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Title: SIMULATING PLANTING DATE EFFECTS ON CORN PRODUCTION USING RZWQM AND CERES-MAIZE

Author
item SASEENDRAN, S. - COLORADO STATE UNIVERSITY
item Ma, Liwang
item Nielsen, David
item Vigil, Merle
item Ahuja, Lajpat

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/30/2004
Publication Date: 1/1/2005
Citation: Saseendran, S.A., Ma, L., Nielsen, D.C., Vigil, M.F., Ahuja, L.R. 2005. Simulating planting date effects on corn production using RZWQM and CERES-Maize Models. Agronomy Journal. 97:58-71 (2005).

Interpretive Summary: Successful corn production in the central Great Plains requires determination of a planting date appropriate to the climate and hybrid maturity length. Planting date trials at various locations and with various hybrids could be conducted over a period of several years to determine optimum planting date. Alternatively, calibrated models of corn growth, development, and yield could be used to determine optimum planting date. In this study we calibrated and validated the Root Zone Water Quality Model and the CERES-Maize model using a data set from three corn hybrids planted at three dates in two years at Akron, CO under irrigation. Both models could be used to predict planting date effects on corn yield. Using the long-term Akron weather record with the CERES-Maize model resulted in latest planting date recommendations of 13 May, 20 May, and 6 May for the 91-day, 101-day, and 109-day hybrids, respectively.

Technical Abstract: Corn (Zea mays L.) production in northeastern Colorado is constrained by an average frost-free period bounded by 11 May to Sep 27. Hence, for optimization of crop yield, it is critical to plant the crop at the appropriate time to fit the hybrid maturity length into the optimum growing season of the locality. Crop models could be used to determine optimum planting windows for a locality. We calibrated the plant parameters of the Root Zone Water Quality Model (RZWQM) and genetic coefficients for the CERES-Maize model and validated their performance against experimental data of three corn hybrids varying in days to maturity, planted on three planting dates in two years at Akron, CO under irrigation. Both models could be calibrated to predict leaf area index (LAI), soil water content, crop water use, and yield with similar levels of accuracy. Both models accurately simulated planting date effects on plant growth, with better simulations from CERES-Maize for LAI and crop water use. Using the long-term Akron weather record, the latest planting dates for the short-, mid-, and long-season hybrids to have a 50% chance of achieving a break-even yield under irrigation were 13 May, 20 May, and 6 May, respectively. Long-term simulations also revealed that the longer maturity length hybrids lose yield faster than short maturity length hybrids with planting delay. The information generated can be useful for making both planting and replanting decisions of the three hybrids in northeastern Colorado.