Zobrazeno 1 - 10 of 17 pro vyhledávání: '"IGOR CRISTIAN DE OLIVEIRA VIEIRA"'
2
ÍNDICE DE ESTRESSE HÍDRICO DO FEIJÃO-CAUPI EM DIFERENTES DISPONIBILIDADES HÍDRICAS EM CASTANHAL-PA
Autor: ERIKA DE OLIVEIRA TEIXEIRA DE CARVALHO, DEBORAH LUCIANY PIRES COSTA, IGOR CRISTIAN DE OLIVEIRA VIEIRA, BRUNO GAMA FERREIRA, HILDO GIUSEPPE GARCIA CALDAS NUNES, PAULO JORGE DE OLIVEIRA PONTE DE SOUZA
Publikováno v: Revista Caatinga, Volume: 35, Issue: 3, Pages: 711-721, Published: 22 AUG 2022
REVISTA CAATINGA; Vol. 35 No. 3 (2022); 711-721
Revista Caatinga; v. 35 n. 3 (2022); 711-721
Revista Caatinga
Universidade Federal Rural do Semi-Árido (UFERSA)
instacron:UFERSA
Cowpea is a crop of great socioeconomic relevance for the populations of the North and Northeast of the country, and its low yield is commonly related to environmental stresses, especially water. The objective of this study was to evaluate the water
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d08f7d4c06b43b1ccf6d44912b589432
https://doi.org/10.1590/1983-21252022v35n322rc
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3
PRODUTIVIDADE E EFICIÊNCIA DO USO DA ÁGUA DE CUPUAÇUZEIRO IRRIGADO NAS CONDIÇÕES CLIMÁTICAS DE CASTANHAL-PA, AMAZÔNIA BRASILEIRA
Autor: Deborah Luciany Pires Costa, Igor Cristian de Oliveira Vieira, Erika de Oliveira Teixeira de Carvalho, Matheus Yan Freitas Silva, Maria de Lourdes Alcântara Velame, Paulo Jorge de Oliveira Ponte de Souza
Publikováno v: IRRIGA. 27:1-15
PRODUTIVIDADE E EFICIÊNCIA DO USO DA ÁGUA DE CUPUAÇUZEIRO IRRIGADO NAS CONDIÇÕES CLIMÁTICAS DE CASTANHAL-PA, AMAZÔNIA BRASILEIRA DEBORAH LUCIANY PIRES COSTA 1; IGOR CRISTIAN DE OLIVEIRA VIEIRA 2; ERIKA DE OLIVEIRA TEIXEIRA3; MATHEUS YAN FREITA
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7815953a64e6dcb6521812bdb2c18a99
https://doi.org/10.15809/irriga.2022v27n1p1-15
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5
Biophysical controls of evapotranspiration in cowpea cultivation under different water regimes
Autor: João Vitor de Nóvoa Pinto, Thieres George Freire da Silva, Paulo Jorge de Oliveira Ponte de Souza, Daniely Florencia Silva de Souza, Deborah Luciany Pires Costa, Igor Cristian de Oliveira Vieira
Publikováno v: Revista Brasileira de Engenharia Agrícola e Ambiental v.23 n.10 2019
Revista Brasileira de Engenharia Agrícola e Ambiental
Universidade Federal de Campina Grande (UFCG)
instacron:UFCG
Revista Brasileira de Engenharia Agrícola e Ambiental-Agriambi, Vol 23, Iss 10, Pp 725-732
The objective of this study was to analyze the variations of the decoupling factor and the aerodynamic and stomatal conductances for cowpea subjected to different levels of water availability during the reproductive phenological stages of the crop. T
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b2c61d73064186a50533e93e177946b
https://doi.org/10.1590/1807-1929/agriambi.v23n10p725-732
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6
Performance of the AquaCrop model in the climate risk analysis and yield prediction of cowpea (Vigna Unguiculatta L. Walp)
Autor: João Vitor de Nóvoa Pinto, Vivian Dielly da Silva Farias, Denilson Pontes Ferreira, Evandro Chaves de Oliveira, Hildo Giuseppe Garcia Caldas Nunes, Igor Cristian de Oliveira Vieira, Denis de Pinho Sousa, Paulo Jorge de Oliveira Ponte de Souza, Vandeilson Belfort Moura
Publikováno v: Australian Journal of Crop Science. :1105-1112
The present work evaluated the Aquacrop model as a tool for climate risk analysis and yield prediction of cowpea, cultivated in a dystrophic yellow oxisol. The model was previously calibrated and validated for two harvests, in order to simulate the b
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ff62335974ac6286bacc166a61d4fe5f
https://doi.org/10.21475/ajcs.19.13.07.p1590
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8
Machine learning algorithms for soybean yield forecasting in the Brazilian Cerrado
Autor: Valter Barbosa dos Santos, Aline Moreno Ferreira dos Santos, José Reinaldo da Silva Cabral de Moraes, Igor Cristian de Oliveira Vieira, Glauco de Souza Rolim
Publikováno v: Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Made available in DSpace on 2022-04-29T08:38:00Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 BACKGROUND: We evaluated different machine learning (ML) models for predicting soybean productivity up to 1 month in advance for the Matopiba
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7908370d054ee036ffb63267e8651499
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