Source: UNIVERSITY OF FLORIDA submitted to NRP
LINKING THE GENOTYPE OF PLANT TO THEIR PHENOTYPE THROUGH MODELS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
Reporting Frequency
Annual
Accession No.
1009208
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Feb 9, 2016
Project End Date
Jan 31, 2021
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
UNIVERSITY OF FLORIDA
G022 MCCARTY HALL
GAINESVILLE,FL 32611
Performing Department
Agricultural and Biological Engineering
Non Technical Summary
A Grand Challenge facing the plant science community is the linking of the genotypes (genes) to the phenotypes (plant traits) of the plant, termed the G2P problem. One way to link these two is through the use of crop models by using the genetic background of the plant to define coefficients used in the model. These models would be particularly useful for plant breeders or farmers to either developor select genotypes for specific environments.However, many limitations to the use of crop models for breedingor at the field levelexist. For example, crop models have crude representations of the environment (many lack the effects of diseases, soil compaction, among other factors) which limits their ability to represent interactions between genotype, environment and cropping system. Several "genetic traits" are considered independent and may in fact be directly linked, while many of the parameters representing these "genetic traits" are not yet linked to any gene(s) per se. In addition, some of the subroutines that represent specific traits may not adequately represent the variance in the gene pool, thus are optimized for a narrow range of genotypes. Finally, crop models will likely never be able to incorporate the complete complexity of all gene networks due to limitations in resources and propagation of uncertainties within the models. Despite the limitations, the next generation of crop models will need to include more genetic and physiology linkages which this project will provide.We will approach the G2P problem from several approaches. First, we will usestatistical (empirical) models can that can link quantitative trait loci (QTL) to the parameters in these empirical modelsthrough multi-environment studies. Second,we (Correll, and colleagues) have developed an algorithm using a Markov Chain Monte-Carlo (MCMC) method to estimate the GSPs in the DSSAT CROPGRO-Bean model using a staged approach to estimate crop model parameters. This approach estimates GSPs in the order of developmental growth (i.e., planting to emergence (PLEM) is estimated before emergence to flowering (EMFL)) and targets specific crop traits rather than all outputs of the model. Once the GSPs for the model are estimated, a QTL analysis on the GSP can be conducted and then integrated into a mathematical function (now a gene-based function)to estimate the GSP value. Third, the crop model can be used for selection schemes for the breeder and provide outputs of crop traits that may then be used in identifying QTLs. Finally, we expect to develop new or improve existing modules for predicting crop traits Regardless of the approach, we expect to improve the prediction of key traits ofcrops that are based on the genotype of the plant thus building a tool for plant breeders to optimizecrops or a variety of environments and management scenarios. These tools will be key to selecting and developing crop cultivars to feed the 9 billion people by 2050 especially as Climate Change puts our food security at risk.
Animal Health Component
40%
Research Effort Categories
Basic
40%
Applied
40%
Developmental
20%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
4022499108140%
2057310106040%
2011410102020%
Goals / Objectives
The goals of this project are to define the Genotype by Phenotype linkages in crop systems. This linkage is being done through statistical models and through identifying genes associated with crop modelparameters.The major outcomes from this project are to better understand how different genotypes will perform in varying environments through predictive models.
Project Methods
This project will use new or existing crop or plant level data to improve the understanding of the linkages between phenotype and genotype in a variety of environments through models. This data will be used to build new physiological or morphological models and to estimate parameters in existing crop models. The estimation process will use a Monte Carlos approach that targets field outputs with specific parameters in the crop model. Additional QTL analyses will be performed to link the genotype to the coefficentsofthe model (crop or plant level) to create gene-based models.The sucess of the project will be based on the ability of the gene-based models to acurately predict growth and development along with yield of thecrops. These models will be used to develop teaching curriculum for undergraduate students to learn BIG DATA analyses andbiological systems models. Breeders will be introduced and trained on these topics through workshops.

Progress 10/01/18 to 09/30/19

Outputs
Target Audience:This year we leveraged research with Florida Space Grant (NASA) and this project to promote education in agriculture and excite students K-12 (60 students), undergraduates (100), and stakeholders (i.e., with industry collaboration). We provided an International Course with UF and Wageningen on Crop Physiology with approximately 25 international participants including postdocs, other researchers and graduate students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Below are list of presentations that were presented by students related to this project. E.Larkin. August 1, 2019. Hydroponic control systems. Guest Lecture (instructor Celina Gomez). PLS 3021C: HYDROPONIC SYSTEMS. (over 60 students). University of Florida, Gainesville, FL. · E. Larkin and M. Correll. July 31, 2019. Water-Plants-Microbes and Algae for Sustainable Cities of the Future. To over 40 students (freshmen engineering) through the STEPUP Program at the University of Florida, Gainesville, FL. · M. Correll. Growing Plants For Space Exploration using the SmartPath-HydroPatrol. To over 100 students in the SSTP Program. University of Florida, Gainesville, FL. June 20, 2019. · E. Larkin, M. Correll, E. McLamore, E. Bean. 2019. SmartPath- HydroPatrol: A Wireless Sensor Network and Analytics Platform for Controlled Environments. American Society of Agricultural and Biological Engineers. Boston, MA July 7-10. (oral) · E. Larkin, Robshaw, R., M. Correll, E. McLamore, E. Bean. SmartPath HydroPatrol: A Wireless Sensor Network and Analytics Platform for Controlled Environments. Agricultural and Biological Engineering Annual Research Symposium. March 13, 2019. (poster) · M. Correll, Y. Huang, E. Liu, and E. Larkin. July 12, 2019. Developing IoT sensor networks to support sustainable agriculture: SmartPath-Hydropatrol and Beyond. To Four visiting Scientists and Former Director of the Institute of Plant Nutrition and Resources Beijing Academy of Agriculture and Forestry Science. (oral presentations). · Eric Liu, E. Larkin, M. Correll. (high school student). July 25-26, 2019. Spectrophotometric Monitoring and Analyses of anti-Pathogenic Microbes Grown for Continuous Inoculation of a Hydroponic Nutrient Solution. Annual SSTP Symposium and Poster Session. University of Florida, Gainesville, FL. (oral and poster) · Yanqing Huang, E. Larkin, M. Correll. (high school student). July 25-26, 2019. Design and Operation of a Bioreactor for the Continuous Culturing of Growth Promoting Microbes for Hydroponic Systems. Annual SSTP Oral Symposium and Poster Session. University of Florida, Gainesville, FL. (oral and poster) M.Correll et al. Organizer, instructor, presenter on: Course on Fundamentals of Crop Physiology in a Changing World, UF and Wageningen Universtiy. The Netherlands. May 5-11,2019. https://www.pe-rc.nl/crop-physiology How have the results been disseminated to communities of interest?The major engagement this year has been through presenations, development of an international course, and workshops. These include presentations to high school student (Student Science Traning Program, the Compuatational Camp by the UF Informatics Institute), undergradutates (STEPUP program, research opportunities, projects/poster/oral presentations), graduate student presentations (American Society of Agricultural and Biologiclal Engineers, incorporation of material from project into UF courses) and the international course with Wageningen (The Netherlands) and UF on Fundamentals of Crop Physiology in a Changing World which was a 6 day course and includes a workshop on crop modeling. What do you plan to do during the next reporting period to accomplish the goals?This next period, three publications in press are expected, a student graduating his Ph.D., an undergraduate presenting at two National/International Society meetings and these students sucessfully entering the next stage of their careers. Several members of this project will be panel organizers for a presetnation by the Board of the National Academies to be held at the Universty of Florida with a focus on crop genetics and systems approaches.

Impacts
What was accomplished under these goals? Impact: This year we have educated over 160 indivduals on agricultural systems. This includes presentations to K-12 students including a Computational Camp for highschool students,a Science Training Program (50 stduents) with two high school students who spent 7 weeks working on projects for improved agricultural systems, presentations to undergraduates (approx. 60) and a preliminary study with industry was completed. We developed another approach to modeling plant systems to link genetic information to crop simulation models (article in draft and review by co-authors). This article will show a significant example of how to directly tie genetic-based models to DSSAT-CROPGRO one of the most widely used crop simulation models worldwide and is expected to be published in the upcoming year. We have supported three undergraduate students who worked on collecting data for modeling crop systems one of whom was just hired by the agriculture industry.

Publications


    Progress 10/01/17 to 09/30/18

    Outputs
    Target Audience:The targeted audiences during the reporting period include: Plant Breeders, Microbiologists, Industry in Hydroponics, and elementary school students and their teachers. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Graduate students were able to attend Professional Society Meetings and one student was able to complete an Internship at Bayer (MO). How have the results been disseminated to communities of interest?A workshop was presented to Clay County 4H Students. A peer-reviewed journal article was published on the crop models. A seminar was presented to elementary school students. A course on plant physiology was presented at Wageningen University, The Netherlands. What do you plan to do during the next reporting period to accomplish the goals?This year additional funding to expand the project include more image analyes will be completed.

    Impacts
    What was accomplished under these goals? This year we have developed another method for integrating genetic information into crop models. This method allows for the use of statitical tools to build the model once a crop model framework is added. In addition we have developed a Workshop for 4H on Space Agriculture with Clay County Extension Agents. There were several in attendance at the workshop, approx. 20 students (plus parents) with positive feedback and requests to perform other workshops similar to this. Another presentation was developed for a 3rd grade class at J.J. Finely Gainesville, FL with approximately 25 students in attendance to learn about hydroponics plant phenotyping for space agriculture. As part of the training component a SSTP high school student was trained in plant phenotyping, experimental design, data analyses, report and presentations. An International Course on Plant Physiology was presented to 30 student from around the world at Wageningen University in the Netherlands. The scope of the course description is below: Scope This course focusses on the fundamental knowledge and insight one must have about crops to be able to adapt agronomic practices to the changing world. Here the changing world refers to the environment, increased demands on sustainable production and food quality. We will be integrating the different physiological processes in relation to change using a systems approach, rather than studying them separately. The toolbox in this course will be a variety of plant and crop models (e.g. Gene-based Modelling, Functional-Structural Plant Modelling, Dynamic Crop Growth Modelling, Decision Support Systems) that will be used to understand and address the fundamental challenges and questions. Moreover, we will not only see what these models have to offer but also whether they are state-of-the-art to support agronomic practice decisions in a current and future changing world. Current models are poor in predicting response to extreme events and erratic conditions. We will address crop physiology at different scales of space (field to region and the globe), time (seconds to decades), and level of integration (gene to whole plant). The overall goal of this course is to understand the effects of temperature, light, CO2 or water on the carbon source-sink relationships of plants and to improve the underlying models. Several training opportunities were completed under this reporting period and included k-12 (36), high school students (1), undergraduates (1), graduate students (32) and two visiting high school teachers.

    Publications

    • Type: Journal Articles Status: Published Year Published: 2018 Citation: Wallach, Daniel, Christopher Hwang, Melanie J. Correll, James W. Jones, Ken Boote, Gerrit Hoogenboom, Salvador Gezan, Mehul Bhakta, and C. Eduardo Vallejos. "A dynamic model with QTL covariables for predicting flowering time of common bean (Phaseolus vulgaris) genotypes." European Journal of Agronomy 101 (2018): 200-209.


    Progress 10/01/16 to 09/30/17

    Outputs
    Target Audience:Target Audiences: This past reporting period two undergraduate students (to high school students), two graduate students and one postdoctoral associate worked on this project and were part of the target audience. In addition, we have met with the plant breeding community and crop modeling community to provide evidence and example models of linking genetics to plant phenotypes. TheEffort: The effort of this project includes,formal classroom training, laboratory instruction, and presentations at conferences. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?As integrated into this project,two high school students completed a research experience for 10 weeks, full time through the University of Florida Student Science Training Program with the PD (Correll) on integrating genetic information into crop models. These students presented at the SSTP presentation and poster symposium (July 2017). Approximately 20 high school students were involved in a lecture/in-class exercise entitled "Building the Tools to Manage and Breed Crops: Integration of Genetic and Environmental Information" (June 9, 2017) during thesummer Gator Computing Program at the University ofFlorida. Additionally, two graduate students presented at the American Society of Agronomy, Crop Science Society of America, & Soil Science Society of America, International Annual Meeting in Tampa, FL.Another presentation at the Institute of Biological Engineers on building gene-based crop models through mixed-effect models was presented in Salt Lake City, UT (March 31 2017). How have the results been disseminated to communities of interest?As indicated in the training section, 22 high school students were provided educational experiences in compuational biology as it relates to crop modeling and bridging the gap between phenotypeand genotype of crops. Four seminars were provided to the EGS 1006 course(approximatley 20 undergraduate, engineering students per class) and additionally four lectures to ABE 2012c (approximately15 students per lecture) were providedtoon the methods tolinkthegenotype of plants to their phenotype based on genetic,environment and management information. What do you plan to do during the next reporting period to accomplish the goals?An Internationalcourse is being developed as part of this project for the Agroecology program at the University of Florida in collaboration with Wageningen University. The course will be June 3-8, 2018 at Wageningen Universityentitled "Fundamentals in crop physiology in a changing world".Other plans include exanding thisproject toinclude plants grown in hydroponic systems so we can predict plant responsestocontrolled environment agriculture systems.

    Impacts
    What was accomplished under these goals? We have builtmodels to predict flowering and node addition for the common bean,based on genetic, environment and management information. These models have been published and the data behind them provided to the community of plant breeders, crop modelers and plant scientists in general.A new methodology to esitmate parameters of crop models is published. Several training opportunities were completed under this reporting periodand mainly targetedhigh school students (22), undergraduates (2), graduate students (2)and a postdoctoral associate.

    Publications

    • Type: Journal Articles Status: Published Year Published: 2017 Citation: Hwang, C., Correll, M. J., Gezan, S. A., Zhang, L., Bhakta, M. S., Vallejos, C. E., and Jones, J. W. 2017. Next generation crop models: A modular approach to model early vegetative and reproductive development of the common bean (Phaseolus vulgaris L). Agricultural Systems. 155:225-239.
    • Type: Journal Articles Status: Published Year Published: 2017 Citation: Acharya, S., Correll, M.J., Jones, J.W., Boote, K.J., Alderman, P., Hu, H., and Vallejos, C.E. 2017. Reliability of Genotype-Specific Parameter Estimation for Crop Models: Insights from a Markov Chain Monte-Carlo Estimation Approach. Transactions of the ASABE. 60(5): 1699-1712. (doi: 10.13031/trans.12183)
    • Type: Journal Articles Status: Published Year Published: 2017 Citation: Bhakta, M.S., Gezan, S.A., Michelangeli, J.A.C., Carvalho, M., Zhang, L., Jones, J.W., Boote, K.J., Correll, M.J., Beaver, J., Osorno, J.M. and Colbert, R., 2017. A Predictive Model for Time-to-Flowering in the Common Bean Based on QTL and Environmental Variables. G3: Genes, Genomes, Genetics, 7(12), pp.3901-3912.
    • Type: Journal Articles Status: Published Year Published: 2017 Citation: Zhang, L., Gezan, S. A., Vallejos, C. E., Jones, J. W., Boote, K. J., Clavijo-Michelangeli, J. A., & Correll, M.J. 2017. Development of a QTL-environment-based predictive model for node addition rate in common bean. Theoretical and Applied Genetics, 130(5):1065-1079.
    • Type: Journal Articles Status: Published Year Published: 2017 Citation: Johnson, C.M., Subramanian, A., Pattathil, S., Correll, M.J. and Kiss, J.Z., 2017. Comparative transcriptomics indicate changes in cell wall organization and stress response in seedlings during spaceflight. American journal of botany, 104(8), pp.1219-1231.


    Progress 02/09/16 to 09/30/16

    Outputs
    Target Audience:Target audience: The targeted audience was plant breeders andstudents through educational experiences. Efforts: We have met with plant breeders to discuss methodologies that can improve the efficiency of plant breeding, through a small symposium funded by International Rice Research Insititute (IRRI, Tao Li Director)but our roles asorganizers and participants fell under this project. Although this was held on Nov 1-4, 2016, outside the reporting period, the preparationfor theprogram and intellectual transfer of information was completed during this reporting period. In addition, three undergraduate students had practal experience working in the field through extension and research interships. These students were trained in agronomic practices, plant physiology, and computer imaging techniques. Changes/Problems:Although we were sucessful in phenotyping over 480 plots over two overlapping field seasons, this was challenging. We have learned more efficient ways of collecting data and can streamline the data collection (i.e., not all 20 parameters may be necessary for a good crop model). What opportunities for training and professional development has the project provided?This project has trained three undergraduate students (two in Horticultural Sciences, one in Agricultural and Biological Engineering), one graduate student (Agricultural and Biological Engineering), and one Post-Doc (Horticultural Sciences). How have the results been disseminated to communities of interest?Results can be found in the reported publication (Hwang et al., 2016 available online). What do you plan to do during the next reporting period to accomplish the goals?This next period will require the completion of data analysis from the 480 genotypes of common bean and we willanalyze the results from the tomato to begin building a tomato crop model. These results will be used to write manuscripts and prepare for grant opportunities.

    Impacts
    What was accomplished under these goals? Four separate field sites wereused in Florida, two in Citra, FL and two in Balm, FL. The field sites were used to characterizing the phenology, and physiology of two species of plants (common bean and tomato)using many genotypes. The data will allow us to improve our existing crop models that link genetypes to phenotypes as well as build new models. The twoCitra field experiments eachcontained 140 different genotypes of the common bean and the two Balm had approximately 150-180 different genotypes of tomato. Since the common bean experiments were staggered by six weeks, the beans experienced extreme heat stress in the second planting. This allowed us to find genotypes that still produced yield even in heat stress. For the bean, sample plants were harvested weekly and measured for leaf numbers, dry weight, phenology among other parameters. Through this projectover 8000 images of leaf and stems of beanwerecollected and are now in the process of being analyzed for leaf area.The tomato field experiments has allowed us to bulk up a seed stock of heat tolerant lines that will be used in future experiments to characterizetomato responses to heat stress. As part of this reporting period, a graduate student was able to visit Colombia (CIAT) to grow selected bean lines to improve our modeling efforts on the common bean. His trip was 1/2019 until 5/2016 and his lines have been used as an evaluation of our crop models.

    Publications

    • Type: Journal Articles Status: Published Year Published: 2016 Citation: Hwang, C., Correll, M.J. , Gezan, S.A., Zhang, L, Bhakta, M.S. Vallejos, C.E., Boote, K.J., Clavijo Michelangeli, J.A., Jones, J.W. Next Generation Crop Models: A Modular Approach to Model Early Vegetative and Reproductive Development of the Common Bean (Phaseolus vulgaris L.). Ag. Systems J. Special issue: Next Generation Crop Models. 2016