@TechReport{ChenFons:1979:CoYiMo,
               author = "Chen, Sherry Chou and Fonseca, Lourdes Bernadete da",
                title = "Corn yield model for Ribeir{\~a}o Preto, S{\~a}o Paulo State, 
                         Brazil",
          institution = "INPE",
                 year = "1979",
                 type = "RPQ",
               number = "INPE-1488-RPE/034",
              address = "Sao Jose dos Campos",
             keywords = "DIRA-Ribeir{\~a}o Preto, soil moisture, corn yield model, 
                         stepwise multiple regression.",
             abstract = "The weather and technology effects on corn (Zea mays L.) yield in 
                         the district of Ribeir{\~a}o Preto were studied by a correlation 
                         analysis. The most important monthly meteorological factor 
                         affecting corn yield is total evaporation, which has significant 
                         correlation coefficients in five of the six study months. All 
                         meteorological factors used for analysis are significant in 
                         December, indicating that this is the critical month for corn 
                         production. Technology improvement during the period 1957 to 1975 
                         also plays a significant role in corn yield and explains more than 
                         45% of yield variation. The best yield-weather technology (YWT) 
                         model for corn yield prediction employs the summation of relative 
                         humidity from October to March, and technology trend as 
                         independent variables (predictors). The regression equation of the 
                         YWT model, based on the data period of 1957-1975, is relatively 
                         stable and the prediction errors range from 1.97% to 4.32% when 
                         extrapolating to independent test years after 1975. However, 
                         prediction accuracy of the - model for a current crop year may be 
                         improved by including all the available historic data to the 
                         preceding year of forecasting in calculating the regression 
                         coefficients. According to the test results, the predicted yield 
                         for 1979 is 2527.89 kg/ha, if the summation of relative humidity 
                         between October and March is equal to the average of the same term 
                         from 1957 to 1978. Each 1% increase or decrease from the average 
                         will result in a +- 17.18 kg/ha change in yield. The VWT model 
                         gives accurate com yield information and more importantly 
                         pre-dates the available official estimate by at least 3 months.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
           copyholder = "SID/SCD",
                label = "165",
             language = "en",
                pages = "14",
                  ibi = "6qtX3pFwXQZ3r59YD6/GLFas",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZ3r59YD6/GLFas",
        urlaccessdate = "08 maio 2024"
}