Prediction by Nonlinear Programming of Relative Chemical Composition of Dietary Botanical Components

Abstract

Nonlinear programming and matrix methods of analysis were used to predict relative chemical composition, energy values, and cellulose digestion coefficients for dietary botanical components. These methods provided data that would be difficult or impossible to obtain by direct experimental techniques. Estimates of chemical composition are presented for plant groups, plant parts, and individual species in the diets of cattle and sheep grazing together in early, middle, and late summer on annual range. These results illustrate the usefulness of, and the need for, training more resource scientists in systems analysis and computer techniques for biological problems.