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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
23/11/2016 |
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Actualizado : |
10/02/2020 |
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Autor : |
DEL PONTE, E. M.; MAIA, ALINE DE H. N.; DOS SANTOS, T. V.; MARTINS, E. J.; BAETHGEN, W. |
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Afiliación : |
EMERSON M. DEL PONTE, Faculdade de Agronomia, Universidade Federal do Rio Grande do Sul, Brazil; ALINE DE H. N. MAIA, Embrapa Meio Ambiente, Brazil; THIAGO V. DOS SANTOS, Faculdade de Agronomia, Universidade Federal do Rio Grande do Sul, Brazil; EDUARDO J. MARTINS, Faculdade de Agronomia, Universidade Federal do Rio Grande do Sul, Brazil; WALTER BAETHGEN, International Research Institute for Climate and Society (IRI), Columbia University, USA. |
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Título : |
Early-season warning of soybean rust regional epidemics using El Niño Southern/Oscillation information. |
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Fecha de publicación : |
2011 |
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Fuente / Imprenta : |
International Journal of Biometeorology, 2011, v. 55, no. 4, p. 575?583. |
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DOI : |
10.1007/s00484-010-0365-6 |
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Idioma : |
Inglés |
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Notas : |
Received: 20 May 2010 // Revised: 2 September 2010 // Accepted: 2 September 2010 // Published online: 21 September 2010 |
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Contenido : |
ABSTRACT.
Soybean rust (SBR) is a disease of significant impact to Brazilian soybean production. Twenty-four locations in a major growing region in southern Brazil, where long-term (30 years) weather information was available, were selected to estimate the risk of SBR epidemics and identify potential predictors derived from El Niño 3.4 region. A rainfall-based model was used to predict SBR severity in an ?epidemic development window? (the months of February and March for the studied region) in the time series. Twenty-eight daily simulations for each year-location (n = 720) were performed considering each day after 31 January as a hypothetical detection date (HDD) to estimate a severity index (SBRindex). The mean SBRindex in a single year was defined as the ?growing season severity index? (GSSI) for that year. A probabilistic risk assessment related GSSI and sea surface temperatures (SST) at the El Niño 3.4. region (here categorized as warm, cold or neutral phase) in October?November?December (OND) of the same growing season. Overall, the median GSSI across location-years was 34.5%. The risk of GSSI exceeding 60% was generally low and ranged from 0 to 20 percentage points, with the higher values found in the northern regions of the state when compared to the central-western. During a warm OND-SST phase, the probability of GSSI exceeding its overall mean (locations pooled) increased significantly by around 25 percentage points compared to neutral and cold SST phases, especially over the central western region. This study demonstrates the potential to use El Niño/Southern Oscillation information to anticipate the risk of SBR epidemics up to 1 month in advance at a regional scale.
@ ISB 2010 MenosABSTRACT.
Soybean rust (SBR) is a disease of significant impact to Brazilian soybean production. Twenty-four locations in a major growing region in southern Brazil, where long-term (30 years) weather information was available, were selected to estimate the risk of SBR epidemics and identify potential predictors derived from El Niño 3.4 region. A rainfall-based model was used to predict SBR severity in an ?epidemic development window? (the months of February and March for the studied region) in the time series. Twenty-eight daily simulations for each year-location (n = 720) were performed considering each day after 31 January as a hypothetical detection date (HDD) to estimate a severity index (SBRindex). The mean SBRindex in a single year was defined as the ?growing season severity index? (GSSI) for that year. A probabilistic risk assessment related GSSI and sea surface temperatures (SST) at the El Niño 3.4. region (here categorized as warm, cold or neutral phase) in October?November?December (OND) of the same growing season. Overall, the median GSSI across location-years was 34.5%. The risk of GSSI exceeding 60% was generally low and ranged from 0 to 20 percentage points, with the higher values found in the northern regions of the state when compared to the central-western. During a warm OND-SST phase, the probability of GSSI exceeding its overall mean (locations pooled) increased significantly by around 25 percentage points compared to neutral and cold SST phases, especial... Presentar Todo |
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Palabras claves : |
AGRICULTURAL RISK; EL NIÑO; PLANT DISEASE; PROBABILISTIC RISK ASSESSMENT. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 02596naa a2200241 a 4500
001 1056122
005 2020-02-10
008 2011 bl uuuu u00u1 u #d
024 7 $a10.1007/s00484-010-0365-6$2DOI
100 1 $aDEL PONTE, E. M.
245 $aEarly-season warning of soybean rust regional epidemics using El Niño Southern/Oscillation information.$h[electronic resource]
260 $c2011
500 $aReceived: 20 May 2010 // Revised: 2 September 2010 // Accepted: 2 September 2010 // Published online: 21 September 2010
520 $aABSTRACT. Soybean rust (SBR) is a disease of significant impact to Brazilian soybean production. Twenty-four locations in a major growing region in southern Brazil, where long-term (30 years) weather information was available, were selected to estimate the risk of SBR epidemics and identify potential predictors derived from El Niño 3.4 region. A rainfall-based model was used to predict SBR severity in an ?epidemic development window? (the months of February and March for the studied region) in the time series. Twenty-eight daily simulations for each year-location (n = 720) were performed considering each day after 31 January as a hypothetical detection date (HDD) to estimate a severity index (SBRindex). The mean SBRindex in a single year was defined as the ?growing season severity index? (GSSI) for that year. A probabilistic risk assessment related GSSI and sea surface temperatures (SST) at the El Niño 3.4. region (here categorized as warm, cold or neutral phase) in October?November?December (OND) of the same growing season. Overall, the median GSSI across location-years was 34.5%. The risk of GSSI exceeding 60% was generally low and ranged from 0 to 20 percentage points, with the higher values found in the northern regions of the state when compared to the central-western. During a warm OND-SST phase, the probability of GSSI exceeding its overall mean (locations pooled) increased significantly by around 25 percentage points compared to neutral and cold SST phases, especially over the central western region. This study demonstrates the potential to use El Niño/Southern Oscillation information to anticipate the risk of SBR epidemics up to 1 month in advance at a regional scale. @ ISB 2010
653 $aAGRICULTURAL RISK
653 $aEL NIÑO
653 $aPLANT DISEASE
653 $aPROBABILISTIC RISK ASSESSMENT
700 1 $aMAIA, ALINE DE H. N.
700 1 $aDOS SANTOS, T. V.
700 1 $aMARTINS, E. J.
700 1 $aBAETHGEN, W.
773 $tInternational Journal of Biometeorology, 2011$gv. 55, no. 4, p. 575?583.
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| 1. |  | LEADLEY, P.; GONZALEZ, A.; OBURA, D.; KRUG, C.B.; LONDOÑO-MURCIA, M.C.; MILLETTE, K.L.; RADULOVICI, A.; RANKOVIC, A.; SHANNON, L.J.; ARCHER, E.; ATO ARMAH, F.; NIC BAX, N,; CHAUDHARI, K.; COSTELLO, M.J.; DÁVALOS, L.M.; ROQUE, F DE O; DECLERCK, F.; DEE, L.E.; ESSL, F.; FERRIER, S.; GENOVESI, P.; GUARIGUATA, M.R.; HASHIMOTO, S.; IFEJIKA SPERANZA, CH.; ISBELL, F.; KOK, M.; LAVERY, S.D.; LECLÈRE, D.; LOYOLA, R.; LWASA, S.; MCGEOCH, M.; MORI, A.S.; NICHOLSON, E.; OCHOA, J.M.; ÖLLERER, K.; POLASKY, S.; RONDININI, C.; SCHROER, S.; SELOMANE, O.; SHEN, X.; STRASSBURG, B.; RASHID SUMAILA, U.; TITTENSOR, D.P.; TURAK, E.; URBINA, L.; VALLEJOS, M.; VÁZQUEZ-DOMÍNGUEZ, E.; VERBURG, P.H.; VISCONTI, P.; WOODLEY, S.; XU, J. Achieving global biodiversity goals by 2050 requires urgent and integrated actions. One Earth, 2022, Volume 5, Issue 6, Pages 597-603. doi: https://doi.org/10.1016/j.oneear.2022.05.009 Artticle history: Available online 17 June 2022, Version of Record 17 June 2022.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
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