The Influence of Seeding rates on Crop Yield in a DSS Framework: Application to two Alfalfa Cultivars in Sudan

Abstract

This paper presents a decision support system to support agronomists, stand on their ideas and helps them to determine the best level of seeding rate based on the data collected from their field’s experiment. This study employs the split-plot algorithm of Gomez & Gomez (1984) under the framework of a decision support system (DSS). The DSS that automated the Split plot procedure, based on which the best seeding rate out of several rates of the agronomist’s experiment is discussed in this paper. The DSS was also able to incorporate several cultivars in addition to the different seeding rates.