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Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes. | LitMetric

Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes.

Sci Rep

Nebraska Water Center, Robert B. Daugherty Water for Food Global Institute, 2021 Transformation Drive, University of Nebraska, Lincoln, NE, 68588, USA.

Published: May 2023

AI Article Synopsis

  • - GOSSYM is a detailed cotton crop simulation model that recently enhanced its below-ground process simulations by upgrading to a more advanced 2D soil model called 2DSOIL, focusing on daily water movement.
  • - The model's photosynthesis and transpiration calculations were improved by implementing the Farquhar biochemical model and the Ball-Berry leaf energy balance model, leading to better accuracy in predictions.
  • - The modifications resulted in a significant enhancement in predicting net photosynthesis and transpiration, as well as a 6.0% improvement in yield predictions, making the updated GOSSYM more effective at modeling cotton crop growth.

Article Abstract

GOSSYM, a mechanistic, process-level cotton crop simulation model, has a two-dimensional (2D) gridded soil model called Rhizos that simulates the below-ground processes daily. Water movement is based on gradients of water content and not hydraulic heads. In GOSSYM, photosynthesis is calculated using a daily empirical light response function that requires calibration for response to elevated carbon dioxide (CO). This report discusses improvements made to the GOSSYM model for soil, photosynthesis, and transpiration processes. GOSSYM's predictions of below-ground processes using Rhizos are improved by replacing it with 2DSOIL, a mechanistic 2D finite element soil process model. The photosynthesis and transpiration model in GOSSYM is replaced with a Farquhar biochemical model and Ball-Berry leaf energy balance model. The newly developed model (modified GOSSYM) is evaluated using field-scale and experimental data from SPAR (soil-plant-atmosphere-research) chambers. Modified GOSSYM better predicted net photosynthesis (root mean square error (RMSE) 25.5 versus 45.2 g CO m day; index of agreement (IA) 0.89 versus 0.76) and transpiration (RMSE 3.3 versus 13.7 L m day; IA 0.92 versus 0.14) and improved the yield prediction by 6.0%. Modified GOSSYM improved the simulation of soil, photosynthesis, and transpiration processes, thereby improving the predictive ability of cotton crop growth and development.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163017PMC
http://dx.doi.org/10.1038/s41598-023-34378-3DOI Listing

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