Mathematical Models of Crop Growth and Yield

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,

Product Details

ISBN-13:	9781135564070
Publisher:	CRC Press
Publication date:	08/27/2002
Series:	Books in Soils, Plants, and the Environment
Sold by:	Barnes & Noble
Format:	eBook
Pages:	344
File size:	20 MB
Note:	This product may take a few minutes to download.

About the Author

Allen R. Overman (Author) , Richard V. Scholtz, III (Author)

Table of Contents

INTRODUCTION
Historic Background
Yield Response Models
Growth Models
Environmental Input
SEASONAL RESPONSE MODELS
Background
Extended Logistic Model
Extended Multiple Logistic Model
Water Availability
Legume/Grass InteractionGROWTH RESPONSE MODELS
Background
Empirical Growth Model
Extended Empirical Growth Model
Phenomenological Growth Model
Expanded Growth Model
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
PASTURE SYSTEMS
Background
Quadratic Model
Linear Exponential Model
NONLINEAR REGRESSION FOR MATHEMATICAL MODELS
Background
Logistic Model
Probability Model
Confidence Contours
Sensitivity Analysis
Dimensionless Plots
Correlation Coefficient

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