Análise de risco das mudanças climáticas globais sobre a sigatoka-negra da bananeira no Brasil

Ghini, R.; Hamada, E.; Gonçalves, Renata Ribeiro do Valle; Gasparotto, L.; Pereira, Jonny Everson Scherwinski

doi:10.1590/s0100-41582007000300003

Cited by 32 publications

(36 citation statements)

References 12 publications

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“…These changes will be gradual for the decades of 2020, 2050 and 2080, with some exceptions that will be presented later in this paper. Results are in agreement with Ghini et al (2007) who predicted that there will be a reduction of the favorable area to BS in Brazil in the future. Other authors also showed changes on the spatial distribution of favorability classes for other pathosystems in the future, like Carter et al (1996), Boag et al (1991), Brasier & Scott (1994) and Brasier et al (1996).…”

Section: Resultssupporting

confidence: 90%

“…Complete results for simulations based on the six different climate change models and the "multimodel ensemble" are presented in Tables 2 to 4. The intervals used in this study to characterize classes of favorability to BS were adequate because the obtained maps considering the current climate (Figure 1) were in agreement with data available in the literature (Mourichon et al, 1997;Carlier et al, 2000;Ghini et al, 2007). The pathogen produces conidia and ascospores and both play roles in the spread of the disease.…”

Section: Resultssupporting

confidence: 78%

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Worldwide geographical distribution of Black Sigatoka for banana: predictions based on climate change models

Júnior¹,

Júnior²,

Cecílio³

et al. 2008

Sci. agric. (Piracicaba, Braz.)

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Global climatic changes will potentially influence plant diseases and the efficacy of their management options. One of the most likely impacts of climate change will be felt by the geographical distribution of plant diseases. Black Sigatoka is considered the most damaging and costly disease of banana. The socio-economic impact of this disease has continued to increase as the pathogen reaches new areas and the disease becomes more difficult to be controled. The objectives of this research were to compare the global geographical distribution of the disease based on maps elaborated using weather data representing: i) current and future periods (2020, 2050 and 2080), ii) Intergovernmental Panel on Climate Change scenarios A2 and B2, iii) predictions based on six different climate change models and the "multimodel ensemble" and, iv) individual months. The "multimodel ensemble" lead to a reduction in the variability of the simulations when compared to the results obtained using the individual models separately. The predictions suggested that, in the future, areas favorable for the development of the Black Sigatoka disease will decrease. This reduction will occur gradually and will be higher for the A2 than for the B2 scenario. Changes in the geographical distribution of the disease will occur from one month to another, with unfavorable areas becoming favorable and vice-versa. However, in spite of these changes, extensive areas will still continue to be favorable for the occurrence of Black Sigatoka.

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Section: Resultssupporting

confidence: 90%

Section: Resultssupporting

confidence: 78%

Worldwide geographical distribution of Black Sigatoka for banana: predictions based on climate change models

Júnior¹,

Júnior²,

Cecílio³

et al. 2008

Sci. agric. (Piracicaba, Braz.)

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“…The climate change risk analysis for the Blacksigatoka of banana (caused by Mycosphaerella fijiensis) was studied by Ghini et al (2007), elaborating disease distribution maps assembled from scenarios and GCM data provided by the IPCC (2001). The maps revealed that there will be a reduction in the favorable area for the disease in Brazil.…”

Section: Geographical and Temporal Distribu-tionmentioning

confidence: 99%

Climate change and plant diseases

Ghini¹,

Hamada²,

Bettiol³

2008

Sci. agric. (Piracicaba, Braz.)

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126

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Human activities are altering greenhouse gas concentrations in the atmosphere and causing global climate change. In the near future, there will certainly be changes in the Brazilian phytosanitary scenario attributed to global climate change. The impacts of climate change can be positive, negative or neutral, since these changes can decrease, increase or have no impact on diseases, depending on each region or period. These impacts will also be observed on plants and other organisms as well as on other agroecosystem components. However, these impacts are not easily determined, and consequently, specialists from several areas must go beyond their disciplinary boundaries and placing the climate change impacts in a broader context. This review focuses on the discussion of different aspects related to the effects of climate change on plant diseases. On the geographical and temporal distribution of diseases, a historical context is presented and recent studies using data of forecast models of future climate associated with disease simulation models are discussed in order to predict the distribution in future climate scenarios. Predicted future disease scenarios for some crops in Brazil are shown. On the effects of increasing concentrations of atmospheric CO 2 and other gases, important aspects are discussed of how diseases change under altered atmospheric gases conditions in the future. The consequences of these changes on the chemical and biological control of plant diseases are also discussed. Key words: CO 2 , global climate change, global warming, spatial analysis, control MUDANÇAS CLIMÁTICAS E DOENÇAS DE PLANTASRESUMO: As atividades antrópicas estão alterando as concentrações de gases de efeito estufa da atmosfera e causando mudanças no clima do planeta. Certamente, num futuro próximo, devido às mudanças climáticas globais, ocorrerão modificações no cenário fitossanitário brasileiro. Os impactos podem ser positivos, negativos ou neutros, pois as mudanças podem diminuir, aumentar ou não ter efeito sobre as doenças, em cada região ou época. Esses impactos também serão observados sobre as plantas e outros organismos, além de outros componentes do agroecossistema. Porém, esses impactos não são facilmente determinados e, desta forma, os especialistas das diferentes áreas precisam ir além de suas disciplinas e abordar os impactos das mudanças climáticas em um contexto mais amplo. Nessa revisão são discutidos os aspectos relacionados com os efeitos das mudanças climáticas sobre as doenças de plantas. Na distribuição geográfica e temporal das doenças, um contexto histórico é apresentado, incluindo estudos recentes utilizando dados de modelos de previsão do clima futuro associados com modelos de simulação da doença a fim de predizer a distribuição nos cenários climáticos futuros. Também são apresentados os cenários futuros de previsão de doenças de algumas culturas no Brasil. Sobre os efeitos do aumento da concentração de CO 2 atmosférico e outros gases são discutidos importantes aspectos do comportamento das doe...

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“…Neste patossistema, os autores observaram que a região do espectro do visível foi a que melhor detectou a ocorrência do patógeno nos diferentes níveis de danos testados. A utilização de imagens de sensoriamento remoto permitiu espacializar o risco de ocorrência da doença em função do pixel, o que tornou possível realizar inferências em pequenas propriedades, diferentemente do trabalho desenvolvido por Ghini et al (2007), em que os autores fizeram uma projeção de cenários do comportamento da Sigatoka-negra em função das mudanças climáticas e considerando áreas continentais.…”

Section: Resultsunclassified

Análise de risco da ocorrência de Sigatoka-negra baseada em modelos polinomiais: um estudo de caso

Bendini

Moraes

Silva

et al. 2013

Trop. plant pathol.

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RESUMOA Sigatoka-negra (Mycosphaerella fijiensis) ameaça os bananais comerciais em todas as áreas produtoras do mundo e provoca danos quantitativos e qualitativos na produção, acarretando sérios prejuízos financeiros. Faz-se necessário o estudo da vulnerabilidade das plantas em diversos estádios de desenvolvimento e das condições climáticas favoráveis à ocorrência da doença. Objetivou-se com este trabalho desenvolver um modelo probabilístico baseado em funções polinomiais que represente o risco de ocorrência da Sigatokanegra em função da vulnerabilidade decorrente de fatores intrínsecos à planta e ao ambiente. Realizou-se um estudo de caso, em bananal comercial localizado em Jacupiranga, Vale do Ribeira, SP, considerando o monitoramento semanal do estado da evolução da doença, séries temporais de dados meteorológicos e dados de sensoriamento remoto. Foram gerados mapas georreferenciados do risco da Sigatoka-negra em diferentes épocas do ano. Um modelo para estimar a evolução da doença a partir de imagens de satélite foi obtido com coeficiente de determinação R 2 igual a 0,9. A metodologia foi desenvolvida para a detecção de épocas e locais que reúnem condições favoráveis à ocorrência da Sigatoka-negra e pode ser aplicada, com os devidos ajustes, em diferentes localidades, para avaliar o risco da ocorrência da doença em polos produtores de banana. Palavras-chave: Mychosphaerella fijiensis, modelagem, previsão. ABSTRACT Risk analysis of Black Sigatoka occurrence based on polynomial models: A case studyBlack Sigatoka (Mycosphaerella fijiensis) threatens the banana trade in most of world's producing areas, damaging the production and bringing significant financial loss. It is necessary to study the plant's susceptibility in the various developmental stages and climatic conditions that favor the disease occurrence. This paper presents a probabilistic model based on polynomial functions for estimating the risk of Black Sigatoka occurrence. A case study was developed in a commercial banana plantation located in Jacupiranga, Vale do Ribeira, SP, Brazil, considering the weekly monitoring of the disease's state evolution (EE), time series of meteorological data and remote sensing data. Georeferenced risk maps were prepared for different dates. We obtained a model to estimate the evolution of the disease from satellite imagery, with a coefficient of determination of 0.9. This methodology was developed for the detection of times and locations that have favorable conditions to the occurrence of Black Sigatoka and can be applied, with appropriate adjustments for different locations, to assess the risk of disease occurrence in other areas of banana production.

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Análise de risco das mudanças climáticas globais sobre a sigatoka-negra da bananeira no Brasil

Cited by 32 publications

References 12 publications

Worldwide geographical distribution of Black Sigatoka for banana: predictions based on climate change models

Worldwide geographical distribution of Black Sigatoka for banana: predictions based on climate change models

Climate change and plant diseases

Análise de risco da ocorrência de Sigatoka-negra baseada em modelos polinomiais: um estudo de caso

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