Developing functional relationships of corn growth and developmental responses to nitrogen nutrition for modeling

Authors: WALNE, CHARLES - Mississippi State University; JAGMAN, DHILLION - Mississippi State University; Reddy, Krishna; REDDY, RAJA - Mississippi State University

Submitted to: Frontiers of Earth Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/15/2024
Publication Date: 2/27/2025
Citation: Walne, C.H., Jagman, D., Reddy, K.N., Reddy, R.K. 2025. Developing functional relationships of corn growth and developmental responses to nitrogen nutrition for modeling. Frontiers of Earth Science. https://doi.org/10.1007/s11707-024-1137-7.
DOI: https://doi.org/10.1007/s11707-024-1137-7

Interpretive Summary: Nitrogen (N) availability and uptake are essential to support crop growth, development, and yield. Plant root access to N varies temporally and spatially due to soil heterogeneity and dynamic microbial conversions, affected by agronomic practices and environmental conditions. Therefore, quantifying the relationship between plant N content and root morphology during early vegetative growth stages will help unravel how N status could affect a plant’s future ability to uptake nutrients and moisture during critical growth stages occurring later in the growing season. Scientists from Mississippi State University, Mississippi State, Mississippi and USDA-ARS, Crop Production Systems Research Unit, Stoneville, Mississippi have quantified (1) the effects of different N supplies on the N content, growth, development, and physiological characteristics of corn during early growth stages, and (2) the functional relationships held between plant N content and growth, development, and physiological characteristics. Plants were grown in pots under optimal conditions in sunlit controlled-environment chambers but with varying N supplies. Corn physiology growth and developmental traits, including major root traits, responded with changes in shoot N levels. The decline in photosynthesis was primarily due to non-stomatal limitation than the decline in stomatal conductance with declining shoot N levels. Plants under stressed conditions downregulated physiology, including gas exchange parameters and chlorophyll content and nitrogen balance indices and upregulated protective mechanisms such as flavonoids and anthocyanins. Thus, shoot-N deficiency decreased leaf area and photosynthesis of corn plants resulting in lower biomass. The functional relationships produced from this study could help update crop simulation models and apply them to emerging precision agriculture technologies.

Technical Abstract: Nitrogen (N), one of the essential mineral elements, is involved in many biochemical processes and ultimately closely relates to agronomic yield. Our ability to monitor N concentrations in plants through direct tissue sampling or remote sensing has rapidly evolved as technology has advanced. However, functional relationships between morphological and physiological processes and tissue N are not widely published and are needed to advance precision and predictive agricultural technologies further. Therefore, an experiment was conducted to determine the relationships between tissue N concentration and corn morphological and physiological characteristics. Plants were grown in pots under optimal conditions in sunlit controlled-environment chambers but with varying N supplies. Plant growth, developmental, and physiological properties were monitored weekly. Shoot N content differed among treatments and declined over time for all treatment levels. Photosynthesis declined as N content decreased, but these decreases were largely non-stomatal limiting. Reductions in N content were due to declining chlorophyll and N balance index values and increasing flavonoids and anthocyanins. Stem elongation and leaf expansion were highly sensitive to declining N content. Below the soil surface, root growth and development rates fell and held a quadratic relationship with N content. They were less sensitive at low N stress levels than plant growth above the soil surface. The functional relationships produced from this study could help update crop simulation models and apply them to emerging precision agriculture technologies.