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ARS Home » Southeast Area » Stoneville, Mississippi » Crop Production Systems Research » Research » Publications at this Location » Publication #404882
Research Project: Development of Productive, Profitable, and Sustainable Crop Production Systems for the Mid-South

Location: Crop Production Systems Research

Title: Examining the corn seedling emergence–temperature relationship for recent hybrids: insights from experimental studies

Author
item BEEGUM, SAHILA - University Of Nebraska
item WALNE, CHARLES H - Mississippi State University
item Reddy, Krishna
item Reddy, Vangimalla
item REDDY, RAJA - Mississippi State University

Submitted to: Agricultural & Environmental Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/25/2023
Publication Date: 10/27/2023
Citation: Beegum, S., Walne, C., Reddy, K.N., Reddy, V., Reddy, R. 2023. Examining the corn seedling emergence–temperature relationship for recent hybrids: insights from experimental studies. Agricultural & Environmental Letters. 12(21):3699. https://doi.org/10.3390/plants12213699.
DOI: https://doi.org/10.3390/plants12213699

Interpretive Summary: Corn emergence is a crucial factor that significantly affects the final yield of this widely-grown crop. To optimize corn yields, farmers require an accurate model that predicts the timing of emergence. Scientists from Mississippi State University, Mississippi State, Mississippi; University of Nebraska, Lincoln, Nebraska; USDA-ARS, Crop Production Systems Research Unit, Stoneville, Mississippi; and USDA-ARS, Adaptive Cropping System Laboratory, Beltsville, Maryland have developed a statistical model for emergence as a function of soil and air temperatures for recent corn hybrids. The developed model was evaluated and compared with that of existing models. The developed quadratic model relating the air temperature with time to emergence was more accurate for all corn hybrids followed by the quadratic model based on soil temperature. The growing degree days-based model was overpredicting at lower temperatures and vice-versa. The developed model can be helpful for farmers, researchers, and crop management professionals to make informed decisions related to corn crop management.

Technical Abstract: Corn emergence is a critical factor affecting crop yields, and an accurate prediction of emergence is necessary for crop management decisions. This study developed a statistical model for emergence as a function of soil and air temperatures for recent corn hybrids. The developed model is evaluated and compared with that of existing models. The developed quadratic model relating the air temperature with time to emergence was more accurate for all corn hybrids (coefficient of determination (R2): 0.97, root mean squared error (RMSE): 0.42 days) followed by the quadratic model based on soil temperature (R2: 0.96, RMSE: 1.42 days), linear model for air (R2: 0.94, RMSE: 0.53 days) and soil temperature (R2: 0.94, RMSE: 0.70 days). The growing degree days-based model was overpredicting at lower temperatures and vice-versa. The developed model can be helpful for farmers, researchers, and crop management professionals to make informed decisions related to corn crop management.