Degree Type

Dissertation

Date of Award

1985

Degree Name

Doctor of Philosophy

Department

Agronomy

Abstract

The major objectives of this research were: (1) to test and select weather indexes relative to various periods of the growing season in the presence of soil and management factors for each of the N, P, and K corn leaf concentrations; (2) to use and evaluate a summation technique to relate each leaf nutrient to weather indexes computed for various time periods; and (3) to develop a regression prediction model for each leaf nutrient on weather, soil, and management variables. Concentrations of N, P, and K in the corn leaf at the silking stage and related data were from 1927 observations in 15 Iowa counties representing most soil association areas;A number of excess moisture, moisture stress, and precipitation indexes for various periods of the growing season were evaluated by correlation and regression analysis. A summation technique was applied to 5-day moisture stress and precipitation indexes to assess their effects on the leaf nutrients as well as those of their interactions with selected soil and management variables;The early-season moisture and precipitation indexes had negative effects on the leaf nutrients, while less moisture stress and higher rainfall just prior to silking increased both leaf N and P and midseason rainfall increased leaf K. The summation technique was useful to describe the effects of the weather indexes and of their interactions with other variables on leaf nutrients;The final leaf N model had 76 variates and an R('2) of 0.419. From the explained variability in leaf N, 8.6% was due to the weather indexes, 4.5% to their interactions with other variables, and 1.8% to interactions between soil and management variables;The final leaf P model had 75 variates and an R('2) of 0.512. From the explained variability in leaf P, 8.8% was due to the weather indexes, 3.3% to their interactions with other variables, and 4.2% to interactions between soil and management variables;The final leaf K model had 58 variates and an R('2) of 0.683. From the explained variability in leaf K, 3.5% was due to the weather indexes, 1.1% to their interactions with other variables, and 2.1% to interactions between soil and management variables.

DOI

https://doi.org/10.31274/rtd-180813-5028

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

Claudio Esquivel-Alvarez

Language

en

Proquest ID

AAI8514396

File Format

application/pdf

File Size

314 pages

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