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Corn Grain and Stover Yield Prediction at R1 Growth Stage

Spyridon Mourtzinis, Francisco J. Arriaga, Kipling S. Balkcom, Brenda V. Ortiz
Agronomy journal 2013 v.105 no.4 pp. 1045-1050
Secale cereale, Zea mays, atmospheric precipitation, corn, corn stover, cover crops, developmental stages, equations, fertilizer rates, grain yield, growing season, models, nitrogen fertilizers, no-tillage, planting date, prediction, rye, stems, Alabama
Estimating corn (Zea mays L.) grain and stover yield during the growing season is an appealing idea. An accurate yield estimation could benefit farmers, as well as corn-related industries. The objective of this study was to develop regression equations to estimate corn grain and stover yield using easily accessible information (N fertilization rate and cumulative precipitation), and simple plant morphological measurements such as height, stem diameter at various heights, height of the first ear, and plants per hectare. Measurements made at silking (R1) were used since the maximum explainable variability would not exceed 58% at early stages of plant development (V2–V10; between 2-leaf and 10-leaf stages). The experiment was conducted from 2009 until 2011 in two locations, in north and central Alabama, under no-tillage and non-irrigated conditions. Treatments were assigned to a 3 × 4 × 2 complete factorial design arranged in a split-split-plot with three replications. Factors were; winter rye (Secale cereale L.) cover crop (main plot), N fertilization rates (subplot), and stover residue harvest (sub-subplot). All measurements from this study, across years and locations, were used in the final regression equations to create robust prediction models. Equations, with and without intercept, were developed and compared according to several statistical criteria. The final grain yield equation at R1 growth stage included an intercept with a R² of 0.7705. The final stover equation also included an intercept (R² = 0.8473). This study suggests that N rate, total precipitation amount from planting until silking, and simple plant morphological measurements can be used to predict corn yield.