The major objective of this experiment was to identify optimum plant population densities for different maize maturity groups depending on the environments’ potential and identify situations that reduce risk of crop failures while maximizing opportunities for better yield when weather conditions are good.
A series of simulations were carried out to identify the yield response of three genotypes: P38F70, P34N43 and Hy624 which represented early, medium and late maturity types, respectively. Planting density was selected as a management option since it is known to influence productivity and profitability of maize production in Australia. Field experiments were conducted using different genotypes and 2, 4 and 6 plant/m2 planting densities at Hermitage, Kingaroy and Emerald. Production risks and opportunities for maximum yields were determined based on cumulative probability using the simulation outputs.
Simulations showed that in relatively better maize growing environments of Hermitage and Kingaroy, increasing planting density from 1 to 4 plants/ m2 was found to be beneficial for late maturing hybrids. It was also noted that productivity can be increased by increasing planting density up to 7 plants/m2 for both quick and intermediate types. In the most marginal production environment, Goondiwindi, increasing planting density beyond 3 plants/m2 for late genotype (Hy624) resulted in a dramatic reduction in yield. At Hermitage, the cumulative probability distribution indicated that the risk of crop failure is very low at 4 plants/ m2while the yield level at 50% probability is about 7 t/ha, suggesting 4 plants/ m2 was the optimum density for late maturing hybrids. In the extremely dry production environment of Goondiwindi, the risk of crop failure was so high with no significant opportunity for better productivity if the late type was to be grown. Nevertheless, the risk of crop failure can be significantly reduced and opportunity for better yield can be significantly increased if the quick or intermediate types were grown at 2 plants/ m2. Simulation outputs were compared using field experiments, and the results generally agree very well particularly for physiological maturity and reasonably well for yield.
This preliminary result showed that modelling framework allows for identifying the genotypes and management options that will minimize production risks and maximize opportunities in target population of environments.