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Updated: Jul 2, 2026

Bioassays for Monitoring Insecticide Resistance

Bioassays for Monitoring Insecticide Resistance

Published on: December 30, 2010

An Assessment Model for Agricultural Databases: The Arthropod Pesticide Resistance Database as a Case Study.

Jane Payumo¹, Julia Bello-Bravo², Vineeth Chennuru¹

¹Research Evaluation and Data Analytics, MSU AgBioResearch, Michigan State University, East Lansing, MI 48824, USA.

|October 25, 2024

Summary

This study introduces a framework to evaluate agricultural databases, like the Arthropod Pesticide Resistance Database, assessing their impact and utility in the digital economy. It offers guidance and metrics for measuring the effectiveness of these vital digital tools.

Keywords:

agricultural database global metrics impact assessment pesticide resistance qualitative survey quantitative analysis

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Area of Science:

Agricultural Science
Digital Economy
Information Science

Background:

The digital economy necessitates robust evaluation of agricultural databases.
Assessing the utility and impact of these resources is crucial for innovation.
The Arthropod Pesticide Resistance Database is a key global resource.

Purpose of the Study:

To present a multi-method approach for evaluating agricultural databases.
To provide a framework for assessing database effectiveness and impact.
To offer practical guidance for stakeholders in the agricultural digital economy.

Main Methods:

Developed a multi-method evaluation approach.
Focused on the Arthropod Pesticide Resistance Database as a case study.
Introduced an index-based method evaluating multiple impact dimensions.

Main Results:

Established a comprehensive framework for agricultural database evaluation.
Demonstrated the utility of the framework using a global pesticide resistance database.
Provided metrics for validating contributions and impact.

Conclusions:

The proposed framework effectively measures the impact of agricultural databases.
This methodology can guide the development and assessment of similar digital tools.
Effective database evaluation supports agricultural decision-making and innovation.