Aplicação da análise harmônica por séries de Fourier para a previsão de produtividade da cultura do café no Estado de Minas Gerais

Carvalho, Luiz Gonsaga de; Sediyama, Gilberto Chohaku; Cecon, Paulo R.; Alves, Helena Maria Ramos

doi:10.1590/s0100-69162005000300019

Cited by 8 publications

(7 citation statements)

References 2 publications

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“…Dessa forma, é acrescido 10% ao valor da maior produtividade da soja obtida na série, com o objetivo de eliminar qualquer efeito do ambiente que pudesse interferir sobre o potencial de produtividade (MORAES et al, 1998;CARVALHO et al, 2005).…”

Section: Methodsunclassified

Modelagem Agrometeorológica Para Estimativa De Produtividade De Soja Para O Vale Do Médio Paranapanema-Sp

Silva-Fuzzo

Prela-Pantano

Camargo

2015

R_I

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RESUMOModelos agrometeorológicos de estimativa de safra utilizam dados climatológicos coletados em estações convencionais de superfície. A precipitação é o elemento meteorológico que apresenta maior variabilidade espacial, e desta forma com o intuito de obter uma maior cobertura e disponibilidade de dados de precipitação pluvial vem sendo utilizados dados estimados por satélite. Com isso melhora a qualidade das estimativas de produtividade da cultura da soja no Estado de São Paulo. O objetivo foi estimar a produtividade da cultura da soja, para a região do Vale do Médio Paranapanema-SP, utilizando dados de temperatura e precipitação de estações meteorológicas convencionais e dados de precipitação estimados pelo satélite TRMM para o período de 1998 a 2008, por meio de modelagem agrometeorológico. O modelo de estimativa de produtividade utilizado levou em consideração tanto deficiência hídrica como o excedente hídrico e apresentou desempenho satisfatório e melhoria significativa com a inserção dos dados do satélite TRMM, com valores de índice de concordância 'd' variando de 0,80 a 0,90. Palavras-chave:Precipitação pluvial, variabilidade climática, TRMM. SILVA-FUZZO,D.F.; PRELA-PANTANO, A.; CAMARGO,M.B.P. AGROMETEOROLOGICAL MODELING TO ESTIMATE SOYBEAN YIELD IN THE VALLEY OF THE MIDDLE PARANAPANEMA-SP ABSTRACTAgrometeorological models to estimate harvest use climatological data collected in conventional surface stations. Precipitation is the weather parameter which presents the highest spatial variability. Therefore, in order to achieve greater coverage and rainfall data availability, data estimated by satellite have been used, and consequently, better estimates of soybean crop yield have been found in São Paulo state. The objective of this study was to estimate crop yield of soybean in the Valley of the Middle Paranapanema-SP, using data of temperature and precipitation from conventional meteorological stations and precipitation data estimated by the TRMM satellite in the period from 1998 to 2008 using agrometeorological modeling. The estimation model of productivity considered both water stress and water surplus, and using data of the TRMM satellite caused a significant improvement with values of concordance index 'd' of Willmott ranging from 0.80 to 0.90.

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Section: Methodsunclassified

Modelagem Agrometeorológica Para Estimativa De Produtividade De Soja Para O Vale Do Médio Paranapanema-Sp

Silva-Fuzzo

Prela-Pantano

Camargo

2015

R_I

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“…Since the temporal variation is a periodical phenomenon, it can be represented by the Fourier's trigonometric series (CARVALHO et al, 2005) and, according to QUEIROZ et al (2001), it is possible to be adjusted by using only the first three harmonics of this series. GD modeling was conducted with the daily scale as follows:…”

Section: Methodsmentioning

confidence: 99%

“…However, data are not always available from all sites for bioclimatic characterization of a region. This scarcity of information may be overcome by estimating GD by means of mathematical models based on historical series of climate data, similarly to what has been done to estimate air temperature (CARVALHO et al, 2005;STAHL et al, 2006;CARGNELUTTI FILHO et al 2006) as a function of geographical coordinates and a certain time period. BURIOL & ESTEFANEL (1976) estimated the sum of monthly and annual GD at the state of Rio Grande do Sul as a function of the altitude, latitude, longitude, using T b of 0 ºC, 5 °C, 10 ºC, 15 ºC and 20 ºC, and obtained coefficients of determination ranging between 0.92 and 0.97, depending on the month and the T b applied.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal modelling of the duration of the cotton cycle in the State Of Goiás, Brazil

et al. 2011

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The objective of this work was to develop and validate a mathematical model to estimate the duration of cotton (Gossypium hirsutum L. r. latifolium hutch) cycle in the State of Goiás, Brazil, by applying the method of growing degree-days (GD), and considering, simultaneously, its time-space variation. The model was developed as a linear combination of elevation, latitude, longitude, and Fourier series of time variation. The model parameters were adjusted by using multiple-linear regression to the observed GD accumulated with air temperature in the range of 15°C to 40°C. The minimum and maximum temperature records used to calculate the GD were obtained from 21 meteorological stations, considering data varying from 8 to 20 years of observation. The coefficient of determination, resulting from the comparison between the estimated and calculated GD along the year was 0.84. Model validation was done by comparing estimated and measured crop cycle in the period from cotton germination to the stage when 90 percent of bolls were opened in commercial crop fields. Comparative results showed that the model performed very well, as indicated by the Pearson correlation coefficient of 0.90 and Willmott agreement index of 0.94, resulting in a performance index of 0.85.

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“…The third estimation model developed for the same purpose was described by Carvalho et al (2005) and uses the harmonic analysis based on Fourier series. This model involves 33 variables; however, results obtained by using this model were not satisfactory due to the high level of complexity found in coffee production forecast.…”

Section: Introductionmentioning

confidence: 99%

Validation of a phenological model for coffee tree productivity in Southern State of Minas Gerais, Brazil

Miranda¹,

Carvalho²,

Fahl³

et al. 2017

Afr. J. Agric. Res.

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There are studies on the current state of understanding productivity models, focusing on the applicability of different estimation models for coffee tree productivity; the majority involving a considerable level of complexity. Thus, when searching for a simple and direct association between phenological characteristics and coffee productivity, doing research on this hypothesis is necessary. In this study, we aimed to validate a phenological model for coffee tree productivity by using phenological indices, under given edaphoclimatic conditions of Southern State of Minas Gerais, Brazil. We used 10 sample plots obtained from the municipalities of Lavras, Varginha, Carmo de Minas, Ijaci and Santo Antônio do Amparo. Plots were chosen based on the existing history about coffee productivity, which is over 40 sacks ha -1 . Phenological data were collected in September-October, December-January and March to April of the harvesting seasons 2012/2013 and 2013/2014. The number of flowers and fruits were obtained at the fourth and fifth productive nodes of coffee plagiotropic branches sampled at the middle third of each coffee plant. Forty plants were sampled in each plot for the measurement of plant height and estimates of productivity phenological indices. Data regarding the observed production were obtained for models comparison and validation and, then, statistical tests were run. Results showed that these models are suitable for the coffee crop in the region under study. In addition, productivity phenological indices showed good correlation with the observed productivity.

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Aplicação da análise harmônica por séries de Fourier para a previsão de produtividade da cultura do café no Estado de Minas Gerais

Cited by 8 publications

References 2 publications

Modelagem Agrometeorológica Para Estimativa De Produtividade De Soja Para O Vale Do Médio Paranapanema-Sp

Modelagem Agrometeorológica Para Estimativa De Produtividade De Soja Para O Vale Do Médio Paranapanema-Sp

Spatio-temporal modelling of the duration of the cotton cycle in the State Of Goiás, Brazil

Validation of a phenological model for coffee tree productivity in Southern State of Minas Gerais, Brazil

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