Project Details:

Using engineering tools to identify and quantify biotic and abiotic stress in soybean for customizable agriculture production

Parent Project: This is the first year of this project.
Checkoff Organization:Iowa Soybean Association
Categories:Environmental stress, Crop management systems
Organization Project Code:450-46-04
Project Year:2016
Lead Principal Investigator:Arti Singh (Iowa State University)
Co-Principal Investigators:
Baskar Ganapathysubramanian (Iowa State University)
Daren Mueller (Iowa State University)
Soumik Sarkar (Iowa State University)
Asheesh Singh (Iowa State University)
Gregory Tylka (Iowa State University)
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Keywords: Field Spectro-radiometer, Hyperspectral Imaging, Machine learning, Smart phone app, Soybean disease signatures, UAV

Contributing Organizations

Funding Institutions

Information and Results

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Project Summary

To meet the future demand of food, feed, fiber, and fuel, crop production needs to be doubled by 2050. Crop yields are inherently limited by plant stresses (biotic and abiotic), and plant breeders have protected yield from plant stress losses by incorporating resistance genes and developing more climatically resilient cultivars. Whether it is a private or public sector breeder, the success of plant breeder is quantified by releasing cultivars, which are adopted by farmers on a large scale and that have superior yield, end-use quality, and biotic and abiotic stress resistance.
State-of-the-art: Farmers and researchers rely on phenotyping to determine the health of their crop or to make selections. However, phenotyping (process of collecting data on traits, such as, diseases, insect feeding, yield) can be time consuming (and at times resource intensive) especially on large farms and fields. The bottleneck in phenotyping has driven intense efforts by the scientific community to apply newer technology in field phenotyping. State-of-the-art High Throughput Phenotyping (HTP) has unlocked new prospects for non-destructive field-based phenotyping (Deery et al. 2014) for a large number of traits including physiological, biotic and abiotic stress traits in plants. Both ground and aerial HTP platforms equipped with multiple sensors are being used in agriculture to measure multiple plant traits at varying growth stages rapidly, precisely and accurately (Figure 1). Currently these HTP platforms are being used in crops for phenotyping in breeding plots and for farm scouting. While there have been tremendous improvements in rapidly, and automatically imaging fields, what is currently lacking is the availability of methodology to quickly screen large amount of images generated by HTP imaging platforms into easy-to-use tools (and simple digital signatures of diseases) that will enable the end-user to identify, detect, classify, and predict plant diseases. One major limitation of phenotyping/imaging tools is the ability to identify and differentiate among multiple soybean diseases occurring in the same field at the same time. These limitations are especially true for aerial imagery using manned aircrafts.

Project Objectives

1. Use hyperspectral camera and spectroradiometer to develop disease signatures to distinguish among SCN, SDS, BSR, Charcoal rot and IDC.
2. Develop algorithms to differentiate diseases with confounding symptoms
a) Differentiate between SCN infestation and IDC in field
b) Differentiate between SDS and BSR (only feature to distinguish them is to cut stems)
3. Develop predictions for disease onset using ‘disease signatures’.
4. Develop algorithm to count SCN eggs under the microscope in a rapid and accurate manner.

Project Deliverables

1. Farmers can scout field for diseases using their phone, making scouting easier.
2. Farmers can scout field though aerial systems to identify diseases, which will help them make decisions on pest management in a timely and effective manner.
3. Farmers will save input costs due to their ability to do site-specific management disease management rather than spraying entire fields.
4. Improved profitability due to reduced chemical costs.
5. Provide entrepreneurial opportunities for chemical companies, technology companies, equipment companies, prescription farming companies.
6. Better health and safe environment.

Progress of Work

See attached pdf file

View uploaded report PDF file

Final Project Results

Benefit to Soybean Farmers

Performance Metrics

Project Years