Can UAV technology be used for peanut variety selection?

Institution:

Virginia Polytechnic Institute and State University

Budget ID:

1415

Project ID:

447

Report BID:

State:

Virginia

Region:

Virginia

State Group:

VA-54

Project Fiscal Year:

2016

Category:

Breeding/Genetics/Biotech

Report Type:

Report Received Date:

Investigator:

Balota

Project NPB Budget:

$14,210

This work was aimed at validating drone technology use for improving and expediting breeding selection for drought tolerance in peanut. Drought stress was imposed by covering the plots with two rainout shelters staring at beginning pegging. In the same field set up, well watered plots were replicated next to water stressed plots also replicated under the shelters. Weekly measurements of normalized difference vegetation index (NOVI) and canopy temperature differential (CT) were taken. On Aug 3 and IO at 15 and2l days after water stress imposition wilting was rated visually and pictures of individual plots were taken. After harvest, pod yield, Sound Mature Kernel (SMK) content and Crop Value were determined. Data show strong relationship between the agronomic traits and vegetation indices determined as CT, NDVI, and from RGB pictures. These denotes that both ground and aerial indices can be used to predict peanut performance under a range of soil water regimes. However, more research is needed to identify which indices or combination of them can be used for verity selection. 

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