Leaf area index simulation in soybean grown under near-optimal conditions

Different approaches have been used to simulate leaf area index (LAI) in soybean (Glycine max L. Merr). Many of these approaches require genotype-specific calibration procedures. Studies modeling LAI dynamics under optimal growth conditions with yields close to the yield potential of soybean have remained scarce. A sink-driven approach was developed and evaluated for LAI simulation in soybean under near-optimal environments. The rate of change in expanding leaf area was simulated using the first derivative of a logistic function accounting for plant population density, air temperature, and water deficit. The rate of change in senescing leaf area was also simulated using the first derivative of a logistic function, assuming monocarpic senescence that began at the flowering stage (R1). Phenology was simulated as a function of temperature and photoperiod. Data for model development and evaluation were obtained from irrigated field experiments conducted at two locations in Nebraska, where agronomic management was optimized to achieve growth at a near yield potential level. LAI simulation with the proposed model had average RMSE of 0.52 m2 m−2 for independent data at the two locations. The proposed model has minimum input requirements. Interactions between leaf growth and source-driven processes can be incorporated in the future, while maintaining the basic physiological assumptions underlining leaf expansion and senescence.