Knowledge-Based Reasoning in Integrated Resistance Management: The Colorado Potato Beetle (Coleoptera: Chrysomelidae)

Abstract

The Colorado potato beetle, Leptinotarsa decemlineata (Say), is one of 13 insect and mite species in which development of insecticide resistance has become “critical.” In this paper, we review methods for controlling this important agricultural pest while managing insecticide resistance. Many of these strategies were incorporated into an integrated pest management (IPM) program for northeastern potato growers and encapsulated in a knowledge-based expert system (PotatoES). Three years of field trails evaluating the IPM expert system’s ability to act as a surrogate for a human specialist, its capability to manage Colorado potato beetle resistance development in experimental and commercial fields, and its impact on crop yields and production economics were conducted. Comparison of management recommendations made by PotatoES with those of a human IPM specialist demonstrated a high degree of agreement. Under experimental field conditions, Colorado potato beetle insecticide resistance development was always best managed in populations controlled with the IPM program. In commercial production settings, the expert system resulted in similar (under low insect pressure) or superior (under higher insect pressure) control of resistance development compared with grower practices. Implementation of the IPM program in commercial production was more expensive than standard practices, but resulted in higher crop yields and greater net profits. These results demonstrate the potential utility of know ledge-based approaches to integrated resistance management by showing that these systems can capture and faithfully represent the specialized crop, insect, and disease management knowledge of experienced individuals; manage resistance better than traditional insecticide application regimes; manage a crop profitably; and be practically used as a treatment in a field trial and, as such, be validated in terms of their worth in agricultural decision support.