Assessing Biogeography of Coffee Rust Risk in Brazil as Affected by the El Niño Southern Oscillation

The El Niño Southern Oscillation (ENSO) is an oceanic-atmospheric phenomenon influencing worldwide weather and climate. Its occurrence is determined by the sea surface temperature (SST) anomaly of the 3.4 Niño region in the Pacific Ocean (5°N-5°S, 120°-170°W). El Niño (EN), Neutral (NT), and La Niña (LN) are the three possible phases of ENSO, respectively for warm, normal, and cold SST anomaly. As in other regions around the world, weather in Brazil is influenced by ENSO phases. The country is the major coffee producer in the world and production is strongly influenced by weather conditions, which affect plant yield, harvest quality, and interactions with pests and diseases. Coffee leaf rust (CLR), caused by the fungus Hemileia vastatrix, is a major cause of coffee yield and quality losses in Brazil, and requires fungicide spray applications every season. Because CLR is highly influenced by weather conditions, it is possible to use weather variables to simulate its progress during the cropping cycle. Therefore, the aims of this study were to estimate CLR infection rate based on a validated empirical model, which has daily minimum air temperature and relative humidity as inputs, and to assess the extent of ENSO influence on the annual risk of this disease at 45 sites in Brazil. Cumulative infection rates (CIR) were estimated daily from October to June of each growing season and location, based on the prevailing ENSO phase. Differences between the extreme phases (EN-LN), were assessed by the Two-One-Sided-Tests (TOST) method. Analysis of data from eight sites, located mainly in Paraná state, provided evidence of CIR differences between EN and LN phases (G1). Evidence of no difference of CIR between EN and LN was found in 18 sites (G2), whereas 19 sites showed no evidence of differences (G3), due to relatively large variation of CIR within the same ENSO phase. The G1 sites are located mostly in Southern Brazil, where ENSO exerts a well-defined influence on rainfall regime. In contrast, the G2 sites are mainly in Minas Gerais state, which is characterized as a transition region for ENSO influence on rainfall. The G3 sites are located between the northern region of Minas Gerais state and southern region of Bahia state, which is characterized by a sub-humid climate that is usually very dry during winter, and where rainfall can vary up to 300% from one year to another, influencing relative humidity and resulting in a high CIR variability. Therefore, ENSO had a well-defined influence on CIR only in Paraná state, a region with minor importance for coffee production in Brazil. No ENSO influence was found in more northerly zones where the majority of Brazilian coffee is produced. This is the first evidence of ENSO-linked regional impact on the risk of coffee rust

Water excess in different soils and sowing times for sunflower in the state of Rio Grande do Sul, Brazil

O objetivo deste trabalho foi identificar datas de semeadura com menor ocorrência média de dias com excedente hídrico para a cultura do girassol, e determinar a persistência de dias consecutivos com excedente hídrico ao se considerar a capacidade de armazenamento de água disponível de diferentes solos da região central do Rio Grande do Sul. O desenvolvimento da cultura e o aprofundamento do sistema radicular foram simulados de acordo com a soma térmica para 14 datas de semeadura, de agosto até meados de fevereiro, com dados de 1968 até 2011. A partir da capacidade de armazenamento de água disponível para as diferentes classes de solos da região, calculou-se o balanço hídrico sequencial diário para determinar os dias com excesso hídrico. Avaliou-se a ocorrência de dias com excesso hídrico em diferentes subperíodos de desenvolvimento da cultura, e procedeu-se à análise exploratória com gráficos box‑plot para determinação da persistência de dias consecutivos com excesso hídrico durante todo o ciclo da cultura. O excedente hídrico limita o cultivo de girassol em determinadas áreas e períodos na região central do Rio Grande do Sul. A persistência de dias consecutivos com excedente hídrico e a duração do ciclo de desenvolvimento da cultura são  influenciados pela data de semeadura.The objective of this work was to identify sowing dates with the lowest average occurrence of days with water excess for sunflower crop, and to determine the persistence of consecutive days with water excess considering the available water storage capacity of different soils of the central region of the state of Rio Grande do Sul, Brazil. Crop development and root system deepening were simulated based on thermal summation for 14 sowing dates, from August until mid‑February, with data from 1968 to 2011. From the available water storage capacity of the different soil classes of the region, the sequential daily water balance was calculated to determine the days with water excess. The occurrence of days with water excess was evaluated in different crop development sub‑periods, and exploratory analysis with box‑plot graphs was performed to determine the persistence of consecutive days with water excess during the crop cycle. Water excess limits sunflower cultivation in some areas and periods in the central region of the state of Rio Grande do Sul. The persistence of consecutive days with water excess and the duration of the crop development cycle are influenced by the sowing date

Desenvolvimento e aplicação de sistemas de alerta fitossanitário para o manejo da ferrugem do cafeeiro

Coffee crop is of major importance to Brazil, being cultivated on more than 2 million hectares. It is a strategic commodity for the country, which is the main world producer. Several factors influence the yields, mainly a disease known as coffee leaf rust (CLR), caused by the fungus Hemileia vastatarix. This disease can reduce yield up to 35% and the most common strategy for CLR controlling is by spraying fungicides, with interval based on the residual period and according to regional CLR intensity. This traditional way does not consider the climate influence on disease development. With the aim of developing a forecast system (FS) for CLR management, employing weather data from CLR field assessments since 1998, several steps were performed: a) CLR epidemiology analysis; b) correlation between disease progress rates and weather variables; c) development of a forecast system, in order to rationalize chemical control; d) assessment of the FS performance on field trials; e) generation of an agro-climatic index for CLR risk assessment in Brazilian coffee areas; and f) evaluation of possible El Niño Southern Oscillation (ENSO) influence on CLR epidemics. Analising 88 siteseason CLR epidemics, from Varginha, Boa Esperança and Carmo de Minas, MG, the best fit was obtained by Gompertz model. Using stepwise method, CLR infection rates were estimated with multiple linear regressions, using minimum temperature and relative humidity as inputs. The model performed well, presenting less than 9.5% of false negatives in the months assessed. To evaluate CLR forecast system, two field trials were performed during 2015-16 season (Varginha and Boa Esperança), and five during 2016-17 season (Varginha, Boa Esperança, Uberlândia, Buritizal, and Campinas). The FS treatments performed better than the calendar spray system in six trials, with the exception for Campinas. The poor FS performance in Campinas evidenced the necessity of FS threshold calibration at sites different from the region where the FS was developed, once it is empirical. In order to assess the risk, the estimated CLR infection rate was evaluated for 46 different sites in Brazilian coffee producing region. Historical weather data since 1961 to 2015 for each site was used to estimate daily values of cumulative infection rate (CIR). Each site and season were classified into five CIR scores from Very Low (score 0) to Very High (score 4). The risk was spatialized using multiple linear regression based on geographical coordinates and altitude. The Brazilian coffee region was classified into four risk classes, being most of them between Medium to High risks in the area currently cultivated with coffee. For the same historical serie, CIR was estimated for 45 locations and then classified by ENSO phases: El Niño (EN); Neutral (NT); and La Niña (LN). A predominant absence of ENSO effect on CLR in Brazil was observed. Only in Paraná and São Paulo states there was ENSO effect, with higher CIR during EN seasons.O cultivo do cafeeiro é de grande importância para o Brasil, sendo cultivado em mais de 2 milhões de hectares. Diversas doenças influenciam a produtividade, sendo a ferrugem do cafeeiro (CLR), a principal. Ocasionada pelo fungo Hemileia vastatrix, a CLR é capaz de reduzir a produtividade em até 35%. A estratégia mais comum de controle dessa doença é a aplicação de fungicidas foliares, baseado no período residual e de acordo com a intensidade da doença na região. Este método tradicional não considera a influência do clima no desenvolvimento da doença. Com o objetivo de desenvolver um sistema de previsão (FS) para o manejo da CLR utilizando dados de experimentos de campo obtidos desde 1998, diversas etapas foram realizadas: a) análise epidemiológica; b) relação da taxa de progresso da doença com variáveis ambientais; c) desenvolvimento do FS, visando racionalizar o controle químico; d) avaliação do desempenho do FS, em experimentos de campo; e) geração de índices agroclimáticos de favorabilidade para a ocorrência da CLR nas áreas produtoras de café do Brasil; e f) avaliar efeitos do fenômeno El Niño Oscilação Sul (ENOS) nas epidemias de CLR. Foram analisadas 88 epidemias de CLR, em Varginha, Boa Esperança e Carmo de Minas, MG, sendo o modelo de Gompertz o que resultou em melhor ajuste à curva de progresso da doença. Usando metodologia stepwise, as taxas de progresso mensais da doença foram estimadas com regressões lineares múltiplas, baseada em dados de temperatura mínima e umidade relativa do ar. O melhor modelo de estimativa resultou em menos de 9.5% de ocorrências de falso negativos, durante os meses avaliados. Para avaliar o desempenho do FS, dois experimentos foram realizados na safra 2015-16 (Varginha e Boa Esperança, MG) e cinco na safra 2016-17 (Varginha, Boa Esperança, Uberlândia, Buritizal e Campinas). Os tratamentos baseados no FS resultaram em melhor desempenho que o sistema tradicional em seis experimentos, à exceção de Campinas. Este desempenho inferior evidenciou a necessidade de calibração de limiares em diferentes locais, diferentes da região onde o FS foi desenvolvido, devido a sua base empírica. Para avaliar o risco da doença, a taxa de progresso diária foi estimada em 46 locais da região produtora de café, durante as estações de cultivo disponíveis, em uma base de dados históricos de 1961 a 2015, gerando as taxas de progresso acumuladas (CIR). Para cada local e estação, cinco classes com pontuação de Muito Baixo (0) a Muito Alto (4) foram atribuídas, gerando valores de risco. Utilizando regressão linear múltipla, o risco para a CLR foi espacializado em função dos valores de coordenadas geográficas e altitude. Os riscos Médio e Alto foram os mais comuns onde atualmente se cultiva café. No mesmo período de dados meteorológicos, a CIR de 45 locais foi estimada, sendo as estações classificadas em função das possíveis fases de ENOS: El Niño (EN), Neutro (NT) e La Niña (LN). Houve predominio da ausência de efeito do ENOS na CLR no Brasil. Apenas nos estados do PR e SP o EN induziu a uma maior CIR

Desenvolvimento e aplicação de sistemas de alerta fitossanitário para o manejo da ferrugem do cafeeiro

Coffee crop is of major importance to Brazil, being cultivated on more than 2 million hectares. It is a strategic commodity for the country, which is the main world producer. Several factors influence the yields, mainly a disease known as coffee leaf rust (CLR), caused by the fungus Hemileia vastatarix. This disease can reduce yield up to 35% and the most common strategy for CLR controlling is by spraying fungicides, with interval based on the residual period and according to regional CLR intensity. This traditional way does not consider the climate influence on disease development. With the aim of developing a forecast system (FS) for CLR management, employing weather data from CLR field assessments since 1998, several steps were performed: a) CLR epidemiology analysis; b) correlation between disease progress rates and weather variables; c) development of a forecast system, in order to rationalize chemical control; d) assessment of the FS performance on field trials; e) generation of an agro-climatic index for CLR risk assessment in Brazilian coffee areas; and f) evaluation of possible El Niño Southern Oscillation (ENSO) influence on CLR epidemics. Analising 88 siteseason CLR epidemics, from Varginha, Boa Esperança and Carmo de Minas, MG, the best fit was obtained by Gompertz model. Using stepwise method, CLR infection rates were estimated with multiple linear regressions, using minimum temperature and relative humidity as inputs. The model performed well, presenting less than 9.5% of false negatives in the months assessed. To evaluate CLR forecast system, two field trials were performed during 2015-16 season (Varginha and Boa Esperança), and five during 2016-17 season (Varginha, Boa Esperança, Uberlândia, Buritizal, and Campinas). The FS treatments performed better than the calendar spray system in six trials, with the exception for Campinas. The poor FS performance in Campinas evidenced the necessity of FS threshold calibration at sites different from the region where the FS was developed, once it is empirical. In order to assess the risk, the estimated CLR infection rate was evaluated for 46 different sites in Brazilian coffee producing region. Historical weather data since 1961 to 2015 for each site was used to estimate daily values of cumulative infection rate (CIR). Each site and season were classified into five CIR scores from Very Low (score 0) to Very High (score 4). The risk was spatialized using multiple linear regression based on geographical coordinates and altitude. The Brazilian coffee region was classified into four risk classes, being most of them between Medium to High risks in the area currently cultivated with coffee. For the same historical serie, CIR was estimated for 45 locations and then classified by ENSO phases: El Niño (EN); Neutral (NT); and La Niña (LN). A predominant absence of ENSO effect on CLR in Brazil was observed. Only in Paraná and São Paulo states there was ENSO effect, with higher CIR during EN seasons.O cultivo do cafeeiro é de grande importância para o Brasil, sendo cultivado em mais de 2 milhões de hectares. Diversas doenças influenciam a produtividade, sendo a ferrugem do cafeeiro (CLR), a principal. Ocasionada pelo fungo Hemileia vastatrix, a CLR é capaz de reduzir a produtividade em até 35%. A estratégia mais comum de controle dessa doença é a aplicação de fungicidas foliares, baseado no período residual e de acordo com a intensidade da doença na região. Este método tradicional não considera a influência do clima no desenvolvimento da doença. Com o objetivo de desenvolver um sistema de previsão (FS) para o manejo da CLR utilizando dados de experimentos de campo obtidos desde 1998, diversas etapas foram realizadas: a) análise epidemiológica; b) relação da taxa de progresso da doença com variáveis ambientais; c) desenvolvimento do FS, visando racionalizar o controle químico; d) avaliação do desempenho do FS, em experimentos de campo; e) geração de índices agroclimáticos de favorabilidade para a ocorrência da CLR nas áreas produtoras de café do Brasil; e f) avaliar efeitos do fenômeno El Niño Oscilação Sul (ENOS) nas epidemias de CLR. Foram analisadas 88 epidemias de CLR, em Varginha, Boa Esperança e Carmo de Minas, MG, sendo o modelo de Gompertz o que resultou em melhor ajuste à curva de progresso da doença. Usando metodologia stepwise, as taxas de progresso mensais da doença foram estimadas com regressões lineares múltiplas, baseada em dados de temperatura mínima e umidade relativa do ar. O melhor modelo de estimativa resultou em menos de 9.5% de ocorrências de falso negativos, durante os meses avaliados. Para avaliar o desempenho do FS, dois experimentos foram realizados na safra 2015-16 (Varginha e Boa Esperança, MG) e cinco na safra 2016-17 (Varginha, Boa Esperança, Uberlândia, Buritizal e Campinas). Os tratamentos baseados no FS resultaram em melhor desempenho que o sistema tradicional em seis experimentos, à exceção de Campinas. Este desempenho inferior evidenciou a necessidade de calibração de limiares em diferentes locais, diferentes da região onde o FS foi desenvolvido, devido a sua base empírica. Para avaliar o risco da doença, a taxa de progresso diária foi estimada em 46 locais da região produtora de café, durante as estações de cultivo disponíveis, em uma base de dados históricos de 1961 a 2015, gerando as taxas de progresso acumuladas (CIR). Para cada local e estação, cinco classes com pontuação de Muito Baixo (0) a Muito Alto (4) foram atribuídas, gerando valores de risco. Utilizando regressão linear múltipla, o risco para a CLR foi espacializado em função dos valores de coordenadas geográficas e altitude. Os riscos Médio e Alto foram os mais comuns onde atualmente se cultiva café. No mesmo período de dados meteorológicos, a CIR de 45 locais foi estimada, sendo as estações classificadas em função das possíveis fases de ENOS: El Niño (EN), Neutro (NT) e La Niña (LN). Houve predominio da ausência de efeito do ENOS na CLR no Brasil. Apenas nos estados do PR e SP o EN induziu a uma maior CIR

Assessing Biogeography of Coffee Rust Risk in Brazil as Affected by the El Niño Southern Oscillation

The El Niño Southern Oscillation (ENSO) is an oceanic-atmospheric phenomenon influencing worldwide weather and climate. Its occurrence is determined by the sea surface temperature (SST) anomaly of the 3.4 Niño region in the Pacific Ocean (5°N-5°S, 120°-170°W). El Niño (EN), Neutral (NT), and La Niña (LN) are the three possible phases of ENSO, respectively for warm, normal, and cold SST anomaly. As in other regions around the world, weather in Brazil is influenced by ENSO phases. The country is the major coffee producer in the world and production is strongly influenced by weather conditions, which affect plant yield, harvest quality, and interactions with pests and diseases. Coffee leaf rust (CLR), caused by the fungus Hemileia vastatrix, is a major cause of coffee yield and quality losses in Brazil, and requires fungicide spray applications every season. Because CLR is highly influenced by weather conditions, it is possible to use weather variables to simulate its progress during the cropping cycle. Therefore, the aims of this study were to estimate CLR infection rate based on a validated empirical model, which has daily minimum air temperature and relative humidity as inputs, and to assess the extent of ENSO influence on the annual risk of this disease at 45 sites in Brazil. Cumulative infection rates (CIR) were estimated daily from October to June of each growing season and location, based on the prevailing ENSO phase. Differences between the extreme phases (EN-LN), were assessed by the Two-One-Sided-Tests (TOST) method. Analysis of data from eight sites, located mainly in Paraná state, provided evidence of CIR differences between EN and LN phases (G1). Evidence of no difference of CIR between EN and LN was found in 18 sites (G2), whereas 19 sites showed no evidence of differences (G3), due to relatively large variation of CIR within the same ENSO phase. The G1 sites are located mostly in Southern Brazil, where ENSO exerts a well-defined influence on rainfall regime. In contrast, the G2 sites are mainly in Minas Gerais state, which is characterized as a transition region for ENSO influence on rainfall. The G3 sites are located between the northern region of Minas Gerais state and southern region of Bahia state, which is characterized by a sub-humid climate that is usually very dry during winter, and where rainfall can vary up to 300% from one year to another, influencing relative humidity and resulting in a high CIR variability. Therefore, ENSO had a well-defined influence on CIR only in Paraná state, a region with minor importance for coffee production in Brazil. No ENSO influence was found in more northerly zones where the majority of Brazilian coffee is produced. This is the first evidence of ENSO-linked regional impact on the risk of coffee rust.This is a manuscript of an article published as Hinnah, Fernando Dill, Paulo C. Sentelhas, Mark L. Gleason, Philip Dixon, and Xiaoyu Zhang. "Assessing Biogeography of Coffee Rust Risk in Brazil as Affected by the El Niño Southern Oscillation." Plant Disease (2019). doi: 10.1094/PDIS-01-19-0207-SR. Posted with permission.</p

Estimation of leaf area index in the sunflower as a function of thermal time1

The aim of this study was to obtain a mathematical model for estimating the leaf area index (LAI) of a sunflower crop as a function of accumulated thermal time. Generating the models and testing their coefficients was carried out using data obtained from experiments carried out for different sowing dates in the crop years of 2007/08, 2008/09, 2009/10 and 2010/11 with two sunflower hybrids, Aguará 03 and Hélio 358. Linear leaf dimensions were used for the non-destructive measurement of the leaf area, and thermal time was used to quantify the biological time. With the data for accumulated thermal time (TTa) and LAI known for any one day after emergence, mathematical models were generated for estimating the LAI. The following models were obtained, as they presented the best fit (lowest rootmean- square error, RMSE): gaussian peak, cubic polynomial, sigmoidal and an adjusted compound model, the modified sigmoidal. The modified sigmoidal model had the best fit to the generation data and the highest value for the coefficient of determination (R2). In testing the models, the lowest values for root-mean-square error, and the highest R2 between the observed and estimated values were obtained with the modified sigmoidal model

Excedente hídrico em diferentes solos e épocas de semeadura do girassol no Rio Grande do Sul

O objetivo deste trabalho foi identificar datas de semeadura com menor ocorrência média de dias com excedente hídrico para a cultura do girassol, e determinar a persistência de dias consecutivos com excedente hídrico ao se considerar a capacidade de armazenamento de água disponível de diferentes solos da região central do Rio Grande do Sul. O desenvolvimento da cultura e o aprofundamento do sistema radicular foram simulados de acordo com a soma térmica para 14 datas de semeadura, de agosto até meados de fevereiro, com dados de 1968 até 2011. A partir da capacidade de armazenamento de água disponível para as diferentes classes de solos da região, calculou-se o balanço hídrico sequencial diário para determinar os dias com excesso hídrico. Avaliou-se a ocorrência de dias com excesso hídrico em diferentes subperíodos de desenvolvimento da cultura, e procedeu-se à análise exploratória com gráficos box-plot para determinação da persistência de dias consecutivos com excesso hídrico durante todo o ciclo da cultura. O excedente hídrico limita o cultivo de girassol em determinadas áreas e períodos na região central do Rio Grande do Sul. A persistência de dias consecutivos com excedente hídrico e a duração do ciclo de desenvolvimento da cultura são influenciados pela data de semeadura