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Calibration and Evaluation of the IXIM Model for Simulation of Growth and Yield of Maize (SC 704) in Gorgan Climatical Conditions | ||
| به زراعی نهال و بذر | ||
| Article 4, Volume 33, Issue 2, February 2018, Pages 203-230 PDF (478.47 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/sppj.2018.116417 | ||
| Authors | ||
| M. T. Feyzbaksh* 1; B. Kamkar2; H. Mokhtarpour1; M. E. Asadi3 | ||
| 1Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran. | ||
| 2, Department of Agronomy, Gorgan University of Agricultural Science and Natural Resources, Gorgan, Iran. | ||
| 3Agricultural Engineering Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran. | ||
| Abstract | ||
| The use of modeling in research and farm management is developing every day. IXIM is a new model and its evaluation has begun by researchers around the world. For calibration and validation of the IXIM model, two experiments (each in two years) were carried out at Agricultural Research Station of Gorgan, Golestan province . The model was calibrated using optimum irrigation treatments along with no stress of drought condition in 2012 and two treatments of the second experiment in 2007. The Evaluation of the model was done using planting date treatments of spring experiment (2008), planting date and deficit irrigation of experiments in 2012 and 2013. The evaluation results of the model indicated that the model simulated phenological stages (anthesis and maturity occurrence) with high accuracy at different sowing dates and different irrigation regimes. The highest root mean square error for anthesis belonged to 6 July with 2.24 days, therefore, this model could be used in the field programing management. Evaluation results in spring sowing (2008) and summer sowing dates (2012 and 2013) revealed that the model simulated dry matter and yield of maize with a high accuracy. Also, the model simulated reduction of dry matter and seed yield in different levels of irrigation (except for full stress) and had enough accuracy base on model’s statistical indices. The model had not enough accuracy in simulation of leaf area index (LAI) and evapotransopiration in irrigation treatments. Referring to results of this experiment, this model could be used in Gorgan climatic conditions to simulate growing stages, dry matter and grain yield of maize (SC704) in different sowing dates and different irrigation regimes. | ||
| Keywords | ||
| Maize; modeling; sowing date; low irrigation; Grain yield | ||
| References | ||
|
Alizadeh, O., Majede, E., Nadian, H. A., Normohamade, Gh., and Amerian, M. R. 2008. Effect of water stress and different nitrogen rates on phenology, growth and development of corn. Bimonthly Journal of Agricultural Sciences and Resources 14: 101-115 (in Persian).
Andarzian, B., Bakhshandeh, A. M., Bannayan, M., and Emam, Y. 2007. Evaluation of the CERES-wheat model in Ahvaz condition. Iranian Journal of Field Crops Research 6: 11-22 (in Persian).
Anonymous 1989. SAS/STAT User’s Guide, Release 6.09. SAS Inst., Inc., Cary, NC. Anonymous 2010. Decision Support System for Agrotechnology Transfer (DSSAT) [Online] http://www.icasa.net/dssat/index.html (cited 2014 Oct. 2).
Bannayan, M., Hoogenboom, G., and Crout, N. M. J. 2004. Photothermal impact on maize performance: a simulation approach. Ecological Modelling 180: 277-290.
Boedhram, N. 1998. Seasonal changes of leaf area distribution and light response curves, and incorporation of vapor pressure deficit into a canopy photosynthesis model in corn. Publication of University of Nebraska, Lincoln, USA.
DeJonge, K. 2011. Evaluation and improvement of CERES-Maize Evapotranspiration simulations under full and limited irrigation treatments in northern Colorado. Ph.D. Thesis, Department of Civil and Environmental Engineering, Colorado State University, Colorado, USA.
Dogan, E., Clark, G. A., Rogers, D. H., Martin, V., and Vanderlip, R. L. 2006. On-farm scheduling studies and CERES-Maize simulation of irrigated corn. Applied Engineering in Agriculture 22(4): 509-516.
Dokoohaki, H., Gheysari, M., Mousavi, S. F., and Mirlatifi, S. M. 2012. Estimation soil water content under deficit irrigation by using DSSAT. Agricultural Water Management 2: 1-14.
Eck, H.V. 1984. Irrigated corn yield response to nitrogen and water. Agronomy Journal 76: 421-428.
Faria, R. T. D., and Bowen, W. T. 2003. Evaluation of DSSAT soil-water balance module under cropped and bare soil conditions. Brazilian Archives of Biology and Tecnology 46: 489-498.
Gheysari, M., Mirlatifi, S. M., Homaee, M., Asadi, M. E., and Hogenboom, G. 2009. Nitrate leaching in a silage maize field under different irrigation and nitrogen fertilizer rates, Agricultural Water Managment 96: 964- 954.
Gungula, D. T., Kling, J. G., and Togun, A. O. 2003. CERES-Maize predictions of maize phenology under nitrogen-stressed condition in nigeria. Agronomy Journal 95: 892-899.
Hoogenboom, G., A. Jintrawet., and Wilkens, P. W. 2009. A training program on DSSAT version 4.5: Assessing crop production, nutrient management, climatic risk and environmental sustainability with simulation models., In N. U. O. Malaysia, (ed.), March 30 -April 10. Bangi, Selangor, Malaysia.
Hoogenboom, G., J. W. Jones, C. H. Porter, P. W. Wilkens, K. J. Boote, W. D. Batchelor, L. A. Hunt, and Tsuji, G. Y. 2003. Decision Support System for Agrotechnology Transfer Version 4.0. Vol. 1. University of Hawaii, Honolulu, HI, USA.
Irmak, A., Jones, J. W., Mavromatis, T., Welch, S. M., Boote, K. J., and Wilkerson, G.G. 2000. Evaluating methods for simulating soybean cultivar responses using cross validation. Agronomy Journal 92: 1140-1149.
Jamieson, P., Porter, J., and Wilson, D. 1991. A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crops Research 27: 337-350.
Jibrin, M., Jibrin, A., Kamara, Y., and Friday, E. 2012. Simulating planting date and cultivar effects on dryland maize production using CERES-maize model. African Journal of Agricultural Research 7(40): 5530-5536.
Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J., and Ritchie, J. T. 2003. The DSSAT cropping system model. European Journal of Agronomy 18: 235–265.
Kamkar, B., Koochki, A. R., Mahallati, M. N., and Razvani- Moghaddam, P. R. 2006. Yield gap analysis of cumin in nine regions of Khorasan provinces using modelling approach. Iranian Journal of Field Crops Research 2(2): 196-208 (in Persian).
Kamkar, B., Koocheki, A. R., Mahallati, M. N., and Razvani- Moghaddam, P. R. 2008. Construction and primary evaluation of a simple model to predict potential dry matter production in pearl millet. Electronic Journal of Crop Production 3: 99-116 (in Persian).
Khaliq, T., 2008. Modeiling the impact of climate change on (Zea mays L.) productivity in the Panjab. Ph.D. Thesis, University of Agriculture, Faisalabad, Pakistan.197 pp.
Lizaso, J., Batchelor, W., and Adams, S. 2001. Alternate approach to improve kernel number calculation in CERES-Maize. Transactions of the ASAE. 44: 1011-1018.
Lizaso, J., Batchelor, W., Boote, K., and Westgate, M. 2005a. Development of a leaf-level canopy assimilation model for CERES-Maize. Agronomy Journal 97: 722-733.
Lizaso, J., Batchelor, W., Boote, K., Westgate, M., Rochette, P., and Moreno-Sotomayor, M. 2005b. Evaluating a leaf-level canopy assimilation model linked to CERES-Maize. Agronomy Journal 97: 734-740.
Lizaso, J., Batchelor, W., and Westgate, M. 2003a. A leaf area model to simulate cultivar-specific expansion and senescence of maize leaves. Field Crops Research 80: 1-17.
Lizaso, J., Westgate, M., Batchelor, W., and Fonseca, A. 2003b. Predicting potential kernel set in maize from simple flowering characteristics. Crop Science 43: 892. 1005.
Lizaso, J., Boote, K. J., Jones, J. W., and Porter, C. H. 2008. IXIM: A new maize simulation model for DSSAT v4. 5. 10th Congreso de la Sociedad Europea de Agronomia, 15-19 Sep., Bolonia, Italia.
Loague, K., and Green, R. E. 1991. Statistical and graphical methods for evaluating solute transport models: Overview and application. Contaminant Hydrology Journal 7: 51-73.
Loomis, R., and Amthor, J. 1999. Yield potential, plant assimilatory capacity, and metabolic efficiencies. Crop Science 39: 1584-1596.
Mahru- Kashani, A. H., Soltani, A., Galeshi, S., and Kalate-Arabi, M. 2010. Estimates of genetic coefficients and evaluation of model DSSAT for Golestan province. Electronic Journal of Crop Production 3 (2): 229-253 (in Persian).
Mavromatis, T., Boote, K. J., Jones, J. W., Wilkerson, G. G., and Hoogenboom, G. 2002. Repeatability of model genetic coefficients derived from soybean performance trials across different states. Crop Science 42: 76–89.
Mokhtarpour, H. 2011. Impact of planting date and density on growth of maize in northeren Iran. Ph.D. Thesis, University of Putra, Putra, Malysia.
Nielsen, D. C., Ma, L., Ahuja, L. R., and Hoogenboom, G. 2002. Simulating soybean water stress effects with RZWQM and CROPGRO models. Agronomy Journal 94: 1234-1243.
Rochette, P., Desjardins, R. L., Pattey, E., and Lessard, R. 1996. Instantaneous measurement of radiation and water use efficiencies of a maize crop. Agronomy Journal 88: 627-635.
Saseendran, S. A., Ma, L., Nielsen, D. C., Vigil, M. F., and Ahuja, L. R. 2005. Simulating planting date effects on corn production using RZWQM and CERES-Maize models. Agronomy Journal 97: 58-71.
Sohrabi, B., and Ghorbani, N. 2002. The effect of soil moisture allowed depletion on cotton yield in Gorgan. Bimonthly Journal of Agricultural Sciences and Natural Resources 9: 100-108 (in Persian).
Soltani, A. 2007. Application of SAS in Statistical Analysis. JDM Press, Mashhad, Iran.182pp. (in Persian).
Soltani, A. 2008. Mathematical Modeling in Field Crops. Ferdowsi University Press. Mashhad, Iran. 175 pp. (in Persian).
Soltani, A., Robertson, M. J., Mohammad-Nejad, Y., and Rahemi-Karizaki, A. 2008. Modeling leaf production and senescence in chickpea. In: International Meeting on Soil Fertility and Management and Agroclimatology. pp. 655-674.
Turkey. Tollenaar, M., and Hunter, R. 1983. A photoperiod and temperature sensitive period for leaf number of maize. Crop Scince 23: 457-460.
Westgate, M.E., Forcella, F., Reicosky, D.C., and Somsen, J. 1997. Rapid canopy closure for maize production in the northern US Corn Belt: Radiation-use efficiency and grain yield. Field Crops Research 49: 249-258.
Willmott, C. J. 1982. Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society 63: 1309-1313.
Yazar, A., Sezen, S. M., and Gencel, B., 2002. Drip irrigation of corn in the Southeast Anatolia Project (GAP) area in Turkey. Irrigation and Drainge 51: 293-300.
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