Agriculture Reference
In-Depth Information
8
CHAPTER
Developments in Soil Chemistry
and Soil Classification
Goro Uehara
CONTENTS
Abstract ............................................................................................................................................67
Quantifying Amorphous Materials ..................................................................................................68
Implications ......................................................................................................................................69
Conclusion........................................................................................................................................72
References ........................................................................................................................................72
ABSTRACT
The best predictors of soil chemical behavior are mineralogy and speciÝc surface. Mineralogy
yields information on the physicochemical nature of surfaces, and speciÝc surface provides infor-
mation on the extent of the surface. Recent advances in quantitative mineralogy enable soil scientists
to apply knowledge of mineral properties to predict soil behavior and performance. If, in addition
to this, quantitative mineralogy is supplemented with total chemical analysis, the elements can be
allocated to minerals and the amorphous fraction. Accessory properties that can be predicted from
knowledge of mineralogy, speciÝc surface, and elemental composition include surface charge
characteristics, ion exchange capacity, noncoulombic adsorption-desorption reactions, aggregation,
aggregate stability, pore size distribution, and water, energy, and gas transport coefÝcients. A
classiÝcation system that includes mineralogy, including the amount and composition of the amor-
phous fraction, and speciÝc surface as differentiating criteria should enable users to make better
predictions of soil behavior and performance.
The goal of advancing soil chemistry and soil classiÝcation is to enable individuals who are
responsible for the care and management of land to make better long-term predictions of how
soils will behave and perform when used for speciÝed purposes. Two ways to achieve this goal
are to develop better prediction models and to improve the characterization of soil constituents.
The latter is the more critical, because a model can only be as good as the knowledge we have
about a soilÔs characteristics.
While soil surveys and classiÝcation enable users to Ýnd useful information about how a soil
will behave and perform, users are increasingly asked to make more precise predictions about the
