Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes
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 calcula...
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Nature Portfolio
2023-05-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-34378-3 |
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author | Sahila Beegum Dennis Timlin Kambham Raja Reddy Vangimalla Reddy Wenguang Sun Zhuangji Wang David Fleisher Chittaranjan Ray |
author_facet | Sahila Beegum Dennis Timlin Kambham Raja Reddy Vangimalla Reddy Wenguang Sun Zhuangji Wang David Fleisher Chittaranjan Ray |
author_sort | Sahila Beegum |
collection | DOAJ |
description | 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 (CO2). 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 CO2 m−2 day−1; index of agreement (IA) 0.89 versus 0.76) and transpiration (RMSE 3.3 versus 13.7 L m−2 day−1; 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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id | doaj.art-fb4177a3d9e44d1cba6a38d31ebf95e1 |
institution | Directory Open Access Journal |
issn | 2045-2322 |
language | English |
last_indexed | 2024-04-09T14:03:55Z |
publishDate | 2023-05-01 |
publisher | Nature Portfolio |
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spelling | doaj.art-fb4177a3d9e44d1cba6a38d31ebf95e12023-05-07T11:11:07ZengNature PortfolioScientific Reports2045-23222023-05-0113111210.1038/s41598-023-34378-3Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processesSahila Beegum0Dennis Timlin1Kambham Raja Reddy2Vangimalla Reddy3Wenguang Sun4Zhuangji Wang5David Fleisher6Chittaranjan Ray7Adaptive Cropping System Laboratory, USDA-ARSAdaptive Cropping System Laboratory, USDA-ARSDepartment of Plant and Soil Sciences, Mississippi State UniversityAdaptive Cropping System Laboratory, USDA-ARSAdaptive Cropping System Laboratory, USDA-ARSAdaptive Cropping System Laboratory, USDA-ARSAdaptive Cropping System Laboratory, USDA-ARSNebraska Water Center, Robert B. Daugherty Water for Food Global Institute, 2021 Transformation Drive, University of NebraskaAbstract 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 (CO2). 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 CO2 m−2 day−1; index of agreement (IA) 0.89 versus 0.76) and transpiration (RMSE 3.3 versus 13.7 L m−2 day−1; 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.https://doi.org/10.1038/s41598-023-34378-3 |
spellingShingle | Sahila Beegum Dennis Timlin Kambham Raja Reddy Vangimalla Reddy Wenguang Sun Zhuangji Wang David Fleisher Chittaranjan Ray Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes Scientific Reports |
title | Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes |
title_full | Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes |
title_fullStr | Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes |
title_full_unstemmed | Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes |
title_short | Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes |
title_sort | improving the cotton simulation model gossym for soil photosynthesis and transpiration processes |
url | https://doi.org/10.1038/s41598-023-34378-3 |
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