ABSTRACT
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 subhumid 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.
Subject(s)
Coffee , El Nino-Southern Oscillation , Brazil , Seasons , WeatherABSTRACT
Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.
Subject(s)
Climate Change , Crops, Agricultural/growth & development , Glycine max/growth & development , Models, Theoretical , Brazil , Carbon Dioxide/analysis , Computer Simulation , Crops, Agricultural/metabolism , Plant Transpiration , Rain , Glycine max/metabolism , Sunlight , TemperatureABSTRACT
The purpose of this study was to compare and evaluate the performance of electronic leaf wetness duration (LWD) sensors in measuring LWD in a cotton crop canopy when unpainted and painted sensors were used. LWD was measured with flat, printed-circuit wetness sensors, and the data were divided into two periods of 24 days: from 18 December 2001 to 10 January 2002, when the sensors were unpainted, and from 20 January to 13 February 2002, when the sensors were painted with white latex paint (two coats of paint). The data analysis included evaluating the coefficient of variation (CV%) among the six sensors for each day, and the relationship between the measured LWD (mean for the six sensors) and the number of hours with dew point depression under 2 degrees C, used as an indicator of dew presence. The results showed that the painting markedly reduced the CV% values. For the unpainted sensors the CV% was on average 67% against 9% for painted sensors. For the days without rainfall this reduction was greater. Comparing the sensor measurements to another estimator of LWD, in this case the number of hours with dew point depression under 2 degrees C, it was also observed that painting improved not only the precision of the sensors but also their sensitivity, because it increases the ability of the sensor to detect and measure the wetness promoted by small water droplets.
Subject(s)
Environmental Monitoring/instrumentation , Plant Leaves , Water/analysis , Gossypium , Humidity , Reproducibility of Results , Seasons , Sensitivity and SpecificityABSTRACT
Five bioclimatic indexes were evaluated to estimate the cycle duration of two sunflower cultivars and one hybrid, at Monte Alegre do Sul, State of São Paulo, Brazil. The following bioclimatic indexes were evaluated: thermic index (IT); heliothermic units (UH); accumulated photosyntetically active radiation (ARFA); Geslin heliothermic index (IHG), and accumulated potential evapotranspiration (AETP). The cultivars, IAC-Anhandy and VNIIMK, and the hybrid Contisol-621 were sown monthly, totalizing 22 different seasons, ranging from 01/14/88 to 01/19/90. Mean standart deviation and coefficient of variation (CV, %) were determined for each bioclimatic index, for all cultivars. The CVs showed that IT was the index that presented the lowest variation for all sowing seasons, with values of 4.5, 3.7, and 5.9%, respectivelly, for IAC-Anhandy, Contisol-621, and VNIIMK. The index IT was used to determine, by variance analysis and Tukey test, the differences between cultivars and the hybrid. The IAC-Anhandy (1743oC.day) and Contisol-621(1713oC.day), did not show significant differences. On the other hand, the VNIIMK was a later cultivar, requiring 1848oC.day to complete its cycle.
Foram avaliados cinco índices bioclimáticos para a estimativa da duração do ciclo de dois cultivares e de um híbrido de girassol, em Monte Alegre do Sul, SP. Os índices avaliados foram: índice térmico (IT); unidades heliotérmicas (UH); acúmulo da radiação fotossinteticamente ativa (ARFA); índice heliotérmico de Geslin (IHG); acúmulo da evapotranspiração potencial (AETP). Foram avaliados dois cultivares, IAC-Anhandy e VNIIMK, e o híbrido Contisol-621, os quais foram semeados mensalmente, totalizando 22 épocas distintas, variando de 14/01/88 a 19/01/90. Através do CV(%) foi possível verificar que o IT foi o índice que apresentou a menor variação ao longo das diferentes épocas de semeadura, com valores de CV de 4,5 e 5,9%, respectivamente, para os cultivares IAC-Anhandy e VNIIMK, e de 3,7% para o híbrido Contisol-621. Utilizando-se o índice térmico, determinou-se, através da análise de variância e teste de Tukey, a diferença entre os materiais avaliados. O cultivar IAC-Anhandy (1743oC.dia) e o híbrido Contisol-621 (1713oC.dia) não apresentaram diferença significativa entre si. Já o cultivar VNIIMK foi o mais tardio, apresentando maior índice térmico (1848 oC.dia).
ABSTRACT
Five bioclimatic indexes were evaluated to estimate the cycle duration of two sunflower cultivars and one hybrid, at Monte Alegre do Sul, State of São Paulo, Brazil. The following bioclimatic indexes were evaluated: thermic index (IT); heliothermic units (UH); accumulated photosyntetically active radiation (ARFA); Geslin heliothermic index (IHG), and accumulated potential evapotranspiration (AETP). The cultivars, IAC-Anhandy and VNIIMK, and the hybrid Contisol-621 were sown monthly, totalizing 22 different seasons, ranging from 01/14/88 to 01/19/90. Mean standart deviation and coefficient of variation (CV, %) were determined for each bioclimatic index, for all cultivars. The CVs showed that IT was the index that presented the lowest variation for all sowing seasons, with values of 4.5, 3.7, and 5.9%, respectivelly, for IAC-Anhandy, Contisol-621, and VNIIMK. The index IT was used to determine, by variance analysis and Tukey test, the differences between cultivars and the hybrid. The IAC-Anhandy (1743oC.day) and Contisol-621(1713oC.day), did not show significant differences. On the other hand, the VNIIMK was a later cultivar, requiring 1848oC.day to complete its cycle.
Foram avaliados cinco índices bioclimáticos para a estimativa da duração do ciclo de dois cultivares e de um híbrido de girassol, em Monte Alegre do Sul, SP. Os índices avaliados foram: índice térmico (IT); unidades heliotérmicas (UH); acúmulo da radiação fotossinteticamente ativa (ARFA); índice heliotérmico de Geslin (IHG); acúmulo da evapotranspiração potencial (AETP). Foram avaliados dois cultivares, IAC-Anhandy e VNIIMK, e o híbrido Contisol-621, os quais foram semeados mensalmente, totalizando 22 épocas distintas, variando de 14/01/88 a 19/01/90. Através do CV(%) foi possível verificar que o IT foi o índice que apresentou a menor variação ao longo das diferentes épocas de semeadura, com valores de CV de 4,5 e 5,9%, respectivamente, para os cultivares IAC-Anhandy e VNIIMK, e de 3,7% para o híbrido Contisol-621. Utilizando-se o índice térmico, determinou-se, através da análise de variância e teste de Tukey, a diferença entre os materiais avaliados. O cultivar IAC-Anhandy (1743oC.dia) e o híbrido Contisol-621 (1713oC.dia) não apresentaram diferença significativa entre si. Já o cultivar VNIIMK foi o mais tardio, apresentando maior índice térmico (1848 oC.dia).
ABSTRACT
Two regression equations were developed to estimate lowland rice yield as a function of air temperature and incoming solar radiation, during the crop yield production period in Pindamonhangaba, SP, Brazil. The following rice cultivars were used: IAC-242, IAC-100, IAC-101 and IAC-102. The value of optimum air temperature obtained was 25.0°C and of optimum global solar radiation was 475 cal.cm-2, day-1. The best agrometeorological model was the one that related least deviation of air temperature and solar radiation in relation to the optimum value obtained through a multiple linear regression. The yield values estimated by the model showed good fit to actual yields of lowland rice (less than 10%).
Foram desenvolvidas duas equações de estimativa da produtividade do arroz irrigado por inundação, para as variedades: IAC-242, IAC-100, IAC-101 e IAC-102, em função da temperatura do ar e da radiação solar, no período crítico de formação da produção, para a região de Pindamonhangaba (SP). Os valores de temperatura do ar e de radiação solar ótimos encontrados para as variedades foram, respectivamente, 25,0oC e 475 cal.cm-2.dia-1. O modelo agrometeorológico desenvolvido para previsão da produtividade da cultura que apresentou melhores resultados quando testado com dados independentes foi o que relacionou o menor desvio dos dois elementos climáticos em relação ao valor ótimo obtido através de uma equação de regressão linear múltipla. Os valores de produtividade estimados pelo modelo mostraram diferenças menores que 10% quando comparados com os valores obtidos no campo.
ABSTRACT
This paper describes the rainfall pattern during the day along the different months of the year, calculated on an hourly basis for three sites: Campinas, Pindorama and Ubatuba, SP, Brazil, utilizing data series from 1957 to 1976. Results indicate that there is significative difference in the total of the hourly rainfall in the months of November to March in Campinas; October to April in Pindorama, and October to June in Ubatuba. Results of the hourly frequencies of rainfall are similar to those of total rainfall for Campinas and Pindorama. For Ubatuba, the hourly frequence of rainfall shows significant differences for all months of the year. During the mouths that show significant differences, the morning period is the most appropriate to realize agricultural practices, in which rainfall probability is reduced. During the months that do not show significant differences, the probability of rainfall occurrence is very reduced, less than 10%, in average, in all hours of the day, being possible to program agricultural practices during the whole period.
Para caracterizar o comportamento das chuvas no decorrer do dia nos diferentes meses do ano, foram calculadas as médias dos totais e das freqüências das chuvas horárias para três locais: Campinas, Pindorama e Ubatuba, no período de 1957 a 1976. Os resultados obtidos mostram que existe diferença significativa no total de chuva horária nos meses de: novembro a março em Campinas; outubro a abril em Pindorama, e outubro a junho em Ubatuba. A freqüência horária das chuvas apresentou resultados semelhantes aos do total de chuva para Campinas e Pindorama. Em Ubatuba, a freqüência horária das chuvas apresentou diferença significativa durante todos os meses do ano. Durante os meses que apresentam diferenças significativas, o período da manhã mostra ser o mais conveniente para a realização das atividades agrícolas, onde são reduzidas as probabilidades de chover. Durante os meses que não apresentaram diferença significativa, a probabilidade de ocorrência de chuvas é pequena, inferior a 10%, em todos os horários do dia, sendo possível programar operações de campo durante todo o período.
ABSTRACT
This paper describes the rainfall pattern during the day along the different months of the year, calculated on an hourly basis for three sites: Campinas, Pindorama and Ubatuba, SP, Brazil, utilizing data series from 1957 to 1976. Results indicate that there is significative difference in the total of the hourly rainfall in the months of November to March in Campinas; October to April in Pindorama, and October to June in Ubatuba. Results of the hourly frequencies of rainfall are similar to those of total rainfall for Campinas and Pindorama. For Ubatuba, the hourly frequence of rainfall shows significant differences for all months of the year. During the mouths that show significant differences, the morning period is the most appropriate to realize agricultural practices, in which rainfall probability is reduced. During the months that do not show significant differences, the probability of rainfall occurrence is very reduced, less than 10%, in average, in all hours of the day, being possible to program agricultural practices during the whole period.
Para caracterizar o comportamento das chuvas no decorrer do dia nos diferentes meses do ano, foram calculadas as médias dos totais e das freqüências das chuvas horárias para três locais: Campinas, Pindorama e Ubatuba, no período de 1957 a 1976. Os resultados obtidos mostram que existe diferença significativa no total de chuva horária nos meses de: novembro a março em Campinas; outubro a abril em Pindorama, e outubro a junho em Ubatuba. A freqüência horária das chuvas apresentou resultados semelhantes aos do total de chuva para Campinas e Pindorama. Em Ubatuba, a freqüência horária das chuvas apresentou diferença significativa durante todos os meses do ano. Durante os meses que apresentam diferenças significativas, o período da manhã mostra ser o mais conveniente para a realização das atividades agrícolas, onde são reduzidas as probabilidades de chover. Durante os meses que não apresentaram diferença significativa, a probabilidade de ocorrência de chuvas é pequena, inferior a 10%, em todos os horários do dia, sendo possível programar operações de campo durante todo o período.
ABSTRACT
Two regression equations were developed to estimate lowland rice yield as a function of air temperature and incoming solar radiation, during the crop yield production period in Pindamonhangaba, SP, Brazil. The following rice cultivars were used: IAC-242, IAC-100, IAC-101 and IAC-102. The value of optimum air temperature obtained was 25.0°C and of optimum global solar radiation was 475 cal.cm-2, day-1. The best agrometeorological model was the one that related least deviation of air temperature and solar radiation in relation to the optimum value obtained through a multiple linear regression. The yield values estimated by the model showed good fit to actual yields of lowland rice (less than 10%).
Foram desenvolvidas duas equações de estimativa da produtividade do arroz irrigado por inundação, para as variedades: IAC-242, IAC-100, IAC-101 e IAC-102, em função da temperatura do ar e da radiação solar, no período crítico de formação da produção, para a região de Pindamonhangaba (SP). Os valores de temperatura do ar e de radiação solar ótimos encontrados para as variedades foram, respectivamente, 25,0oC e 475 cal.cm-2.dia-1. O modelo agrometeorológico desenvolvido para previsão da produtividade da cultura que apresentou melhores resultados quando testado com dados independentes foi o que relacionou o menor desvio dos dois elementos climáticos em relação ao valor ótimo obtido através de uma equação de regressão linear múltipla. Os valores de produtividade estimados pelo modelo mostraram diferenças menores que 10% quando comparados com os valores obtidos no campo.