92-6 Improved Characterization of Photosynthetic Parameters of Maize Grown Under Different N Fertilizer Rates Based on Field Light Response Curves.

Poster Number 1016

See more from this Division: C02 Crop Physiology and Metabolism
See more from this Session: Graduate Student Poster Competition
Monday, October 17, 2011
Henry Gonzalez Convention Center, Hall C
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Laila Puntel and Fernando Miguez, Department of Agronomy, Iowa State University, Ames, IA
Predicting maize physiological response, and thus yield, under current and future climate requires an improved understanding of underlying physiological processes.  There is a need to adjust crop growth models to be capable of capturing environmental variability and available resources. The objective of this work was to characterize the photosynthetic parameters of light response curves at different N fertilizer rates and growing stages. The photosynthetic response to light was measured using a LICOR 6400 at different N fertilizer rates (0, 80, 120 and 200 kg ha-1; N0, N80, N120 and N200, respectively).  In this study, parameter optimization was conducted for a C4 photosynthesis model based on Collatz et al. (1992). The parameters optimized were maximum carboxylation of Rubisco (Amax), the initial slope of the response to irradiance (quantum efficiency), and dark respiration (Rd). The relationship between leaf N concentration and photosynthetic parameters through the growing stages was explored. Preliminary results showed a small effect of N fertilization on Amax, quantum efficiency and Rd for corn stages V4, V6 and V8. However, the effect of N fertilization on photosynthetic parameters tends to increase from V10 until reproductive stages. Amax had a response of 2, 4 and 8 µmol m-2 s-1 at N200 compared to N0 rate for V8, V10, V14, respectively. Accurate modeling of photosynthesis in response to environment (i.e. temperature, light, and relative humidity), phenology, N leaf concentration and agronomic management (i.e. N fertilization) can improve short term predictions of growth and response to stresses and longer term predictions of yield and production under future climate. In addition, incorporation of more refined features of physiological traits interacting with environmental factors can generate a robust framework to assist plant breeding.
See more from this Division: C02 Crop Physiology and Metabolism
See more from this Session: Graduate Student Poster Competition