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Process-level crop models integrate mathematical representations of the soil-plant-atmosphere with genetic, environment, and management factors. These tools support a range of needs including on-farm decision support, scientific inquiry, crop breeding, and climate impact assessments. The USDA-ARS Adaptive Cropping Systems Laboratory models include the current state of empirical knowledge and theories regarding crop and soil processes. These simulators incorporate mechanistic representations of gas exchange, energy balances, relationships between crop development and temperature, and responses to short- and long-term stresses. Unique sets of genetic coefficients account for phenotypic differences among crop varieties, accounting for responses to temperature, photoperiod, fertility and drought, as well as inherent growth rates. ACSL models are integrated with a two-dimensional soils module which allows representation of row topography and vertical / lateral movement of roots, water, solutes, gases, and heat through the soil profile. Recent improvements provide a broader, more accurate range of agricultural system assessments.
- 1 Introduction
- 2 Crop model structure
- 3 Input data
- 4 Model calibration: genetic coefficients determining plant growth characteristics
- 5 Other data inputs and output data
- 6 Distinctive features of ACSL crop models
- 7 Case studies: on-farm applications
- 8 Case studies: climate change impacts
- 9 Case studies: crop quality
- 10 Case studies: soil carbon sequestration
- 11 Conclusion and future trends
- 12 Where to look for further information
- 13 References