Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system

Abstract Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing sea...

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Main Authors: Kamlesh Kumar, C. M. Parihar, H. S. Nayak, D. R. Sena, Samarth Godara, Rajkumar Dhakar, Kiranmoy Patra, Ayan Sarkar, Sneha Bharadwaj, Prakash Chand Ghasal, A. L.Meena, K. Srikanth Reddy, T. K. Das, S. L. Jat, D. K. Sharma, Y. S. Saharawat, Upendra Singh, M. L. Jat, M. K. Gathala
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Language:English
Published: Nature Portfolio 2024-05-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-024-61976-6
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author Kamlesh Kumar
C. M. Parihar
H. S. Nayak
D. R. Sena
Samarth Godara
Rajkumar Dhakar
Kiranmoy Patra
Ayan Sarkar
Sneha Bharadwaj
Prakash Chand Ghasal
A. L.Meena
K. Srikanth Reddy
T. K. Das
S. L. Jat
D. K. Sharma
Y. S. Saharawat
Upendra Singh
M. L. Jat
M. K. Gathala
author_facet Kamlesh Kumar
C. M. Parihar
H. S. Nayak
D. R. Sena
Samarth Godara
Rajkumar Dhakar
Kiranmoy Patra
Ayan Sarkar
Sneha Bharadwaj
Prakash Chand Ghasal
A. L.Meena
K. Srikanth Reddy
T. K. Das
S. L. Jat
D. K. Sharma
Y. S. Saharawat
Upendra Singh
M. L. Jat
M. K. Gathala
author_sort Kamlesh Kumar
collection DOAJ
description Abstract Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.
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spelling doaj-art-70548baefbd744ae998d1dd7fdb9ef4a2025-08-20T02:39:40ZengNature PortfolioScientific Reports2045-23222024-05-0114111810.1038/s41598-024-61976-6Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat systemKamlesh Kumar0C. M. Parihar1H. S. Nayak2D. R. Sena3Samarth Godara4Rajkumar Dhakar5Kiranmoy Patra6Ayan Sarkar7Sneha Bharadwaj8Prakash Chand Ghasal9A. L.Meena10K. Srikanth Reddy11T. K. Das12S. L. Jat13D. K. Sharma14Y. S. Saharawat15Upendra Singh16M. L. Jat17M. K. Gathala18ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Statistical Research Institute (IASRI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Institute of Farming System ResearchICAR-Indian Institute of Farming System ResearchICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Agricultural Research Institute (IARI)ICAR-Indian Institute of Maize Research (IIMR) Unit DelhiICAR-Indian Agricultural Research Institute (IARI)International Fertilizer Development Centre IN (Center US)International Fertilizer Development Centre- Alabama US (International Center)International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)International Maize and Wheat Improvement Center (CIMMYT), South Asia Regional OfficeAbstract Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.https://doi.org/10.1038/s41598-024-61976-6Ammonia volatilizationCERES-MaizeDSSATNitrate leachingZero tillage
spellingShingle Kamlesh Kumar
C. M. Parihar
H. S. Nayak
D. R. Sena
Samarth Godara
Rajkumar Dhakar
Kiranmoy Patra
Ayan Sarkar
Sneha Bharadwaj
Prakash Chand Ghasal
A. L.Meena
K. Srikanth Reddy
T. K. Das
S. L. Jat
D. K. Sharma
Y. S. Saharawat
Upendra Singh
M. L. Jat
M. K. Gathala
Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
Scientific Reports
Ammonia volatilization
CERES-Maize
DSSAT
Nitrate leaching
Zero tillage
title Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
title_full Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
title_fullStr Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
title_full_unstemmed Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
title_short Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system
title_sort modeling maize growth and nitrogen dynamics using ceres maize dssat under diverse nitrogen management options in a conservation agriculture based maize wheat system
topic Ammonia volatilization
CERES-Maize
DSSAT
Nitrate leaching
Zero tillage
url https://doi.org/10.1038/s41598-024-61976-6
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