Mathematical Models of Crop Growth and Yield / Edition 1

by Allen R. Overman, Richard V. Scholtz III

Overview

Highlighting effective, analytical functions that have been found useful for the comparison of alternative management techniques to maximize water and nutrient resources, this reference describes the application of viable mathematical models in data analysis to increase crop growth and yields. Featuring solutions to various differential equations, the book covers the characteristics of the functions related to the phenomenological growth model. Including more than 1300 literature citations, display equations, tables, and figures and outlining an approach to mathematical crop modeling, Mathematical Models of Crop Growth and Yield will prove an invaluable resource.

Product Details

ISBN-13:	9780824708252
Publisher:	Taylor & Francis
Publication date:	08/27/2002
Series:	Books in Soils, Plants, and the Environment , #91
Edition description:	New Edition
Pages:	344
Product dimensions:	6.00(w) x 9.00(h) x (d)

About the Author

Overman, Allen R.; Scholtz III, Richard V.

Table of Contents

INTRODUCTION
Historic Background
Yield Response Models
Growth Models
Environmental Input
Summary
Exercises
References

SEASONAL RESPONSE MODELS
Background
Extended Logistic Model
Extended Multiple Logistic Model
Water Availability
Legume/Grass Interaction
Summary
Exercises
References

GROWTH RESPONSE MODELS
Background
Empirical Growth Model
Extended Empirical Growth Model
Phenomenological Growth Model
Expanded Growth Model
Exercises
References

MATHEMATICAL CHARACTERISTICS OF MODELS
Background
Phenomenological Growth Model
Expanded Growth Model
Rational Basis for Logistic Model
Coupling Among Applied Soil and Plant Components
Accumulation of Dry Matter and Plant Nutrients
Exercises
References

PASTURE SYSTEMS
Background
Quadratic Model
Linear Exponential Model
Summary
Exercises
References

NONLINEAR REGRESSION FOR MATHEMATICAL MODELS
Background
Logistic Model
Probability Model
Confidence Contours
Sensitivity Analysis
Dimensionless Plots
Correlation Coefficient
Exercises
References
Index

Editorial Reviews

Outlining an approach to mathematical crop modeling, Overman and Scholtz (a professor and research fellow, respectively of the Department of Agricultural and Biological Engineering, U. of Florida) analytical functions are presented in a format that progresses from simpler models towards greater levels of complexity and comprehensiveness. Chapters cover seasonal response models, growth response models, mathematical characteristics of models, pasture systems, and nonlinear regression for mathematical models. Annotation c. Book News, Inc., Portland, OR