Best management systems for intensifying a maize – soybean rotation: integrating field production, plant physiology, and modeling - Balboa, Guillermo Raul (Kansas State University, 2018)
Potential yield (PY) is defined by the yield limited by temperature, radiation, and genetics – under no limitation on nutrients or water. The difference between PY and actual yield (AY) is defined as yield gap (YG). Management practices such as planting date, row spacing, seeding rate, fertilization program, pest, and disease control can help producers to intensify the productivity of the farming systems and consequently, close the YGs. To evaluate the impact of different management system (MS, specific combination of management practices) on closing the YG the following objectives were established: i) conduct a historical synthesis analysis to characterize shifts in soybean yields, biomass and nutrient uptake and partitioning dissecting the main physiological component related to nutrient use efficiency, seed nutrient composition and nutrient stoichiometry; ii) study the contribution of five MS for intensifying maize-soybean production systems; iii) quantify the nitrogen (N) contribution from the biological N fixation (BNF) process for soybeans under two contrasting MSs (low vs. high inputs); and iv) utilize the same contrasting input treatments to calibrate the Agricultural Production System Simulator (APSIM) for modeling a maize – soybean rotation and apply the parametrized model to estimate a long-term (1980-2016) simulation. For the first objective, main findings indicate that soybean yield increase over time was driven by an increase in biomass with a relatively small variation in harvest index, and with modern varieties producing more yield per unit of N uptake. For the second objective, field experiments demonstrated that intensification practices (narrow row spacing, increasing seeding rate and implementation of a balanced nutrition program) increased yields in both soybeans and maize under rainfed and irrigated conditions. For the third objective, to better understand the soybean N status, BNF measurements were collected during the 2015 growing season and also investigated in a greenhouse setting. The B value, N fixation when plants are fully relying on atmospheric N, changed among varieties, growth stages and plant fractions. Overall B value at R₇ (beginning of maturity) was -1.97 contrasting with the -1.70 value reported as mode according to a literature review. For the range of fixation measured in this research (average of 45-57%), utilization of a B value obtained from the scientific literature or measured in field conditions will have a reduced impact on BNF estimations. Lastly, for the last and fourth objective, the APSIM performed well in estimating yield, biomass production and total N uptake with a high model efficiency and low relative root mean square error (RRMSE). The long-term simulation helped characterize the YG for each crop and MS according to different weather patterns. The modeling approach increased the value of data collected in field experiments. Overall, this research project provided an approach to quantifying and understanding YGs in a maize-soybean rotation and the impact of different MSs on intensifying productivity. Future work can be conducted to model specific MSs to advise producers on the best management systems (BMSs) for sustainably intensifying productivity while minimizing the environmental footprint of current farming systems.
Keywords: Management systems; Soybean; Maize; Modeling; Nitrogen fixation; Ecological intensification