Simulation of maize and soybean yield using DSSAT under long-term conventional and no-till systems
Teerath Rai
A B * , Sandeep Kumar B , Thandiwe Nleya B , Peter Sexton B and Gerrit Hoogenboom C
+ Author Affiliations
- Author Affiliations
A Department of Crop Sciences, University of Illinois, Urbana-Champaign, Champaign, IL, USA.
B Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, SD, USA.
C Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA.
Soil Research 60(6) 520-533 https://doi.org/10.1071/SR21042
Submitted: 16 February 2021 Accepted: 13 January 2022 Published: 10 February 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing
Abstract
Context: No-tillage (NT) has been gaining popularity over the conventional tillage (CT) for agricultural sustainability. Field experiments conducted worldwide to compare crop production under NT vs CT systems are generally site specific and expensive to maintain over longer duration. To overcome this gap, process-based models have been used to simulate the potential impact and benefits of various management practices on crop yield and soil properties under different environmental conditions.
Aims: (1) We evaluated the Cropping System Model (CSM)-CERES-Maize and CSM-CROPGRO-Soybean model for NT and CT systems; and (2) compared the long-term impacts of NT and CT on crop yield and soil organic carbon (SOC).
Methods: Two crop models, available in the Decision Support System for Agrotechnology Transfer (DSSAT), were calibrated and evaluated using maize (Zea mays L.) and soybean (Glycine max L.) yield data from 2006 through 2011 under CT and NT treatments.
Key results: For crop yield, we showed that the coefficient of determination (R2) for the calibration and evaluation phases of CERES-Maize model were 0.94 and 0.94, respectively, while the index of agreement (d) for these phases were 0.93 and 0.86. Similarly, the R2 values for the calibration and evaluation phases of CROPGRO-Soybean model were 1.00 and 0.65, respectively, with d-values of 0.99 and 0.85.
Conclusions: The results from these long-term (30-year) simulations suggest that compared to CT, the NT system enhanced SOC over time and, hence, crop yield and biomass production.
Implications: Application of NT can be beneficial for enhancing the soils and crop production in the long-term as compared to the CT system.
Keywords: CERES-Maize, CROPGRO-Soybean, crop modelling, DSSAT, soil conservation, soil organic carbon, soil tillage, sustainability.
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