Sunday, 6 November 2005 - 1:45 PM
8-4

Yield Gap Analysis of Maize in a High-Yield Production Environment Using a Simulation Model.

John C. Krohn, University of Nebraska-Lincoln, Agronomy Club, 1913 270th St, Albion, NE 68620

This study evaluated the yield potential of maize in irrigated production fields on a farm near Elgin, NE. The objectives were to: (1) estimate the gap between actual yields and yield potential, (2) identify limiting factors contributing to the yield gap, and (3) identify modifications to crop and soil management that would raise yields. Soil and leaf samples were taken to determine if there were soil or nutrient constraints to yield. The Hybrid-Maize simulation model was used to estimate yield potential based on the actual climate data and management practices employed in the experimental fields and to evaluate the impact of modified management options. Simulations were performed for both the 2004 season in which actual crop and soil measurements were taken, as well as for a 17-year time series for which historical climate data were available. A 15% yield gap was estimated between actual yield and the simulated yield potential for the 2004 growing season. Temporary N deficiency and a brief water deficit during grainfilling were identified as the most probable causes of this yield gap. Minor modifications to N fertilizer management and irrigation would likely result in higher yields with minimal costs. Increased plant population was also identified as an option to increase yields while the planting date and hybrid maturities currently used were found to be near optimal for this location. Although economic implications need to be evaluated for the proposed management changes, the results suggest that planting a 2650 GDD hybrid between April 28 and May 2 to achieve 32,500 plants/acre is optimal for this location. Modifying N fertilizer management (but not higher N rates) and more careful irrigation to avoid water stress would lead to the highest and most practical yield according to the robust simulation model and soil and plant testing.

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