Corn yields as a function of specified production factors expressed as variables in quadratic prediction equations

Corn (Zea mays L.) is one of the major crops of American agriculture. It is a dual purpose crop since it is grown both for grain and forage. The grain is consumed directly and indirectly in different forms by human beings. A high quality silage is made from the forage for livestock. Thus the wide uses of corn indicate its importance. In United States the average per acre yield of corn is 61.8 bushels and the total production per year is 3.55 billion bushels. The productivity of land for a given crop is a function of three major influences–the soil, the climate, and the management practices. Each of these three major influences is made up of several components. The soil includes its physical, chemical, and biological conditions. The climate includes rain fall, temperature, light, etc. The management practices include the application of fertilizer, weed control, plant protection measures, tillage, cropping system, etc. Considerable efforts have been made in recent years to study the relationships between corn yields and one or more components. Probably less work has been done to study the relationships between corn yields and all the components together. The need to predict corn yield on various soils with different types and amounts of management inputs under different environmental conditions has been recognized. Since soil types in Tennessee vary greatly in their capacity to produce corn, more precise prediction information is needed for farmers to better utilize their land and other resources by selecting an appropriate cropping system and management level. The objectives of this study were; 1. to interpret rainfall and soil moisture information in terms of drought as one production factor; 2. to develop methodology for fitting appropriate drought values along with varying levels of selected management factors in quadratic prediction equations; 3. to develop a mathematical relationship in terms of a quadratic function between observed yields and varying levels of selected production factors; 4. to develop "effective" prediction equations for pre-dicting corn yields; and 5. to make an agronomic interpretation of the findings of this study.