| GOSSYM (Cotton) Model |
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GOSSYM is a mechanistic, process-based cotton crop simulation model developed by the USDA Agricultural Research Service (ARS) in collaboration with university partners. Initially developed in the 1980s, the model has undergone several updates and enhancements. GOSSYM simulates crop growth, development, yield, and cotton fiber quality based on environmental factors (solar radiation, temperature, humidity, rainfall, wind, CO₂, and soil physical and hydraulic properties), management practices (such as irrigation, fertilizer, and plant growth regulator application), and cultivar. The model operates on an hourly time step, providing detailed outputs of soil and crop status. It has been validated and is used as a decision-support tool for cotton production.
Key components: Crop Physiology and Growth: GOSSYM includes detailed components for cotton crop growth and development, simulating key stages including squaring, flowering, boll development, and boll opening. It simulates physiological processes like leaf and node addition, stem elongation, leaf area expansion, and fruit development, representing both vegetative and reproductive growth. Model accounts for water, nutrient, heat, and carbon stresses in simulating growth and development. Canopy gas exchange—photosynthesis, stomatal conductance, and transpiration —is modeled using the Farquhar–Ball–Berry leaf energy balance biochemical model. It can also simulate cotton fiber quality, including fiber strength, length, micronaire, and uniformity.
Soil Processes: Soil processes in GOSSYM are simulated using the 2DSOIL module, a comprehensive, two-dimensional finite-element model. 2DSOIL simulates water flow (Richards equation for variably saturated flow), solute and heat transport (convective–dispersive equation), root growth, and root water uptake in a 2D soil profile. Root growth and distribution are simulated using a 2D convective–diffusive model, and nitrogen uptake is driven by a convective–diffusive root N uptake routine. Nitrogen transformations in 2DSOIL account for mineralization, immobilization, nitrification, and denitrification.
References
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Boone, M. Y. L., Porter, D. O., & McKinion, J. M. (1993). Calibration of GOSSYM: Theory and practice. Computers and Electronics in Agriculture, 9(3), 193-203.Calibration of GOSSYM: Theory and practice - ScienceDirect Whisler, F. D., Acock, B., Baker, D. N., Fye, R. E., Hodges, H. F., Lambert, J. R., ... & Reddy, V. R. (1986). Crop simulation models in agronomic systems. Advances in agronomy, 40, 141-208. https://www.sciencedirect.com/science/article/pii/S0065211308602825
Baker, Lambert, J. R., & McKinion, J. M. (1983). GOSSYM: A simulator of cotton crop growth and yield, Technical Bullet in, South Carolina Agricultural Experiment Station, Clemson University , SC, USA.
Landivar, J. A., Baker, D. N., & Jenkins, J. N. (1983). Application of GOSSYM to Genetic Feasibility Studies. II. Analyses of Increasing Photosynthesis, Specific Leaf Weight and Longevity of Leaves in Cotton 1. Crop Science, 23(3), 504-510. https://acsess.onlinelibrary.wiley.com/doi/abs/10.2135/cropsci1983.0011183X002300030015x
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Beegum, S., Hassan, M. A., Reddy, K. N., Reddy, V., & Reddy, K. R. (2025). Assessing fiber quality variability among modern upland cotton cultivars and incorporating it into the GOSSYM-based fiber quality simulation model. Journal of Cotton Research, 8(1), 1-15. https://jcottonres.biomedcentral.com/articles/10.1186/s42397-025-00221-5
Beegum, S., Reddy, K. R., Ambinakudige, S., & Reddy, V. (2024). Planting for perfection: How to maximize cotton fiber quality with the right planting dates in the face of climate change. Field Crops Research, 315, 109483. https://www.sciencedirect.com/science/article/pii/S0378429024002363
Mitra, A., Beegum, S., Fleisher, D., Reddy, V. R., Sun, W., Ray, C., ... & Malakar, A. (2024). Cotton yield prediction: a machine learning approach with field and synthetic data. IEEE Access. https://ieeexplore.ieee.org/abstract/document/10568958/