University of Arizona
The goal of my research program is to understand the natural genetic and phenotypic variation present in plant populations. I’m particularly interested in genetic mechanisms responsible for key agronomic, quality, and stress-adaptive traits that are critical to crop production in areas prone to intense abiotic stress pressures (e.g. heat, drought. etc).
By understanding this variation and identifying responsible ways to utilize it, we can invent solutions to global challenges such as food security or fiber needs that our growing population is facing.
My research program is composed of three separate but synergistic areas that combine to elucidate the genetic mechanisms responsible for key agronomic, quality, and stress-adaptive traits.
In the first area, I try to understand the forces that shape the differences in phenotypes we observe, disentangling the effects of genetic variation, environment stress, and their interaction. I explore how the genetic diversity present in plant populations contributes to phenotypic variability, and how genes interact with the environment to give rise to phenotypic plasticity.
The second area focuses on phenomics – the study of phenotypes – with a special interest in traits that show temporal expression patterns. I describe and measure variation of phenotypes (e.g. leaf size, transpiration) in response to environmental fluctuations throughout the plant’s life cycle.
The third area of my research revolves around the use of statistical methods and genetic mapping populations to discover allelic variants and causative genes that explain the phenotypic variation that I study.
The findings from my work offer new tools, news ideas, and new solutions to develop improved crop cultivars that will meet the socioeconomic demands and environmental constraints of the future.
Crops that we work on
The University of Arizona (UA) Field Scanner is the worlds most advanced and complete phenotyping solution offering unparalleled insights into the plant lifecycle. The UA Field Scanner is a fully automated system that is capable of measuring crop growth and development efficiently, accurately, and quantitatively across the growing season. This longitudinal, continuous collection of high spatiotemporal resolution data enables the capture of deep phenotypes that can elucidate the mechanics and dynamics of plant development and physiology in relation to environmental conditions. To deliver these data, a suite of high-quality cameras and sensors are housed in a weather-proof cabinet that is moved over the field area by the supporting 30-ton robotic gantry. This provides accurate and consistent placement of the sensors relative to the crop canopy delivering robust and highly detailed data of unprecedented amount; two to six terabytes of data are capable of being generated per day. By coupling these cutting-edge sensors with newly developed, high-throughput data processing pipelines, traits such as ground cover, canopy height, plant geometry, growth and biomass, counting features, growth stages, vegetation indices, canopy composition, photosystem performance, and many more can be quantifiably described and recorded. Additionally, data fusion techniques are being used to integrate data collected from multiple sensors with different spatial and spectral resolutions to produced fused data sets that contain more information compared to the individual sensors. Through the integration and synthesis of these data streams, novel biological insight is being generated to help solve basic science questions as well as delivered applied solutions for the breeding and development of new crop cultivars and meeting the challenges facing a growing global population.
Phenotyping is one of the greatest limiting factors upon the rate of crop improvement. To ensure that agricultural production can increase in the face of a changing climate, it is imperative that researchers identify and implement more effective means of phenotyping plants. Emerging technologies, including remote sensing via unmanned aerial systems, or UAS, are attractive alternatives that could greatly increase the efficiency of crop improvement programs. Nonetheless, efforts must be made to determine how to implement these technologies and use the data that they generate. To that end, various high-throughput phenotyping projects are currently underway within the program. Rotary-wing UAS equipped with payloads including red, green, and blue (RGB) and thermographic, or infrared, sensors are currently in use, and these devices are being flown or will be flown over economically important crops including cotton (Gossypium hirsutum L.), sorghum (Sorghum bicolor L. Moench), and lettuce (Lactuca Sativa L.). We are using photogrammetry software and algorithms to process these data and extract phenotypes of interest. RGB data is being used to elucidate phenotypic characteristics such as canopy coverage, plant height, estimated yield, growth rate, and more. Thermographic data is being used to determine canopy temperature which is indicative of drought stress levels but also of pathogens such as fusarium wilt in lettuce. Through harnessing UAS imagery with quantitative genetics, we are working towards elucidating the genetic mechanisms that give rise to phenotypic plasticity.
Irrigation for agriculture accounts for 70% of human freshwater use. Without capacity to increase available water, this constraint poses the greatest challenge facing future food and natural resource security. Increases in plant productivity conferred by more effective use of water by plants is thereby needed. However, lack of understanding of the biophysical processes and genetic architecture of traits controlling whole-plant water movement (termed hydraulics) and their relationships and potential trade-offs to yield and quality limits development of more water efficient varieties that have the potential to reach market. Our research in the area of ecophysiological modeling addresses this need by linking genetics, phenomics and physiology via biophysical process-based models. We are leveraging expertise in field-based phenomics and quantitative genetics, genotype x environment modeling (Dr. Wang; Purdue Univ.), stress physiology (Dr.Ewers; Univ. of Wyoming), and biophysical modeling (Dr. Mackay; Univ. at Buffalo), targeting cotton (Gossypium hirsutum L.), a key species for plant-based fiber production. Our teams research aims to elucidate the genetic and physiological mechanisms that underlie their drought response by evaluating diverse germplasm under large-scale field experiments using high-throughput phenomics to develop and test biophysical plant models that simulate across different genotypes.
Meet the Team
Hello! My name is Duke Pauli and I am an assistant professor in the School of Plant Sciences here at the University of Arizona. I was born and raised in Montana where I earned my PhD in Plant Sciences from Montana State University in 2014. My graduate research focused on the application and integration of genomic technologies to the breeding of improved malting barley varieties for the state’s growers. Upon completion of my PhD, I moved to Ithaca, New York where I was a Cotton Incorporated Postdoctoral Fellow in the lab of Dr. Michael Gore at Cornell University. There, my research focused on using high-throughput phenotyping (phenomics) to reveal the genetic basis of stress adaptive traits in cotton as well as how phenomics could be more broadly applied to crop improvement. Since starting my faculty position here at UA in 2018, I have been focused on developing a research program centered on understanding the genetic basis of stress adaptive traits in crop plants through various mechanisms including phenomics, field-based physiology, and quantitative approaches such as models. Broadly, I am interested in all aspects of agriculture from the historical perspective to the actual agronomic practices – I love being involved in ag!
I am a research specialist who was born and raised in Cincinnati, Ohio. I am involved and carry out all day-to-day operations supporting Dr. Pauli’s research efforts. This includes managing and overseeing irrigation scheduling and application, crop management, collecting in-field measurements and just generally making sure everything gets done. I am an Arizona State University graduate in plant genetics and current GIS graduate student at the University of Arizona. I am planning on continuing my education and obtaining a PhD in plant biology. I am an art and live music enthusiast, avid hiker, and animal lover.
I focus on collecting both physical and physiological plant measurements at the Maricopa Agricultural Center, primarily using the LiCOR LI-6400xt portable photosynthesis system, to support the development of ecophysiological models for understanding heat and drought stress. I also aid in other tasks to support the research we do here at MAC incluidng planting, maintaining fields, and other types of data collection. I am eager to learn more about agriculture and excited to get some experience.
I hold a B.S. in Biological and Agricultural Engineering and serve as the on-site engineer for the TERRA-REF robotic field scanner. I have done previous work in high-throughput phenotyping while I was obtaining my degree at Texas A&M University as well as the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT). My interests lie mainly in sensors and robotics but my skills are often needed for many additional tasks to support the research operations at the Maricopa Agricultural Center.
After graduating from Pacific Lutheran University with a bachelor’s degree in biology, I joined the University of Arizona’s Plant Science PhD program. My research interest lies in how plants sense and respond to their environment. As the world population continues to grow, arable land is diminishing. These conditions collectively threaten crop yields and food security across the globe. I hope to study emerging phenotyping technologies that could one day help accelerate plant breeding to meet growing food demands.
N. Ace Pugh
After receiving my doctorate from Texas A&M University, I came to the University of Arizona to be a postdoctoral researcher in Dr. Pauli’s laboratory. I am most interested in using remote sensing technologies, such as UAS-mounted sensors, to efficiently phenotype various crops. I’m also interested in contributing toward developing pipelines to rapidly extract features from flight data. Perhaps most importantly, especially considering our changing climate, is to develop methods to quickly and accurately phenotype drought stress in economically important species. My goal is that I will help evaluate these emerging technologies so that they can be implemented into modern agricultural programs and help to address the challenges of the future.
R&D - Electrical Engineer
Agriculture has been part of my life since I was a kid. Back then, I had no idea that it would become a career. In 1988, I was meandering my way through my electrical engineering degree at Arizona State University and walked into the U.S. Water Conservation Laboratory in Phoenix to apply for a part-time student position. This wonderful USDA facility introduced me to the world of agricultural research, and I continued to work for the USDA for over 26 years. In 2006, the USDA completed construction on a new facility - the U.S. Arid-Land Agricultural Research Center, located on the University of Arizona’s Maricopa Agricultural Center (MAC). My last years with USDA were focused on phenotyping in the field environment. After leaving USDA in 2015, I took a job with LemnaTec Corporation as their North American Field Engineer. As part of my work with LemnaTec, I was again sent back to MAC to manage the construction and support of the world’s largest field phenotyping gantry. Today, I work for the University and am focused on continued gantry operation as well as expansion of the gantry’s capabilities.
After receiving my PhD degree in Plant Physiology from Wageningen University, I joined Dr. Pauli’s laboratory at The University of Arizona. I am interested in physiological and biochemical mechanisms able to confer abiotic stress tolerance to crops and in the identification of their genetic control. My past work mostly focused on the genetic variation in metabolic, antioxidant and stomatal responses to drought in rice and underlying connections with grain yield performance. At Dr. Pauli’s lab I will mainly explore plant genetic variation for stress-adaptive traits under abiotic stress conditions (drought, heat, high light) using high-throughput phenotyping and physiological/metabolic profiling.
I spent a decade and a half working in the private sector, mostly as a computer programmer, but also entertaining the odd impulse into other careers (e.g. glass blowing, airport baggage handling). A few months spent supporting science at the Amundsen–Scott South Pole Station inspired me to acquire a formal scientific education. I received my bachelor's degree at the University of Arizona in geosciences with an emphasis on geology. As a PhD candidate at the UA's Lunar and Planetary Laboratory I studied planet formation via observations of protoplanetary disks. My graduate career led me into my passion for data science and applying statistics and machine learning to large data sets. I am interested in continuing to learn and apply these approaches, and algorithms, to improve the efficiency, affordability and quality of modern plant breeding.
Research Data Specialist
After a tumultuous and short career as a professional musician I discovered a passion for phenomics research while serving as a virtual intern at the Pauli Lab in the Summer of 2020. I now support this research effort by writing machine learning based code for phenotype extraction. I have also been able to make use of my hobby of animation and virtual environment design by creating 3D data visualizations for the teams presentations. I am currently an Undergraduate Biology major at the College of Coastal Georgia, and after graduation I will pursue a graduate level plant sciences degree with the goal of becoming a Professor of Plant Science at a major university. Once in this position, I will be able to share my passion for phenomics on a larger platform and conduct meaningful research that will facilitate smart, sustainable practices in agriculture.
Matthew T Herritt, Jacob Long , Michael Roybal, David Moller, Todd C Mockler, Duke Pauli, Alison L Thompson. “FLIP: FLuorescence Imaging Pipeline for field based chlorophyll fluorescence images.” In review at SoftwareX.
Maimaitijiang, M., Sagan, V., Erkbol, H., Adrian, J., Newcomb, M., LeBauer, D., Pauli, D., Shakoor, N., and Mockler, T.C. 2020. UAV-Based Sorghum Growth Monitoring: A Comparative Analysis of Lidar and Photogrammetry. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 3. doi: 10.5194/isprs-annals-V-3-2020-489-2020Read Study
Alptekin, Burcu, Dylan Mangel, Duke Pauli, Tom Blake, Jennifer Lachowiec, Traci Hoogland, Andreas Fischer, and Jamie Sherman. Combined effects of a glycine-rich RNA-binding protein and a NAC transcription factor extend grain fill duration and improve malt barley agronomic performance. Theoretical and Applied Genetics (2020): 1-16. doi.org/10.1007/s00122-020-03701-1Read Study
We are always looking for talented, passionate people to join the lab! If you have a strong interest in quantitative genetics, plant breeding, field physiology, data science, or abiotic crop stress, please send us your information!
Postdoctoral Associates: There are currently no open positions in the lab. However, we are happy to work with you on submitting a proposal to funding agencies such as NSF Postdoctoral Research Fellowships in Biology or the USDA-NIFA Postdoctoral Program. Submission and proposal information and deadlines vary by program so it is highly recommended that interested individuals check the respective program websites on a frequent basis. If interested in applying for a fellowship or other funding mechanism, please send a CV, cover letter, and outline of your proposal to Duke Pauli at firstname.lastname@example.org. Please do this well in advance of the proposal deadline so that we have adequate time to prepare a competitive proposal.
Graduate Students: Prospective graduate students should apply online at the School of Plant Sciences website (https://cals.arizona.edu/spls/graduate) for consideration of admission to the program. Although limited funding is available, prospective students are expected and encouraged to secure their own, independent funding throughout their time in graduate school. The American Society of Plant Biologists has made available a listing of federal programs and fellowships that provide support for plant science graduate students.