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Biblioteca(s): |
Embrapa Trigo. |
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Data corrente: |
12/08/2024 |
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Data da última atualização: |
12/08/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
RODIGHERI, G.; FONTANA, D. C.; LUZ, L. B. da; DALMAGO, G. A.; SCHIRMBECK, L. W.; SCHIRMBECK, J.; GOUVEA, J. A. de; CUNHA, G. R. da. |
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Afiliação: |
GRAZIELI RODIGHERI, UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL; DENISE CYBIS FONTANA, UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL; LUANA BECKER DA LUZ, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS; GENEI ANTONIO DALMAGO, CNPT; LUCIMARA WOLFARTH SCHIRMBECK, UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL; JULIANO SCHIRMBECK, UNIVERSIDADE DO VALE DO TAQUARI; JORGE ALBERTO DE GOUVEA, CNPT; GILBERTO ROCCA DA CUNHA, CNPT. |
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Título: |
TVDI-based water stress coefficient to estimate net primary productivity in soybean areas. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Ecological Modelling, v. 490, 110636, Apr. 2024. |
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Idioma: |
Português |
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Conteúdo: |
Net Primary Productivity (NPP) is a major parameter to assess carbon (C) increments by crops. Many models based on Light Use Efficiency (LUE) have been developed to estimate NPP in different regions. LUE in different ecosystems is reduced by environmental stressors, such as those caused by water restrictions. However, few studies have used remote sensing data to estimate water stress coefficients. Thus, our goal was to evaluate the performance of the Carnegie-Ames-Stanford-Approach (CASA) model using Temperature-Vegetation Dryness Index (TVDI) as a water stress coefficient to quantify NPP dynamics in agricultural ecosystems in northwestern Rio Grande do Sul state, in Brazil. Weather data from the ERA5 and surface weather stations were used to estimate NPP. Surface temperature (LST), Normalized Difference Vegetation Index (NDVI), estimated (EET) and potential (PET) evapotranspiration data were retrieved from Landsat/OLI and Terra/MODIS and used as input in the model. The CASA model was evaluated using ground-based data and then applied to the agricultural region of study. NPP data obtained using the CASA model and remote sensing data were in accordance with the observed data (RMSE less than 30 gC m�� 2 month�� 1 and r higher than 0,97), highlighting the model’s efficiency in representing the temporal variations of NPP in the experimental area. The high correlation between simulated and observed data indicates that the TVDI is suitable for use as a water stress index. This work may serve as a baseline for future studies, which could explore the use of other indices and enhance NPP estimates. MenosNet Primary Productivity (NPP) is a major parameter to assess carbon (C) increments by crops. Many models based on Light Use Efficiency (LUE) have been developed to estimate NPP in different regions. LUE in different ecosystems is reduced by environmental stressors, such as those caused by water restrictions. However, few studies have used remote sensing data to estimate water stress coefficients. Thus, our goal was to evaluate the performance of the Carnegie-Ames-Stanford-Approach (CASA) model using Temperature-Vegetation Dryness Index (TVDI) as a water stress coefficient to quantify NPP dynamics in agricultural ecosystems in northwestern Rio Grande do Sul state, in Brazil. Weather data from the ERA5 and surface weather stations were used to estimate NPP. Surface temperature (LST), Normalized Difference Vegetation Index (NDVI), estimated (EET) and potential (PET) evapotranspiration data were retrieved from Landsat/OLI and Terra/MODIS and used as input in the model. The CASA model was evaluated using ground-based data and then applied to the agricultural region of study. NPP data obtained using the CASA model and remote sensing data were in accordance with the observed data (RMSE less than 30 gC m�� 2 month�� 1 and r higher than 0,97), highlighting the model’s efficiency in representing the temporal variations of NPP in the experimental area. The high correlation between simulated and observed data indicates that the TVDI is suitable for use as a water stress index. This wor... Mostrar Tudo |
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Thesagro: |
Produtividade; Soja. |
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Thesaurus Nal: |
Primary productivity; Soybeans; Water stress. |
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Categoria do assunto: |
-- |
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Marc: |
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Registro original: |
Embrapa Trigo (CNPT) |
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| 1. |  | PAGAN, C.; COYNE, D.; CARNEIRO, R.; KARIUKI, G.; LUAMBANO, N.; AFFOKPON, A.; WILLIAMSON, V. M. Mitochondrial haplotype-based identification of ethanol-preserved root-knot nematodes from Africa. Phytopathology, v. 105, n. 3, p. 350-357, 2015.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 2. | | PAGAN, C.; COYNE, D.; KARIUKI, G.; CARNEIRO, R. M. D. G.; WILLIAMSON, V. M. Mitochondrial haplotypes for identification of tropical root-knot nematode species and Lineages. Journal of Nematology, v. 46, n. 2, p. 216, June 2014. Edição dos Proceedings do 6th International Congress of Nematology, Cape Town, South Africa, May 2014.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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