Source: TEXAS A&M UNIVERSITY submitted to NRP
FIELD PHENOMICS AND QUANTITATIVE GENETICS IN APPLIED MAIZE BREEDING
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
1021867
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Dec 12, 2019
Project End Date
Dec 9, 2024
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001
Performing Department
Soil & Crop Sciences
Non Technical Summary
Safe, secure, healthy, inexpensive and increasingly productive agricultural commodities remain a cornerstone of increasing American prosperity. Maize (corn) is the most productive U.S. grain crop and farmers plant it because there is high end-user demand, it is easy to grow and often profitable. Plant breeding and agronomic improvements have increased corn yields eight-fold over the last 100 years, a trend that began through research and development in the public sector. While the private sector now excels in maize improvement in the Midwest, the Southern US receives little investment with respect to economic value and productivity is lagging. Major problems facing Southern US corn farmers include losses due to drought and aflatoxin (a carcinogen produced in the grain by a fungus); these problems are expected to increase throughout the U.S. under a changing climate. Corn losses can be most efficiently reduced through scientific plant breeding and genetic improvement. New and improved plant breeding techniques leveraging the latest in scientific technologies need to be developed to meet current and future crop production challenges. Additionally, highly trained students and personnel are needed who understand problems in agriculture and can respond with appropriate solutions. In this project the yield, adaptation, healthfulness and sustainability of corn production will be improved through plant breeding; assisted by newly discovered knowledge and technologies in phenomics, data science, and genomics. The genetic diversity of corn will be increased and drought tolerance, aflatoxin resistance, higher yield, blue grain and improved antioxidants, reduced fertilizer requirements, and increased ecosystem services (such as provided by perennial corn) will be selected for. These improved varieties will sustainably improve economic, environmental, health, and security for farmers, consumers, industry or other stakeholders. We will develop new knowledge and techniques through phenomics, plant breeding and data science that will help all crops be able to be improved to meet societal needs faster (such as predicting the best varieties earlier and more efficiently). We will train students to use modern science to meet farmers and society's needs in the future and train stakeholders on the importance of these technologies.
Animal Health Component
45%
Research Effort Categories
Basic
25%
Applied
45%
Developmental
30%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2011510108010%
2011510209010%
2021510108110%
2021510209010%
2031510108110%
2041510108110%
2061510108110%
2121510108110%
7121510108110%
2051510108110%
Knowledge Area
212 - Pathogens and Nematodes Affecting Plants; 206 - Basic Plant Biology; 204 - Plant Product Quality and Utility (Preharvest); 205 - Plant Management Systems; 203 - Plant Biological Efficiency and Abiotic Stresses Affecting Plants; 712 - Protect Food from Contamination by Pathogenic Microorganisms, Parasites, and Naturally Occurring Toxins; 202 - Plant Genetic Resources; 201 - Plant Genome, Genetics, and Genetic Mechanisms;

Subject Of Investigation
1510 - Corn;

Field Of Science
2090 - Statistics, econometrics, and biometrics; 1081 - Breeding; 1080 - Genetics;
Goals / Objectives
The overall goal of this project is to use science and technology to understand and/or improve the sustainability (both economic and environmental) of agricultural production through crop improvement, specifically of maize (corn). There are four specific objectives:Objective 1: Conduct genetic improvement and advancement of maize and other crops;Objective 2: Develop and deploy new phenomic technologies for plant breeding and agronomy;Objective 3: Advance data science based tools, analytical approaches and discoveries for plant breeding and agriculture;Objective 4: Train and educate the next generation and stakeholders in these approaches.
Project Methods
Objective 1: Conduct genetic improvement and advancement of maize and other crops; Impactful genetic improvement of maize and other crops to be conducted through this project has multiple goals and approaches. Ordered from shortest development timeline to longest are elite by elite, population maintenance and improvement, exotic introgression and adaptation, and perennial development. Elite by elite - After nearly 25 years of breeding competitive elite subtropical maize genetics for Texas and the Southern US, the TAMU maize breeding program has developed and released lines and germplasm with high yield, stress tolerance, low aflatoxin accumulation and high disease resistance (Mayfield et al. 2012; Murray et al. 2019). Elite by elite line crosses will continue to be made within the TAMU breeding program and occasionally between TAMU and expired plant variety protection (ex-PVP) or other public lines. These bred lines will be tested against elite commercial testers lines, including those that have biotech traits (glyphosate tolerance, Bt, etc.) for rapid adoption by seed industry partners to supply improved hybrids to growers. Selection criteria will include improved yield, stress tolerance, disease resistance, decreased flowering times (especially photoperiod sensitivity leading to late flowering in seed production environments), and seed size to decrease hybrid seed production costs while increasing yield; generally in this order. For whiskey or other specialty maize, flavor, appearance, antioxidents and composition will be primary selection criteria followed by those above. Population maintenance and improvement - Population improvement has been an important technique for developing many elite inbreds and may be an end in and of itself for farmers wanting to maintain their own seed. Multiple Texas heirloom and open pollinated cultivars were previously discovered, increased and donated for preservation to USDA GRIN. Additional synthetic populations, such as the Argentine Flinty Composite, 4way and 8way diverse aflatoxin resistant populations, and sweet corn populations have been developed by the Texas A&M breeding program. All of these populations need to be periodically increased and are of increasing interest to growers wanting to decrease input costs. Exotic introgression and adaptation - Exotic germplasm is generally unadapted, primarily tropical in origin, but has phenotypic traits such as disease and stress resistance or biomass production of interest to incorporate into more elite genetics. This material will either be backcrossed into elite material (similar to, or cooperating with, the USDA genetic enhancement of maize project, USDA-ARS-GEM), or selected as lines per se to be adapted to the Texas environment. Perennial development - Perennial maize would decrease input costs (seed, fuel for tillage, etc.), increase ecosystem services (soil cover, wildlife habitat, etc.) and photosynthesize over a longer growing period, possibly increasing grain yield. Similar to other exotic material it also has advantages such as abiotic and biotic stress resistance. For the last 16 years we have been investigating Z. dipploperennis as a donor of perenniality. While it has been easy to recover seed that looks like corn, it is more difficult to recover plants that overwinter (either through rhizomes or crowns), and even more difficult to recover plants that provide both overwintering and yield. For this approach we have changed from managing individual lines to managing and advancing populations of perennial plants. In addition to breeding per se, there are multiple other relevant activities that the research program will conduct. Inbred and population seed increases must be conducted each year for maintenance because Texas corn seed only typically remains reasonably viable for five years and increases must be scaled up for seed distribution. Hybrid seed must be produced each year for testing and remains competitively viable for two to three years. For all breeding and genetics approaches a summer nursery will be grown in Central Texas, a fall/winter nursery will be grown in South Texas. Yield trials will be conducted throughout Texas and the U.S. The research program will also participate in cooperative evaluation and breeding trials, including the maize genomes to fields (G2F) project, the SouthEastern Regional Aflatoxin Trial (SERAT), the Genetic Enhancement of Maize (GEM) project, and others. In addition to maize, pulses and perennial sorghum will also be subjected to breeding activities as appropriate.Objective 2: Develop and deploy new phenomic technologies for plant breeding and agronomy;Phenomics approaches have become the next frontier in plant breeding but require substantial research and development to be effectively deployed in a breeding program. Specific areas this project will continue to develop and advance include near-infrared reflectance spectroscopy (NIRS), phenomic selection approaches, unoccupied aerial systems (UAS) and novel sensors, these will be applied in plant breeding and agronomic management. Specifically RGB, and red-edge imaging of many variables for UAS. Multispectral, fluorescence and Raman spectroscopy may also be used in the field to detect stress, and in the lab to detect stressed grain. The TAMU breeding program will continue to use and develop NIRS predictions on crops to better predict composition (Meng et al. 2015) and yield such as through phenomic selection. Phenomic selection (PS) approaches, involve using high dimensional phenotypic data to develop relationship matrices that can predict yield (Rincent et al. 2018) and can assist the breeding program in making better decisions. The success of Phenomic selection methodologies suggests the importance of high dimensional data collection by other means, the use of UAS among the most promising. UAS can cheaply collect massive amounts of phenotypes across both temporal and spatial scales, useful for both elite line prediction, and biological discovery.Objective 3: Advanced data tools, analytical approaches and discoveries for plant breeding and agriculture; In addition to new methodological tools for phenomics and phenomic selection, new statistical approaches to analyze plant breeding data are useful and important. Improved methods of spatial analysis, identifying and adjusting experimental differences across a field gradient will be explored. Large publicly available and proprietary datasets may be interrogated (including with meta-analyses) to find previously unknown trends, such as the amount of genetic improvement for yield in Texas (Barrero et al. 2013) or the causal factors for pre-harvest aflatoxin from state level loss and weather data. Furthermore, decision makers from breeders to policy makers and even graduate students often lack tools to evaluate larger datasets. Among the most important needs are UAS tools to better and more quickly convert images into actionable data. Publicly available analysis and visualization tools will be developed using R, Python or similar computing platforms and made available through Github, Cyverse or other infrastructures.Objective 4: Train and educate the next generation in these approachesAll research activities will involve and reach early career researchers, including undergraduate, graduate and post-doctoral personnel. Their projects will be transdisciplinary across plant breeding, phenomics, data science, statistics, remote sensing, agricultural engineering, nutrition, and others. They will be mentored to develop independent and impactful careers to make positive improvements in agriculture through the future.

Progress 12/12/19 to 09/30/20

Outputs
Target Audience:Scientists and colleagues, graduate and undergraduate students, farmers/ producers, industry (seed companies primarily) and the public. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Nearly all employed personnel were pursuing a degree (graduate students and technical support were pursuing MS or PhD, undergraduates were pursuing BS) and took classes;PhD level technical support staff excepted. Personnel were given an opportunity to lead one or more research projects. Personnel were introduced to outside visitors and encouraged to meet one on one (where COVID did not prevent this). All personnel attended multiple professional and research seminars throughout the year and some presented their work at regional or national conferences including the ASA/CSSA/SSA meeting, Phenome and other regional or local meetings. How have the results been disseminated to communities of interest?Scientists and colleagues were reached through presentations, publications, and collaborative research activities. Graduate and undergraduate students were reached through formal classroom instructions and in assisting and leading independent research projects. Farmers/ producers were reached through presentations, publications, field days and on-farm research. Industry was reached through personal communication (in person, phone, email) and evaluated our inbred lines and hybrids. The public was reached through popular press presentations, publications and social media. What do you plan to do during the next reporting period to accomplish the goals?As this is the first year of this project, the second year is expected to continue on the accomplishments listed above. Breeding program material and the breeding pipeline will be advanced and flown with UAS. Data will be processed and hopefully this will allow better and earlier yield predictions. The Genomes to Fields project work, graduate student training and improved statistical methodology for plant breeding progress will all continue.

Impacts
What was accomplished under these goals? Activities in all proposed objectives were accomplished as evidenced by publications as well as presentations and students trained. Objective 1: Fall (Lyford Texas) and spring/ summer nurseries (College Station, Texas) were successful in data collection and seed production. Inbred lines were advanced and increased, the focus in 2019 and 2020 was on additional testers for TAMU x TAMU non stiff stalk inbreds, and advancing new stiff stalk inbreds to early generation testing. Perennial corn and sorghum were advanced and increased and screened for overwintering ability. Specialty colored corn and whiskey corn were also further advanced and investigated. Objective 2: Unoccupied aerial system (UAS, drone) campaigns were flown throughout the spring/ summer field season for a Genomes to Fields (G2F) project in addition to breeding program material and graduate student projects being flown. Some orthomosaics and analysis have been conducted and published while others remain ongoing. A study to investigate the impacts of flying height to breeding programs progressed. A new UAS copter with a camera that includes red edge was used to collect some of the data. Objective 3: Plant height was modeled from temporal flights and investigated for yield prediction. Crop vegetation indices were also investigated. A plot calling software (R/UAStools) was submitted and published as was a study using near infrared spectroscopy for phenomic selection (Lane et al. 2020). Preliminary phenomic predictions using UAS were made based on hundreds of extracted traits and look promising. A simulation study showed that high-throughput phenotyping (such as made with UAS) can provide better outcomes than high precision phenotyping; this was submitted for publication. Objective 4: Multiple undergraduate and graduate students were trained in the breeding program. COVID limited the amount of travel these project personnel could have and reduced face to face interactions. Five graduate student led publications were submitted.

Publications

  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Anderson, SN, Seth C Murray*. 2020. R/UAStools::plotshpcreate: Create Multi-Polygon Shapefiles for Extraction of Research Plot Scale Agriculture Remote Sensing Data. Frontiers in Plant Sciences 11: 511768.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Henkhaus, N., M. Bartlett, D. Gang, R. Grumet, E. Haswell, I. Jordon-Thaden, A. Lorence, E. Lyons, S. Miller, S. Murray, A. Nelson, C. Specht, B.Tyler, T. Wentworth, D. Ackerly, D. Baltensperger, P. Benfey, J. Birchler, S. Chellamma, R. Crowder, M. Donoghue, J.P. Dundore-Arias, J. Fletcher, V. Fraser, K. Gillespie, L. Guralnick, M. Hunter, S.Kaeppler, S. Kepinski, F.-W. Li, S. Mackenzie, L. McDade, Y. Min, J. Nemhauser, B. Pearson, P. Petracek, K. Rogers, A. Sakai, D. Sickler, T. Spady, C. Taylor, L. Wayne, O. Wendroth, F. Zapata, and D. Stern. 2020. Plant Science Decadal Vision 2020-2030: Reimagining the Potential of Plants for a Healthy and Sustainable Future. Plant Direct. 4: e00252.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Zhang, M., Y.-H. Liu, W. Xu, C.W. Smith, S.C. Murray and H.-B. Zhang. 2020. Analysis of the genes controlling three quantitative traits in three diverse plant species reveals the molecular basis of quantitative traits. Scientific reports, 10:1-14.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: White, E.L., J.A. Thomasson, B. Auvermann, N.R. Kitchen, L.S. Pierson, D. Porter, C. Baillie, H. Hamann, G. Hoogenboom, T. Janzen, R. Khosla, J. Lowenberg-DeBoer, M. McIntosh, S. Murray, D. Osborn, A. Shetty, C. Stevenson, J. Tevis, and F. Werner. 2020. Report from the conference,⿿identifying obstacles to applying big data in agriculture⿿. Precision Agriculture, 1-10.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Gerald N. De La Fuente*, Ursula K. Frei, Benjamin Trampe, Jiaojiao Ren, Martin Bohn, Nicole Yana, Anderson Verzegnazzi, Seth C. Murray, and Thomas Lübberstedt*. 2020. A diallel analysis of a maize donor population response to in vivo maternal haploid induction: II. Haploid male fertility. Crop Science 60: 873-882
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Steven L. Anderson II, Seth C. Murray,*, Yuanyuan Chen, Lonesome Malambo, Anjin Chang, Sorin Popescu, Dale Cope, and Jinha Jung. 2020. Unoccupied Aerial System Enabled Functional Modeling of Maize Height Reveals Dynamic Expression of Loci. Plant Direct.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: McFarland, Bridget; Naser Al Khalifah; Martin Bohn; Jessica Bubert; Edward S. Buckler; Ignacio Ciampitti; Jode Edwards; David Ertl; Joseph L. Gage; Celeste M. Falcon; Sherry Flint-Garcia; Michael A. Gore; Christopher Graham; Candice N. Hirsch; James B. Holland; Elizabeth Hood; David Hooker; Diego Jarquin; Shawn M. Kaeppler; Joseph Knoll; Greg Kruger; Nick Lauter; Elizabeth C. Lee; Dayane C. Lima; Aaron Lorenz; Jonathan P. Lynch; John McKay; Nathan D. Miller; Stephen P. Moose; Seth C. Murray; Rebecca Nelson; Christina Poudyal; Torbert Rocheford; Oscar Rodriguez; Maria Cinta Romay; James C. Schnable; Patrick S. Schnable; Brian Scully; Rajandeep Sekhon; Kevin Silverstein; Maninder Singh; Margaret Smith; Edgar P. Spalding; Nathan Springer; Kurt Thelen; Peter Thomison; Mitchell Tuinstra; Jason Wallace; Ramona Walls; David Wills; Randall J. Wisser; Wenwei Xu; Cheng-Ting Yeh; Natalia de Leon. 2020. Maize Genomes to Fields (G2F): 2014 ⿿2017 field seasons: genotype, phenotype, climatic, soil and inbred ear image datasets. BMC Research Notes 13: 1-6.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Lane, Holly M., Seth C. Murray*, Osval A. Montesinos?López, Abelardo Montesinos?López, Jose Crossa, David K. Rooney, Ivan D. Barrero Farfan, Gerald N. De La Fuente, Cristine L. Morgan. 2020 . Phenomic Prediction of Maize Grain Yield from Near-Infrared Reflectance Spectroscopy of Kernels with Functional Regression Analyses. The Plant Phenome Journal 3: e20002.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Simone Scalabrin, Lucile Toniutti, Gabriele Di Gaspero, Davide Scaglione, Gabriele Magris, Michele Vidotto, Sara Pinosio, Federica Cattonaro, Federica Magni, Irena Jurman, Mario Cerutti, Furio Liverani, Luciano Navarini, Lorenzo Del Terra, Gloria Pellegrino, Manuela R. Ruosi, Nicola Vitulo, Giorgio Valle, Alberto Pallavicini, Giorgio Graziosi, Patricia Klein, Nolan Bentley, Seth C. Murray, William Solano, Amin Hakimi, Timothy Schilling, Christophe Montagnon, Michele Morgante, Benoît Bertrand. 2020. A single polyploidization event at the origin of the tetraploid genome of Coffea arabica is responsible for the extremely low genetic variation in wild and cultivated germplasm. Scientific Reports 10:1-13.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Pruter, L. S., Brewer, M. J., Murray, S. C., Isakeit, T., Pekar, J. J., & Wahl, N. J. 2020. Yield, Insect-Derived Ear Injury, and Aflatoxin Among Developmental and Commercial Maize Hybrids Adapted to the North American Subtropics. Journal of Economic Entomology, 113(6), 2950-2958.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Murray, S.C.* 2019. Use and Reuse of Agricultural Big Data. 2019. ASA-CSSA-SSSA International Annual Meeting, San Antonio, TX. 11/10-13/2019.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Alper Adak*, Seth C. Murray, Clarissa Conrad, Yuanyuan Chen, Nithya Subramanian, Steven Anderson, Scott Wilde. 2020. Validation of Functional Polymorphisms Affecting Maize Plant Height by Unoccupied Aerial Systems (UAVs) Allows Novel Temporal Detection. Phenome 2020. Tucson, AZ. 2/24-27/2020.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Murray, Seth C.*, Natalie Henkhaus, David B. Stern, Crispin Taylor, David D. Baltensperger, Eric Lyons, Katie L. Rogers, and Plant Summit 2019 participants. 2020. The Plant Science Decadal Vision, 2020-2030 ⿿ Process, Status and Where Phenotyping and Phenomics Fit in. Phenome 2020. Tucson, AZ. 2/24-27/2020.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Adak, Alper, Jose Ignacio Varela, Dustin Eilert, Seth C Murray, Natalia De Leon, Jianming Yu. 2019. Identifying Loci for Delayed Temperate Flowering: Improving Southern Maize (Zea Mays L.) for Midwestern Seed Production. ASA-CSSA-SSSA International Annual Meeting. San Antonio, TX 11/10-13/2019. (Poster and Oral)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Lane, Holly M.*, Seth C Murray, Osval A. Montesinos-Lopez, Abelardo Montesinos-Lopez, Jose Crossa, David K Rooney, Ivan D Barrero-Farfan, Gerald N De La Fuente and Cristine L. S. Morgan. 2019. Phenomic Prediction of Maize Grain Yield Using Near-Infrared Reflectance Spectroscopy. ASA-CSSA-SSSA International Annual Meeting. San Antonio, TX 11/10-13/2019. (Poster and Oral)