Simulating the yield and some physiological characteristics of maize in different nitrogen conditions using the CERES-Maize model (model evaluation)

Document Type : Research Paper

Authors

1 Ph.D Student of Agrotechnology, Iran Islamic Azad University, Amol. Iran.

2 Assistant Professor, Department of Agrotechnology, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran.

3 Professor, Department of Agrotechnology, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran.

Abstract

Background and objectives: A new dimension in agricultural science has been opened up by the rapid development of computer-based information systems. Physiological processes of plant growth and development can be represented mathematically with a plant simulation model. Many studies have used simulation models to quantitatively analyze the effects of different environmental and management factors on the processes of agricultural plants due to the capability to simulate different processes. Since there is limited data on the ability of CERES-Maize to simulate maize under different nitrogen management treatments in Mazandaran, It took place in Qaemshahr city, and involved recalibration of the CERES-Maize model based on graphical representations and statistical analyses of the performance and physiological traits of this crop.
Material and methods: In order to simulate the physiological traits of maize using CERES-Maize model in different nitrogen treatments, an experiment was carried out in Qarakhil, a research farm of Mazandaran Agricultural Research Center, during 2017 and 2018 as randomized completely block design in four replications. The 10 treatments used in this research included: N1: not use of nitrogen (control), N2: use of 60 kg n ha-1 before planting, N3: use of 120 kg n ha-1 before planting, N4: use of 180 kg n ha-1 before planting, N5: Use of 60 kg n ha-1 in two stages (50% before planting + 50% in stage R1), N6: Use of 120 kg n ha-1 in two stages (50% before planting + 50% in R1), N7: use 180 kg n ha-1 in two stages (50% before planting + 50% in R1), N8: 60 kg n ha-1 in 3 stages (one third before planting + one third in stage R1 + one third in stage R3), N9: 120 kg n ha-1in 3 stages (one third before planting + one third in stage R1 + one third in stage R3), N10: 180 kg n ha-1in 3 stages ( One third was before planting + one third at R1 stage + one third at R3 stage).
Results: It was shown that the model had an acceptable accuracy in simulating the yield, biomass and nitrogen level of a shoot at harvest time. It has also been shown that the trait model does not accurately simulate the leaf area index as well as other traits. According to linear regression analysis, R2 coefficients for the calibration and validation data of the model were 0.69 and 0.57, respectively,. Model validation showed a coefficient of explanation of 0.81, while calibration showed a coefficient of explanation of 0.79. Based on the two-year data, the simulated nitrogen value does not differ significantly from the measured value at 0.95 probability level. The model provided a 0.87 explanation coefficient for the difference between simulated and measured shoot nitrogen, thus indicating its accuracy in simulating total shoot nitrogen over the two-year period.
Conclusion: As a result of this research, the highest yield was achieved in the years 2017 and 2018 with 120 kg n ha-1 applied to the soil as 50% of the base + 50% in R1 stage. In view of the obtained results, the CERES-Maize model can be used as a suitable simulation model to find the optimal nitrogen fertilizer management strategy for maize. For generalizable results, this model can also be applied to interpreting climate data in the northern region of the country in terms of potential production, limitations, and reduction of long-term field experiments.

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