News and Upcoming Events
Welcome Dr. Jiali Shang Visiting Precision Agriculture Center, UMN
Dr. Shang is a research scientist at the Ottawa Research and Development Centre in Agriculture and Agri-Food Canada (AAFC) and an adjunct professor at the Department of Earth and Space Science and Engineering, York University. She received her Bsc. in geography from Beijing Normal University, M.A. in Geography from University of Windsor, and Ph.D. in Environmental Remote Sensing from University of Waterloo. She has been actively involved in methodology development and application using Earth Observation (EO) technology to vegetation biophysical parameter retrieval, crop growth modeling, and precision farming using both optial and radar data. She has served as international scientific authority for funding proposal review for Canada and other international organizations. She has led multiple national and international research programs to develop EO applications to agriculture.
Title: Supporting Precision Famring with Earth Observation Technology
Wednesday, September 18 2019 | 3:30 PM CDT | S415 Soils Bldg
06 September 2019 - Dr. Ali Moghimi, UMN alum, to present his dissertation research in upcoming webinar
Tuesday, September 24 2019 | 10:30 AM CDT | IEEE RAS Technical Committee on Agricultural Robotics and Automation webinar series
Artificial intelligence and hyperspectral imaging for high-throughput plant phenotyping
Artificial intelligence (AI) is becoming an increasingly imperative tool for sustainable crop production in the era of digital agriculture. In this talk, I present my Ph.D. research work in which I utilized AI to leverage the unique advantages of hyperspectral imaging for investigating desired phenotyping traits in wheat with both indoor and field setups.
For our indoor setup, we developed a sensor-based framework for analysis of hyperspectral images to assess the difference between the salt tolerance of four wheat lines. We were able to attain a quantitative ranking as early as one day after applying salt treatment. In addition, we developed an ensemble feature selection pipeline to identify the most informative spectral bands associated with the desired trait in plant phenotyping. I present the results of testing the developed feature selection pipeline in finding the most prominent bands for salt stress assessment and Fusarium head blight detection in wheat.
For our field setup, we mounted the hyperspectral camera on an unmanned aerial vehicle to collect aerial imagery in two consecutive growing seasons from three experimental yield fields composed of hundreds of experimental wheat lines. We trained a deep neural network with fully connected layers for yield prediction. While conventional harvesting of plots for yield measurement relies on demanding, extremely laborious, and time-consuming tasks, our automated framework could predict the yield of wheat plots in a fast, cost-effective manner. In addition, our framework offers a unique insight for breeders to investigate the yield variation at sub-plot scale - a valuable new index in breeding programs to nominate high-yielding cultivars that are capable of producing a uniform yield across the plot. The results revealed that the proposed framework can also serve as a valuable tool for remote visual inspection of the plots and optimizing the plot size to investigate more lines in a dedicated field each year.
Dr. Ali Moghimi | Biological and Agricultural Engineering | Digital Agriculture Lab | University of California - Davis
Ali is currently a postdoctoral research associate working in the Digital Agriculture lab at the University of California, Davis. He is passionate about conducting interdisciplinary research centered at the food-water-energy nexus. Ali's current research focuses on applying innovative technologies (LiDAR and multispectral/hyperspectral imaging), automation (UAVs), and artificial intelligence (machine learning and deep learning algorithms) in agriculture to facilitate the digital revolution in agriculture. He completed his Ph.D. at the University of Minnesota in February 2019. His Ph.D. research focused on developing sensor-based, automated frameworks for high-throughput phenotyping in wheat.
Ali is currently working on the following projects at the University of California, Davis:
Project 1: prediction of nitrogen status in table grape using aerial multispectral imagery
Project 2: developing a canopy profile mapping technique using UAV-based LiDAR data for almond orchards
Project 3: developing a low-maintenance system to reduce spray drift without limiting the spray and air delivery
22 August 2019 - New graduate course
01 May 2019 - Precision Agriculture Center Seminar Announcement
Insight Into Site-Specific and Adaptive Nitrogen Management for Corn Following Alfalfa
Dr. Jeffrey A. Coulter | Professor and Extension Specialist - Corn-Based Cropping Systems | Dept. of Agronomy of Plant Genetics | University of Minnesota
Seminar hosted by the Precision Agriculture Center
8 March 2019 - Precision Agriculture Center hosts leading researchers as part of the Production Agriculture Symposium
Several students affiliated with the Precision Agriculture Center served on the organizing committee for the 2019 Production Agriculture Symposium. This year's topic was Dialing in: Precision Agriculture in Action, and included three keynote addresses, student oral presentations, expert panel discussions, and a student poster session/competition throughout the day. Overall, it was a great turnout with around 240 attendees - thank-you to all who participated!
5 February 2019 - Congratulations to Ali on his successful defense!
Dr. Ali Moghimi successfully defended on Tuesday, February 5th. Dr. Moghimi will start a postdoc postition in March at University of California - Davis. Congratulations Ali and good luck with your new position in California!
3 February 2019 - Ali Moghimi PhD Defense Seminar
Feb 5 | 10 AM | 310 Alderman
7 January 2019 - Visit us at the Climate FieldView™ Winter Conference
Be sure to stop by our booth at the Climate FieldView Winter Conference to hear about the on-going research at the PAC.
For more information visit the FieldView Event Page
See you then!