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United States Department of Agriculture

Agricultural Research Service

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Research Project: Developing the Use of Sensors to Model Bee Colony Dynamics and to Monitor Bee Health Productivity and Performance

Location: Honey Bee Research

Project Number: 5342-21000-018-03
Project Type: Specific Cooperative Agreement

Start Date: May 15, 2013
End Date: May 15, 2015

Objective:
To: 1) develop visual sensors for continuous monitoring of forager traffic and forager mortality in bee hives that will lead to improved remote monitoring of general hive status and improved real-time detection of the impact of pests, diseases, pesticide exposure and other hive management problems; 2) conduct parallel field experiments in Australia and the USA monitoring bee colony growth and activity in addition to environmental factors; and 3) use the resulting field data to field validate analytical and simulation models of bee hives to improve bee health forecasting, understand the dynamics underlying Colony Collapse Disorder, and more precisely identify the effects of management practices, including feeding, and pest and disease control on colony growth and productivity.

Approach:
Bee forager sensors and software under development by the Cooperator will be improved and made available to Australian and U.S. apiaries. As a separate activity, at least two apiaries with at least ten healthy colonies each will be continuously monitored with respect to temperature, weight and activity in addition to environmental variables (weather, forage, and agricultural activity), after controlling for factors such as pest and pathogen load and queen quality. Varroa mites, a major cosmopolitan pest of honey bees, do not occur in Australia so those effects will also be examined. These data will be analyzed and correlated with hive growth as measured by direct hive observation and will be used to validate into recently-constructed analytical and simulation models of colony health and productivity. Statistical and mathematical analyses will be used to identify which continuous data parameters are most indicative and predictive of hive health and activity.

Last Modified: 4/16/2014
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