Duration: 08/27/2020 to 09/30/2022

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Statement of Issues and Justification

To ensure the food, fiber and energy supply for a global population of 9 billion people by 2050, we need to have dramatic development in agriculture science to create crop plants that deliver more nutritious value and higher yield while requiring less inputs (e.g. water and nutrient) and possessing enhanced tolerance to environmental challenges. To this end, plant scientists have been developing and adopting cutting-edge advances in plant biology to establish novel traits in agronomical crops.

Phenomics is a key link between progress in plant genomics and novel trait development in agronomic crops because of its focus on assessing and quantifying plant traits at multiple scales. The phenotype of an organism refers to the observable morphological and physiological properties of the organism. Yet, plant phenotyping has been a bottleneck that limits efficient adoption of genomic tools to improve crop breeding.  Until recently, the majority of plant phenotyping data have been manually collected and were low throughput, time-consuming, and labor intensive. Consequently, these traits were often limited to specific growth stages and did not reflect the dynamic response of crop plants to variations in environmental conditions. Recent advances in remote sensing technologies provide plant biologists the capabilities to ascertain plant responses to environmental variations both in controlled conditions and in field production environments, empowering them to acquire extensive information on key traits of plants.

We propose the creation of a North Central (NC) regional plant phenomics research group to promote efficient phenotyping related research that leverage the established plant phenotyping facilities and capacities among the institutions in the North Central region and to nurture research collaborations among scientists and engineers. Creation of this committee will also coordinate multidisciplinary teams of scientists and engineers in the development of high-throughput phenotyping (HTP) facilities and systems in controlled and field environments. These systems will enable researchers to overcome the phenotyping bottleneck in plant science and crop improvement programs, thereby expanding our knowledge concerning the connection between genomics and predictive phenomics of key US crops at different sites across the region. The synergy of the regional HTP facilities across campus will provide the regional scientists and engineer un-precedent capability in conducting hypothesis-based research that lead to better understanding on the impact of differences in weather, environmental conditions, and production systems on the growth and productivity of various crops, hence providing greater accuracy in predicting crop performance under variable conditions.

Objectives:  The overall goal of this research group is to develop and deploy advanced plant phenotyping technologies to enable creation of knowledge on the impact of genome and environment interaction on plant phenotype, which eventually could result in deploying crops of superior varieties and species.

1. The NC plant phenotyping group will establish a time-sharing mechanism to run experiment for multiple universities’ scientists in the established high-throughput plant phenotyping facilities across the NC region to promote collaboration among scientists in the region. In recent years, there have been tremendous industrial and academic interests in developing and leveraging integrated high-throughput phenotyping facilities. Because this kind of facilities provide unique and advanced capabilities that enable biologists to push the boundary of plant phenomics and to acquire in-depth understanding on biochemical and biophysical processes that underlie desirable physiological traits in specific species or germplasm.  However, because of the significant initial investments, the high cost of operating and maintaining the facilities, and the unique expertise needed in managing the ever-diverging array of technologies in the facilities, it is not practical nor economically viable for each land grand university to establish its own HTP systems like the ones established at Purdue University. The NC regional plant phenotyping committee will not only facilitate unprecedented accessibility of cutting-edge plant phenotyping facilities, but also will promote research activities in multiple universities, thereby enabling the regional universities to more efficiently leverage the ever scarce financial resources to sponsor research and educational activities.


2. Fundamental research activities will establish in-depth connection between the genomic background and phenotypical parameters of key crops in the region. New and existing HTP facilities will be developed to provide the essential capabilities in efficiently assessing crops’ morphological and physiological response to changes in environmental conditions. By making the established HTP systems accessible to scientists across multiple campus, the NC plant phenotyping committee will provide biologists unprecedented capabilities in assessing the response of a wide variety of crops (e.g. corn, sorghum, soybean, wheat) to abiotic and/or biotic stress, such as nutrient deficiency, drought stress, salt and heavy metal stress, high/low temperature, herbicide injury, or disease/insect infection, across the region. The knowledge established using these HTP facilities could be further leveraged in screen for tolerance trait(s) to the above-mentioned stress factors, which eventually will lead to strategies for enhanced stress tolerance and improved yield potential or nutrient values in a wide variety of crops in different climate zones.


3. The plant phenomics research community will serve as a consortium to enable multi-disciplinary collaborations among biologists, engineers, and data scientists across multiple institutions to facilitate the combination of different fields of expertise, such as genetics, genomics, plant physiology, agronomy, crop modeling, computation and informatics, as well as statistics and engineering. The integrated HTP facilities empower efficient plant biology assessment by heavily leveraging non-invasive imaging, machine vision, as well as spectroscopy driven by automated robotics and automated data pipeline based on high-performance computing. The image analysis and data modeling using the matrix extracted from image analysis empower biologists to extract plant growth dynamics, the morphological and physiological characteristics of plants, and to quantify the spatial heterogeneity of key bio-physical parameters as well as the genomic information of the plants. Yet these data/image analysis and modeling are sophisticated and require tremendous expertise in computation/data sciences, as well as in engineering. The NC regional committee, as a consortium that promotes research collaboration across institutions, will perform as a catalyst that drives the cross-disciplinary collaborations among engineers, data scientists and biologists across multiple universities.

Plant phenotyping data collected by collaborators will be deposited in public databases of the integrated high-throughput plant phenotyping facilities of the member institutions. This database will not only promote research in biology, but also empower algorithm development in universities across the region. Furthermore, by making the data collected from the phenotyping facilities accessible to the NC committee members, the committee will also serve as the promoter of development in data management and data mining technologies. To establish efficient connections between phenotypical and genomic data, we not only need to create easily digitized phenotypic data in searchable format—preferably after mathematically annotated, but also there are tremendous need to establish a searchable plant phenotype database. Yet the research topics carried in the phenotyping facilities are very divers, and the data and parameters extracted from the integrated HTP facilities are not structured in-nature. Furthermore, the volume of the data could be exponentially higher than those collected in traditional, low-throughput ways. Therefore, it is paramount to leverage the development in data management technologies to empower a database that is flexible, appropriate, structured, and transparent (FAST).  The data that will be created by the research facilitated by the committee will catalyze the development of such a regional database, which could conceivably expand into the national scale in time. The database in turn will empower the development of novel computational and machine learning algorithms in plant phenomics studies.

Objectives

Procedures and Activities

Expected Outcomes and Impacts

Projected Participation

View Appendix E: Participation

Educational Plan

Organization/Governance

Literature Cited

Attachments

Land Grant Participating States/Institutions

DE, IN, MI, ND

Non Land Grant Participating States/Institutions