Modeling corn yields and optimum N rates under variable soil and climatic conditions in the western part of the El Bajio area, Mexico

Villalpando-Ibarra, Jose Francisco

doi:10.31274/rtd-180813-6274

Cited by 2 publications

(3 citation statements)

References 82 publications

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“…An example of what Passioura had in mind may be seen in the following statement of a researcher (Villalpando Ibarra, 1983) who describes the predicted response of maize plants (grown in light-textured soils) to various weather variables:…”

Section: Gravaminamentioning

confidence: 99%

Simulation of kernel development and assimilate partitioning in maize

Salvador

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Section: Gravaminamentioning

confidence: 99%

Simulation of kernel development and assimilate partitioning in maize

Salvador

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“…A higher R -value indicated a better prediction capability of the equation. Many have reported that this criterion alone is not enough and that some others should be used (Laird and Cady, 1969;Cady and Allen, 1972;Snee, 1977;Nelson and Dale, 1978;Chen and da Fonseca, 1980;Draper and Smith, 1981;Wilson and Sebaugh, 1981;Villalpando-Ibarra, 1983).…”

Section: Evaluation Of Modelsmentioning

confidence: 99%

“…Nevertheless, they advised that all the data should be included when computing the regression coefficients of the multiple regression model. Villalpando-Ibarra (1983) used 80% of his data to develop the 2 model and 20% to evaluate it. He obtained a higher R -value when predicting on the 20% data set.…”

Section: Evaluation Of Modelsmentioning

confidence: 99%

Comparison of corn yield regression models derived from stratified and statewide soil, weather, and management data in Iowa

Macias-Laylle

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Data sets developed in the factorial stratification by AREA and TIME 32 Symbols and identification of the variables included in the corn yield regressions on soil, weather, and management variables 35 Means and ranges of the variables included in the yield regressions on soil, weather, and management variables, stratified data for ETl, ET2, WTl, and WT2 series of models 60 Simple correlation coefficients between yield, management, climatic, and soil variables in the ETl, ET2, WTl, and WT2 data sets 63 Variates included in the regressions of corn yield on the linear or quadratic functions of selected variables. Models QETl and QET2 series 72 Variates included in the regressions of com yield on the linear or quadratic functions of selected variables. Models QWTl and QWT2 series 73 Summary of the model selection steps. Models QETl, QET2, QWTl, and QWT2 series 74 Regression statistics of the final quadratic models of com yield on selected variates. Models QETl-25 and QET2-17 77 Regression statistics of the rinal quadratic models of corn yield on selected variates. Models QWTl-17 and QWT2-15 79 Relative changes in yield (AY) for variables with significant quadratic terms, Models QETl-25, QET2-17, QWTl-17, and QWT2-15a 82 Means and ranges of the variables included in the yield regressions on soil, weather, and management variables, stratified data for EAST, WEST, TIMEl, and TIME2 series of models 100

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Modeling corn yields and optimum N rates under variable soil and climatic conditions in the western part of the El Bajio area, Mexico

Cited by 2 publications

References 82 publications

Simulation of kernel development and assimilate partitioning in maize

Simulation of kernel development and assimilate partitioning in maize

Comparison of corn yield regression models derived from stratified and statewide soil, weather, and management data in Iowa

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