| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Centre for Ecology and Hydrology Bush Estate, Penicuik, EH26 0QB, U.K
mgrc{at}ceh.ac.uk
A.R. OVERMAN and R.V. SCHOLTZ III. Marcel Dekker, 270 Madison Avenue, New York, NY 10016. 2002. Hardcover, 344 pp., $150.00. ISBN 0-8247-0825-3.
This book brings together Allan Overman's work of the last 10 years or so on developing equations to describe relationships between crop growth, crop nutrient uptake, amounts of nutrients applied, and time. This is a particular type of empirical crop modeling, aimed at finding functions that describe experimental data. Throughout the book, each development of the equations is evaluated by showing how the functions fit experimental observations, and about one-third of the book consists of exercises inviting the reader to determine model parameters and fit the equations to data. All of it can be done using a pocket calculator and graph paper.
Chapter 1 deals with the ancient art of relating crop yield to amounts of applied nutrients. The authors show that the logistic function generally gives a better fit than the Mischerlich equation, using crop data from early in the twentieth century. In Chapter 2, it is shown how the logistic function also describes the relationship between N uptake and applied N, while dry matter yield tends to be a hyperbolic function of N uptake. Furthermore, a multiple logistic equation can be written that describes the relationship between dry matter yield and applied N, P, and K. Thus far, the authors are sensitive to the criticism that they are simply "curve fitting", but many readers will see it that way.
In Chapter 3, the authors tackle the very different problem of deriving crop growth functions—describing dry matter and nutrient accumulation in crops across time. They use the product of a Gaussian environmental function and a linear intrinsic (genetic) growth function. A different form of the intrinsic function is required for corn, with limited (determinate) growth, as opposed to grass. A final chapter elaborates the mathematical properties of some of the functions.
Although the growth functions have some physical basis, the models described in this book do not pretend to be in any way mechanistic. This contrasts with the work of, for instance, Goudriaan and Monteith (Ann. Bot. 1990, 66:695-701), who derived a crop growth equation with a physiological basis. The whole approach in this book is a far cry from the mechanistic crop models developed by, for instance, de Wit, Charles-Edwards, and Thornley. The book contains one mention of photosynthesis and no mention of respiration, leaf area, or light interception. Overman and Scholtz take the view that it is impossible to develop truly mechanistic models of crop growth because the system is just too complex. Instead, they offer equations, which fit real-world data and so have practical utility in describing what is actually observed. One is left wondering what the functions tell you that the data do not—but perhaps it is better not to enter into that perennial argument.
Overall, I found the book to be very readable. Unusual for these kinds of texts, it is written in a conversational style. Each development of the equations is described in a logical sequence, and the worked examples and exercises enable the reader to get a thorough grasp of how the equations can be used. There is also a short index.
The book will be of value to crop agronomists who are seeking functions to describe their data and find useful relationships between crop growth, yield, and nutrition.
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
