Agricultural Modeling Predicting the effects of genetic coefficients on maize yield in waterlimiting environments
Date of Award
2010
Document Type
Thesis
Degree Name
Bachelors
Department
Natural Sciences
First Advisor
McCord, Jr., Elzie
Keywords
Agricultural Modeling, Maize, Corn, Agriculture, Drought, Aquacrop, DSSAT, Genetics, Coefficients
Area of Concentration
Biology
Abstract
Limited water availability threatens agricultural efficiency, as crops require suffice water for maximum yields and productivity. As human populations grow, water will become more of a concern. Increased water demands require agriculture to compete with municipalities if agriculture is going to feed the masses. I reviewed two models that will soon aid scientists in determining plant modifications to produce marketable yields with available water. Therefore, an overview of drought tolerance in maize is discussed. Genetics and agronomy are two scientific fields that will aid the identification of specific traits or genetic coefficients to improve drought tolerance in crops. Scientists need improved options to predict effects of genetic traits on drought response. Two mathematical models, AquaCrop and CERES-Maize, are available to make rapid predictions and they illustrate physiological and ecological response. These models can serve as powerful tools to advance the science of crop yield improvements. Parameter changes in each model showed maize performance under water stress within 10% of the normal range. Yields were affected by changing the genetic coefficients within each model.. The impact of trait modification was evaluated within each program by comparing resulting yields. A 10% change in DSSAT CERES-Maize filling-rate coefficient resulted in the most yield increases. However, a 10% increase in Aquacrop rooting depth, resulted in the most yield increases. Therefore, CERES-Maize and AquaCrop models have potential uses in predicting and understanding genetic coefficients in maize.
Recommended Citation
Farrell, Anne Amelia, "Agricultural Modeling Predicting the effects of genetic coefficients on maize yield in waterlimiting environments" (2010). Theses & ETDs. 4257.
https://digitalcommons.ncf.edu/theses_etds/4257
Rights
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