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ARS Home » Midwest Area » Ames, Iowa » Corn Insects and Crop Genetics Research » Research » Publications at this Location » Publication #402906

Research Project: Genetic Optimization of Maize for Different Production Environments

Location: Corn Insects and Crop Genetics Research

Title: Accelerated leaf appearance and flowering in maize after four decades of commercial breeding

Author
item DOS SANTOS, CAIO - Iowa State University
item MIGUEZ, FERNANDO - Iowa State University
item KING, KYLE - Iowa State University
item RUIZ, ALEJO - Iowa State University
item SCIARRESI, CINTIA - Iowa State University
item BAUM, MITCHEL - Iowa State University
item DANALATOS, GERASIMOS J - Iowa State University
item STALLMAN, MICKALA - Iowa State University
item WILEY, EMILY - Iowa State University
item OLMEDO PICO, LIA - Purdue University
item THIES, AUGUST - Donald Danforth Plant Science Center
item PUNTEL, LAILA - University Of Nebraska
item TOPP, CHRISTOPHER - Donald Danforth Plant Science Center
item TRIFUNOVIC, SLOBODAN - Bayer Cropscience
item EUDY, DOUGLAS - Bayer Cropscience
item MENSAH, CLARICE - Bayer Cropscience
item Edwards, Jode
item SCHNABLE, PATRICK - Iowa State University
item LAMKEY, KENDALL - Iowa State University
item VYN, TONY - Purdue University
item ARCHONTOULIS, SOTIRIOS - Iowa State University

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/7/2023
Publication Date: 7/12/2023
Citation: dos Santos, C.L., Miguez, F.E., King, K.A., Ruiz, A., Sciarresi, C., Baum, M.E., Danalatos, G.N., Stallman, M., Wiley, E., Olmedo Pico, L., Thies, A., Puntel, L.A., Topp, C.N., Trifunovic, S., Eudy, D., Mensah, C., Edwards, J.W., Schnable, P.S., Lamkey, K.R., Vyn, T.J., Archontoulis, S.V. 2023. Accelerated leaf appearance and flowering in maize after four decades of commercial breeding. Crop Science. 1-13. https://doi.org/10.1002/csc2.21044.
DOI: https://doi.org/10.1002/csc2.21044

Interpretive Summary: Maize breeding has resulted in large increases in grain yield in modern hybrids compared to older hybrids, but less is known about how long-term breeding has impacted other plant traits. The present study demonstrated that in the Bayer Crop Science program, breeding has increased the rate of vegetative development so that new leaves appear sooner in modern hybrids. The study also showed that the reproductive phase of development began sooner and even overlapped the vegetative phase such that anthesis and silking began before leaves were fully developed. This study will benefit breeders and producers who need to make decisions based on crop growth rate and stage of development.

Technical Abstract: Maize breeding programs have indirectly altered many plant traits, however, our knowledge of some important phenological traits remains unexplored. One such trait is leaf appearance rate (LAR), which is crucial for predicting maize development. We studied 40 short-season (103-day) and 40 long-season (111-day) hybrids released from 1980 to 2020 by Bayer Crop Science. Measurements included weekly counting of collared leaves across 13 experiments in the US Corn Belt. The progression of leaf numbers was expressed as a function of thermal time and described with a tri-linear model. Results indicated that new 111-day hybrids produce leaves faster than old hybrids throughout the vegetative phase (7.4 and 3.1% faster before and after the 9th leaf stage, respectively), while new 103-day hybrids produce leaves faster only after the 9th leaf stage (9.4%). Thermal time to silking and anthesis decreased by about 1 and 0.56°C-day year-1, respectively. Our data revealed that silking and anthesis can precede the final collared leaf by 96°C-day (3.3 days under optimal conditions), which indicates an overlap between vegetative and reproductive phases. We concluded that maize breeding has indirectly altered the rate of vegetative development of maize hybrids without affecting the final leaf number. Present results expand our knowledge base on the genotypic variability in maize development traits, which can improve empirical and process-based models used for crop stage and yield prediction.