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Research and Extension for Unmanned Aircraft Systems (UAS) Applications in U.S. Agriculture and Natural Resources

Principal Investigator/Project Leader: 
Giverson
Mupambi
Department of Project: 
UMass Cranberry Station
Project Description: 

Flights will be conducted using a drone with RGB and a multispectral sensor connected to a real-time kinematic (RTK)  mobile base station. The altitude of the flight will depend on the resolution needed for each specific objective. Flights will be conducted within a 2-hour window period of solar noon on clear days. Images will be collected sequentially following a grid pattern that allows for 80% image overlap between images taken in adjacent transects and 80% between images taken within the same transect. RGB orthomosaics and reflectance maps for multispectral imaging will be built using appropriate photogrammetry software. For multispectral images, reflectance corrections will be applied based on the information from a radiometric calibration target. The detailed method for each objective is as follows:

1. Frost monitoring: We will explore the use of multispectral cameras to monitor bud development in the spring and correlate the data to spring frost tolerance thresholds. Flights will be conducted from spring dormancy until 100% full bloom. Physical samples will also be collected to assess bud phenology and correlate with appropriate multispectral indices.

2. Plant Diagnostics/nutrition: Explore multispectral cameras for plant diagnostics by detecting nutritional deficiencies in cranberry bogs. Flights will be conducted from mid-August to mid-September, which is the traditional time for collecting tissue analysis for nutrient content. The tissue samples will be sent to the lab for tissue analysis. Physical readings from tissue analysis will be correlated with spectral indices. The data produced can be used in future UAS applications for variable-rate fertilizer applications.

4. Insect damage: Utilize RGB imaging to map inset damage on cranberry bogs. A database will also be developed to understand the movement patterns of these insects over different growing seasons. The use of multispectral imaging to detect insect infestation/damage before visual symptoms will also be explored. 

5. Weeds: Use UAS to map weed infestations using both RGB and multispectral sensors. The data produced can be used in future UAS applications for targeted herbicide applications.

6. Disease detection: Use UAS to map disease infestations like Phytophthora and upright die-back. Samples will be collected after each flight and sent to the plant clinic to confirm the pathogens related to the observed damage. The data produced can be used in future UAS applications for targeted fungicide applications.

Topics: 
Agriculture topics: 
Best Management Practices (BMP)/Environmental Protection
Crop and Cropping System
Diseases
Field Crops
Integrated Pest Management
Weeds