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Marc: |
LEADER 01285nam a2200265 a 4500
001 1638082
005 2023-07-28
008 1983 bl uuuu u0uu1 u #d
022 $a0101-5117
100 1 $aMAGALHÃES, A. F. de J.
245 $aEstudo da relação N/S em solos de Tabuleiro do Recôncavo da Bahia.
260 $aCruz das Almas: Embrapa Mandioca e Fruticultura$c1983
300 $a19 p.
490 $a(Embrapa Mandioca e Fruticultura. Boletim de Pesquisa, 3).
500 $aMemória.
520 $aForam realiazados 18 ensaios em casa de vegetação visando definir a melhor relação N/S para os solos de "tabuleiro" do Recôncavo em áreas representativas dos municípios de Amélia Rodrigues, Cachoeira, Conceição do Almeida (IBF e EEFT), Cruz das Almas, Feira de Santana; Jaguaripe, Muritiba e Santo Antonio de Jesus. Foram usadas duas plantas indicadoras (Sorghum vulgare Pers. E Medicago sativa L.) testando em onze tratamentos os efeitos de oito relações N/S. Dos resultados obtidos concluiu-se que uma relação N/S = 8 foi a mais indicada para estes solos.
650 $aEnxofre
650 $aMandioca
650 $aNitrogênio
650 $aSolo
653 $aBahia
653 $aBrasil
653 $aFertilizantes
653 $aSolos
700 1 $aSOUZA, L. F. da S.
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Embrapa Mandioca e Fruticultura (CNPMF) |
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