Crop modeling for understanding yield-gap causes and the potential for sustainable intensification of soybean in Brazil - Silva, Evandro Henríque Figueiredo Moura da (2021)
In the next decades, the population is expected to rise by more than two billion people, and food demand projections point to the need to substantially increase soybean (Glycine max L.) supply for food, livestock feed, and biofuel. Soybean is the most important food protein source, and Brazil accounts for 37% (based on the 2020/2021 harvest) of the worlds soybean. The country is the largest soybean producer and exporter, with 60% and 40% of its soybean production is in tropical and subtropical environments. It is expected that the intensification of agricultural management will allow substantial increases in food production on existing agricultural lands, with lowest possible global environmental costs. This Ph.D. thesis explored the estimating of soybean potential yield under tropical and subtropical environments associated with agricultural water and nitrogen (N) management using field data analysis and crop modeling. In Chapter 1, we developed the conceptual framework for understanding the crop yield potential factors for soybean cropping systems in Brazil. We prospected water factors on Chapter 2, using field data and crop modeling to evaluate the soil water balance, evapotranspiration and soil water evaporation methods and crop water productivity. We also examined long-term scenarios to determine the impact of sustainable crop water management under different irrigation regimes, soil texture, and tillage practices on soybean growth and development. Chapter 3 focused on the effects of N-fertilization on soybean growth, crop yield, and protein and oil concentration using several doses of N under limited and non-limiting water conditions across thirteen soybean experiments in major soybean Brazilian producing regions. We also explored long-term scenarios to evaluate N management on soybean. The major findings in Chapters 2 and 3 were: (i) CROPGRO-Soybean model is a useful tool to analyze water and N management on soybean under tropical and subtropical environments; (ii) FAO- 56 Penman-Monteith evapotranspiration combined with Ritchie-Two-Stage soil water evaporation methods provided more accurate simulations; and (iii) N-fertilization provided substantially increases on seed protein concentration, despite that showed marginal or no response on soybean crop yield. Chapter 4 estimated the water-limited crop yield potential YP-W and crop yield potential (YP)using the cultivar calibration and model settings obtained in Chapter 2 and 3, and defined sixteen strategically selected agroclimatic zones (CZs) to represent Brazilian production. We also estimated the crop yield gap (YG), climate efficiency (EC), and agricultural efficiency (EA) for all CZs. We quantify an average YP-W of 4,684 kg ha-1, YP of 5,441 kg ha-1 , YG of 3,092 kg ha-1 EC of 78%, and EA of 50%. We also identified that 26% of soybean area in Brazil with EC < 95%, for this area improvements on root length density distribution with no-tillage practices can contribute to irrigated water savings by 20%. This Ph.D. thesis highlighted the importance of improving agricultural management across the soybean sowed in tropical and subtropical conditions to meet food security with environmental sustainability.