Phosphorus placement an acid arenosols of the West African Sahel

Phosphorus (P) deficiency is a major constraint to pearl millet (Pennisetum glaucum L.) growth on acid sandy soils of the West African Sahel. To develop cost-effective fertilization strategies for cash poor farmers, experiments with pearl millet were conducted in southwestern Niger. Treatments comprised single superphosphate hill-placed at rates of 1, 3, 5 or 7 kg P ha^−1 factorially combined with broadcast P at a rate of 13 kg ha^−1. Nitrogen was applied as calcium ammonium nitrate at rates of 30 and 45 kg ha^−1. At low soil moisture, placement of single superphosphate in immediate proximity to the seed reduced seedling emergence. Despite these negative effects on germination, P placement resulted in much faster growth of millet seedlings than did broadcast P. With P application, potassium nutrition of millet was improved and seedling nitrogen uptake increased two- to three-fold, indicating that nitrogen was not limiting early millet growth. Averaged over the 1995 and 1996 cropping seasons, placed applications of 3, 5 and 7 kg P ha^−1 led to 72%, 81% and 88% respectively, of the grain yield produced by broadcasting 13 kg P ha^−1. Nitrogen application did not show major effects on grain yield unless P requirements were met. A simple economic analysis revealed that the profitability of P application, defined as additional income per unit of fertilizer, was highest for P placement at 3 and 5 kg ha^−1.

Offline Emergence Engineering For Agent Societies

Many examples for emergent behaviors may be observed in self-organizing physical and biological systems which prove to be robust, stable, and adaptable. Such behaviors are often based on very simple mechanisms and rules, but artificially creating them is a challenging task which does not comply with traditional software engineering. In this article, we propose a hybrid approach by combining strategies from Genetic Programming and agent software engineering, and demonstrate that this approach effectively yields an emergent design for given problems.

Applicability of Emergence Engineering to Distributed Systems Scenarios

Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.