2014
Evaluation of satellite remote sensing
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Contributor/Checkoff:
Iowa Soybean Association
Category:
Sustainable Production
Keywords:
Data analysisData Management
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Xun Li, Iowa Soybean Association
Co-Principal Investigators:
X B Yang, Iowa State University
Project Code:
Contributing Organization (Checkoff):
Iowa Soybean Association
(n/a)
Institution Funded:
Iowa Soybean Association
(n/a)
Brief Project Summary:

In Iowa, several soybean siseases cause striking canopy changes due to foliar symptoms, such as soybean sudden death syndrome (SDS), white mold, brown spot, frogeye leaf spot, and Cercospora leaf blight. They all cause loss of healthy leaf tissues or defoliation leading to reduced leaf area index (LAI), which can be detected by remote sensing signals.

There are several major advantages of using RS in monitoring plant diseases. Plant canopy changes can be repeatedly assessed uniformly across the entire targeted area while a regular field survey only retrieves information from points in the field. Remote sensing uses a greater range of electromagnetic wave length than what human eyes can...

Unique Keywords:
#, #analytical standards & measurements
Information And Results
Project Deliverables

Final Project Results

We collected historic satellite remote sensing data from AQUA-TERRA systems and Landsat systems during 2003-2013. Based on limited disease data collected in Iowa and several locations in nearby states from 2009 to 2012, analyses showed that changes of canopy due to foliar diseases, including soybean brown spot, sudden death syndrome, and white mold could be detected by satellite imageries using Normalized Difference Vegetation Index (NDVI). Correlations of SDS occurrence with other indices of remote sensing imageries were analyzed as well. Historical SDS occurrence showed good correlation with the date of onset of greenness at a regional scale.

Using aerial remote sensing data in 2013 provided by the On-Farm Network, we examined the correlation of NDVI with soybean SDS and white mold occurrence on our research farms, which showed similar results to the results from historical data. Soil samples were collected from 48 fields with possibly different historical disease occurrence based on satellite imagery assessment to test the presence of SDS pathogen using a selective medium. However, the selective medium was not sensitive enough to detect difference of SDS pathogen presence in different fields. We are seeking for molecular biology approaches, which will be more sensitive in detection of SDS pathogen, and to repeat this examination in the 2014 growing season.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.