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

Abstract

Soil-Yield Characterization 21 Corn yield as an index of soil productivity 21 Effects of soil variables on corn yield 24 Yield Characterization-Statistical Approach 32 MATERIALS AND METHODS 40 General Description 40 Site and Soil Variables 44 Location 45 Slope, configuration,and aspect 46 Erosion class and depth of A horizon 4? Organic carbon 4? Natural internal drainage 49 Soil permeability 52 Soil texture 55 Biosequence 57 Structure 57 Plant available water capacity 57 Bulk density 6l Parent material 62 Soil test variables 66 Yield and Management Variables

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

“…R improvement due to addition of quadratic 216 functions of the moisture stress and excess moisture indexes to the base yield regres sion model Table 32. Significant weather index interactions 218 selected for testing in the final model Table 33 (Fly and Romine, 1964;Murray, 1969;Salter et al, 1966;Black, 1968;Davies and Runge, 1969;Malo and Worcester, 1975;Henao, 1976).…”

“…Soil test values for N, P, and K in the surface or plow layer have affected corn yield and its response to applied fertilizers in Iowa (Voss and Pesek, 1967;Desselle, 1967;Turrent-Fernandez, 1968) and by many other researchers elsewhere. Henao (1976) The mathematical model commonly used for fitting data is the polynomial of degree n; the degree is usually n = 2 (the quadratic model)* but n = 1/2 (the square root model) is also common (Dumenil, 1958(Dumenil, » 1961Voss and Pesek, 1967;Laird and Cady, 1969;Pena-Olvera, 1973;Henao, 1976). These models when used to approximate multivariate data are called mul tiple linear regression models.…”

“…In order to include weather variables in this study, soil moisture stress and excess moisture indexes were com puted using the computer program described by Dale and Shaw (1965) and modified by Morris (1972) and Henao (1976).…”

NLEAP Computer Model and Multiple Linear Regression Prediction of Nitrate Leaching in Vegetable Systems

“…These data were log transformed to account for unequal variance. Independent variables were analyzed for colinearity before linear model development [variables having correlation coefficient values (r) > 0.60 were not included in the same model] (Henao, 1976) to avoid models with artificially high R 2 values but low predictive value.…”

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).…”