Corn yield in relation to soil, management, and weather variables in western Iowa

Abstract

This was produced from a copy of a document sent to us for microfilming. While the most advanced technological means to photograph and reproduce this document have been used, the quality is heavily dependent upon the quality of the material submitted. The following explanation of techniques is provided to help you understand markings or notations which may appear on this reproduction.

Selection of management variables for regressing Iowa corn yields on management, climatic, and soil variables

“…Pena- Olvera (1979) reported a high correlation between the barren plants variable and yield (r = -0.46) but it had no meaningful inter correlation with the other management variables that he studied. This lack of intercorrelation may be because the highest amount of barrenness is related to two or more variables, including moisture stress.…”

“…Previous studies of regressing Iowa coim yield on management, climatic, and soil variables will be reviewed primarily; these studies were by Morris (1972), Henao (1976), Pena-Olvera (1979), and Manu (1979) who used the same data as were used in this study. The major objective of this study was to examine the management variables in more detail than the previous investigators had done.…”

“…The remaining group of variables that needed to be studied in detail were the management variables along with the recomputed climatic indexes based on the research of Pena-Olvera (1979), using data from all 15 counties. Several of the management variables and a few soil variables were recoded or transformed to improve their usefulness in the regres sion analysis.…”

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

“…In Iowa, a number of researchers have used a moisturestress index, as described originally by Dale and Shaw (1965), to characterize the weather factor. This stress index, along with soil and management variables, has often been used in studying the effect of these factors on crop yields (Voss and Pesek, 1967;Desselle, 1967;Voss et al, 1970;Morris, 1972;Henao, 1976;Pena-Olvera, 1979;Sridodo, 1981).…”

“…78 potential-predicting variables for corn yields in the first case, and (2) to know the degree of correlation between independent variables in the second. The intercorrelations among independent variables have to be considered because they affect the estimation and interpretation of the effects of individual variables and restrict the use of the developed models (Pena-Olvera, 1979), In order to reduce the intercorrelation problems between independent variables, a correla tion coefficient > than ±0.55 was established. This means that, if the correlation coefficient between two variables is equal to or higher than +0,55, one of these variables was deleted.…”