Banner
Current IssueEditorial BoardOnline First ArticlesArchive
Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 52 issue 4 (august 2018) : 392-397,   Doi: 10.18805/IJARe.A-4722

Simulation of phenology, total nutrient uptake and grain yield of wheat under different irrigation and nitrogen application managements in Hisar, India using the DSSAT-CSM-CERES-Wheat model

M
Mukesh Kumar
R
R.K. Pannu
B
Bhagat Singh
Cite article:- Kumar Mukesh, Pannu R.K., Singh Bhagat (2018). Simulation of phenology, total nutrient uptake and grain yield of wheat under different irrigation and nitrogen application managements in Hisar, India using the DSSAT-CSM-CERES-Wheat model. Indian Journal of Agricultural Research. 52(4): 392-397. doi: 10.18805/IJARe.A-4722.

ABSTRACT

The purpose of this study was the calibration and validation of DSSAT-CSM-CERES-Wheat model (v4.5) for wheat in Hisar conditions. The DSSAT-CSM-CERES-Wheat model was calibrated with the field experimental data of rabi 2010-11 having 3 levels of irrigation (I1-one irrigation at crown root initiation [CRI], I2- two irrigations at CRI and heading and I3- four irrigations at CRI, late tillering, heading and milking) and 5 nitrogen levels (0, 50, 100, 150 and 200 kg N/ha) and validated with data of experiment rabi 2011-12 conducted at Hisar (29°10’ N and 75°46’ E). The model performance was evaluated using average error (Bias), root mean square error (RMSE), normalized root mean square error (nRMSE), index of agreement (d-stat) and coefficient of determination (r2), and it was observed that DSSAT-CSM-CERES-Wheat model was able to predict the phenology, total nutrient uptake and grain yield of wheat with reasonably good accuracy. The simulated results were within the permissible limit of the error (error % less than ±15).

REFERENCES

  1. Ambose, J.R. and Rosech, S.E. (1982). Dynamic estuary of model performance. ASCE Journal of Environmental Engineering. 108: 51-71 pp.
  2. Andarzian, B., Gerrit, H., Bannayan, M.,Shirali, M. and Andarzian, B. (2014). Determining optimum sowing date of wheat using CSM-CERES-Wheat model. Journal of the Saudi Society of Agricultural Sciences. 13: 15-26.
  3. Arora, V.K., Singh, H. and Singh, B. (2007). Analyzing wheat productivity responses to climatic, irrigation and fertilizer-nitrogen regimes in a semi-arid sub-tropical environment using the CERES-Wheat model. Agricultural Water Management. 94: 22-30.
  4. Hirel, B., Gouis, J., Ney, B. and Gallais, A. (2007). The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches. Journal of Experimental Botany. 58(9): 2369–2387.
  5. Hoogenboom, G., Jones, J.W., Wilkens, P.W., Porter, C.H., Boote, K.J., Hunt, L.A., et al (2012). Decision Support System for Agro technology Transfer (DSSAT) Version 4.5. University of Hawaii, Honolulu, Hawaii.
  6. Iqbal, M.A., Eitzinger, J., Formayer, H., Hassan, A. and Heng, L.K. (2011). A simulation study for assessing yield optimization and potential for water reduction for summer-sown maize under different climate change scenarios. Journal of Agricultural Science. 149:129-143.
  7. Jamieson, P.D., Porter, J.R. and Wilson, D.R. (1991). A test of computer simulation model ARC-WHEAT1 on wheat crops grown in New Zealand. Field Crops Research. 27: 337–350.
  8. Jones, J.W., Hoogenboom, G., Porter, C.H., Boote, K.J., Batchelor, W.D., Hunt, L.A., et al (2003). DSSAT Cropping System Model. European Journal of Agronomy. 18: 235 265.
  9. Thorp, K.R., DeJonge, K.C. and Kaleita, A.L. (2008). Methodology for the use of DSSAT models for precision agriculture decision support. Computers and Electronics in Agriculture. 64: 276–285.
  10. Timsina, J., Godwin, D., Humphreys, E., Singh, Y., Singh, B., Kukal, S.S. and Smith, D. (2008). Evaluation of options for increasing yield and water productivity of wheat in Punjab, India using the DSSAT-CSM-CERES Wheat model. Agricultural Water Management. 95:1099-1110.
  11. Willmott, C.J., Akleson, G.S., Davis, R.E., Feddema, J.J., Klink, K.M., et al (1985). Statistic for the evaluation and comparison of models. Journal of Geophysical Research. 90: 8995–9005.
  12. Yang, Y., Watanabe, W., Zhang, X., Zhang, J., Wang, Q. and Hayashi, S. (2006). Optimizing irrigation management for wheat to reduce groundwater depletion in the piedmont region of the Taihang Mountains in the North China Plain. Agricultural Water Management. 82: 225-44.
  13. Ziaei, A.N. and Sepaskhah, A.R. (2003). Model for simulation of winter wheat under dryland and irrigated conditions. Agricultural Water Management. 58: 1–17. 
Published In
Indian Journal of Agricultural Research
Article Metrics
Metrics Icon
0
Views
0
Citations
Reviewed By
Share Article
Download Article
In this Article
    Contact us
    Follow us

    Research Article

    volume 52 issue 4 (august 2018) : 392-397,   Doi: 10.18805/IJARe.A-4722

    Simulation of phenology, total nutrient uptake and grain yield of wheat under different irrigation and nitrogen application managements in Hisar, India using the DSSAT-CSM-CERES-Wheat model

    M
    Mukesh Kumar
    R
    R.K. Pannu
    B
    Bhagat Singh
    Cite article:- Kumar Mukesh, Pannu R.K., Singh Bhagat (2018). Simulation of phenology, total nutrient uptake and grain yield of wheat under different irrigation and nitrogen application managements in Hisar, India using the DSSAT-CSM-CERES-Wheat model. Indian Journal of Agricultural Research. 52(4): 392-397. doi: 10.18805/IJARe.A-4722.

    ABSTRACT

    The purpose of this study was the calibration and validation of DSSAT-CSM-CERES-Wheat model (v4.5) for wheat in Hisar conditions. The DSSAT-CSM-CERES-Wheat model was calibrated with the field experimental data of rabi 2010-11 having 3 levels of irrigation (I1-one irrigation at crown root initiation [CRI], I2- two irrigations at CRI and heading and I3- four irrigations at CRI, late tillering, heading and milking) and 5 nitrogen levels (0, 50, 100, 150 and 200 kg N/ha) and validated with data of experiment rabi 2011-12 conducted at Hisar (29°10’ N and 75°46’ E). The model performance was evaluated using average error (Bias), root mean square error (RMSE), normalized root mean square error (nRMSE), index of agreement (d-stat) and coefficient of determination (r2), and it was observed that DSSAT-CSM-CERES-Wheat model was able to predict the phenology, total nutrient uptake and grain yield of wheat with reasonably good accuracy. The simulated results were within the permissible limit of the error (error % less than ±15).

    REFERENCES

    1. Ambose, J.R. and Rosech, S.E. (1982). Dynamic estuary of model performance. ASCE Journal of Environmental Engineering. 108: 51-71 pp.
    2. Andarzian, B., Gerrit, H., Bannayan, M.,Shirali, M. and Andarzian, B. (2014). Determining optimum sowing date of wheat using CSM-CERES-Wheat model. Journal of the Saudi Society of Agricultural Sciences. 13: 15-26.
    3. Arora, V.K., Singh, H. and Singh, B. (2007). Analyzing wheat productivity responses to climatic, irrigation and fertilizer-nitrogen regimes in a semi-arid sub-tropical environment using the CERES-Wheat model. Agricultural Water Management. 94: 22-30.
    4. Hirel, B., Gouis, J., Ney, B. and Gallais, A. (2007). The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches. Journal of Experimental Botany. 58(9): 2369–2387.
    5. Hoogenboom, G., Jones, J.W., Wilkens, P.W., Porter, C.H., Boote, K.J., Hunt, L.A., et al (2012). Decision Support System for Agro technology Transfer (DSSAT) Version 4.5. University of Hawaii, Honolulu, Hawaii.
    6. Iqbal, M.A., Eitzinger, J., Formayer, H., Hassan, A. and Heng, L.K. (2011). A simulation study for assessing yield optimization and potential for water reduction for summer-sown maize under different climate change scenarios. Journal of Agricultural Science. 149:129-143.
    7. Jamieson, P.D., Porter, J.R. and Wilson, D.R. (1991). A test of computer simulation model ARC-WHEAT1 on wheat crops grown in New Zealand. Field Crops Research. 27: 337–350.
    8. Jones, J.W., Hoogenboom, G., Porter, C.H., Boote, K.J., Batchelor, W.D., Hunt, L.A., et al (2003). DSSAT Cropping System Model. European Journal of Agronomy. 18: 235 265.
    9. Thorp, K.R., DeJonge, K.C. and Kaleita, A.L. (2008). Methodology for the use of DSSAT models for precision agriculture decision support. Computers and Electronics in Agriculture. 64: 276–285.
    10. Timsina, J., Godwin, D., Humphreys, E., Singh, Y., Singh, B., Kukal, S.S. and Smith, D. (2008). Evaluation of options for increasing yield and water productivity of wheat in Punjab, India using the DSSAT-CSM-CERES Wheat model. Agricultural Water Management. 95:1099-1110.
    11. Willmott, C.J., Akleson, G.S., Davis, R.E., Feddema, J.J., Klink, K.M., et al (1985). Statistic for the evaluation and comparison of models. Journal of Geophysical Research. 90: 8995–9005.
    12. Yang, Y., Watanabe, W., Zhang, X., Zhang, J., Wang, Q. and Hayashi, S. (2006). Optimizing irrigation management for wheat to reduce groundwater depletion in the piedmont region of the Taihang Mountains in the North China Plain. Agricultural Water Management. 82: 225-44.
    13. Ziaei, A.N. and Sepaskhah, A.R. (2003). Model for simulation of winter wheat under dryland and irrigated conditions. Agricultural Water Management. 58: 1–17. 
    In this Article
      Contact us
      Follow us
      Published In
      Indian Journal of Agricultural Research

      Editorial Board

      View all (0)