ارزیابی عملکرد مدل AquaCrop در شبیه‌سازی رشد گیاه ریحان تحت تنش‌های مختلف حاصلخیزی در شرایط کشت کنترل شده گلخانه

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران

2 هیات علمی،گروه مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران

3 هیات علمی، گروه باغبانی، دانشکده کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران

چکیده

بخش کشاورزی در فرآیند رشد و توسعه اقتصادی جوامع مختلف از اهمیت ویژه­ای برخوردار است. کاربرد کودهای نیتروژنی به عنوان یکی از مهم­ترین عوامل تولید و افزایش بهره­وری محصولات کشاورزی به­شمار می­آید. مدیریت و مصرف بهینه کود صرفاٌ بر اساس آزمایش­های مزرعه­ای یا گلخانه­ای زمان­بر و هزینه­بر است. لذا مدل­هایی که اثرات تنش­های مختلف حاصلخیزی بر تولید محصول را شبیه­سازی می­کنند، ابزارهایی مفید در برنامه­ریزی و بهینه­سازی مصرف کود هستند. در مدل AquaCrop میزان عملکرد محصول تحت تنش کودی توسط روش نیمه­کمی (Semi-quantitative) شبیه­سازی می­شود. هدف از این تحقیق، شبیه­سازی پاسخ گیاه به تیمارهای مختلف کوددهی و ارزیابی روش نیمه­کمی در مدل AquaCrop است. بدین منظور، گیاه ریحان در داخل گلخانه تحقیقاتی پردیس کشاورزی و منابع طبیعی دانشگاه تهران طی دو دوره کشت شد. بررسی اثر تنش حاصلخیزی در پنج سطح کاربرد کود نیتروژنی (کود اوره) و سه تکرار انجام شد. ابتدا روش نیمه­کمی مورد واسنجی قرار گرفت. نتایج واسنجی نشان داد، ضریب بهره­وری آب نرمال شده در اثر تنش حاصلخیزی به میزان 41 درصد کاهش یافت. سپس مدل AquaCrop در تخمین متغیرهای زیست­توده و پوشش گیاهی با استفاده از شاخص­های آماری صحت­سنجی شد. دامنه تغییرات به دست آمده برای شاخص­های R2، MBE و RRMSE برای متغیر زیست­توده گیاه به ترتیب برابر با 98/0-95/0، 56/21-72/1 گرم بر مترمربع، 07/19 -42/17 درصد و برای پوشش گیاهی به ترتیب برابر با 78/0-66/0، 86/12-44/6 درصد و 83/21-66/19 درصد بود. با توجه به نتایج، از مدل AquaCrop و روش نیمه­کمی می­توان به عنوان یک ابزار مناسب جهت شبیه­سازی رشد گیاه در شرایط تنش حاصلخیزی استفاده نمود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Performance Evaluation of AquaCrop Model in Simulating Basil (Ocimum basilicum L.) Growth under Different Soil Fertility Stress in Controlled Greenhouse Conditions

نویسندگان [English]

  • Hadisseh Rahimikhoob 1
  • Teymour Sohrabi 2
  • Mojtaba Delshad 3
1 Department of Irrigation & Reclamation Engineering Faculty of Agriculture Engineering &Technology College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran.
2 Professor, Irrigation and Reclamation Engineering Department, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
3 Associate Professor, Horticultural Sciences Department, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
چکیده [English]

The agricultural sector is particularly important in the economic growth and development of different societies. The application of Nitrogen fertilizer is one of the most influential factors in agricultural productivity enhancement. Management and optimum fertilizer consumption based on field or greenhouse experiments are time and cost consuming. Therefore, the application of models that simulate the effects of different fertility stresses on crop production are useful tools in fertilizer planning and optimization. In the AquaCrop model, the crop biomass is simulated using a semi-quantitative method. The purpose of this study was to simulate basil response to different fertilizer treatments and evaluate the semi-quantitative method used in the AquaCrop model. For this purpose, a study was carried out in a research greenhouse of the College of Agriculture and Natural Resources, University of Tehran, during two growth periods. Five levels of nitrogen fertilizer application (Urea fertilizer) with three replications was investigated to find out the effect of fertility stress on basil yield. Initially, the semi-quantitative method was calibrated. The calibration results showed that the normalized water productivity coefficient decreased by 41%. Then, the AquaCrop model was validated using statistical measures to estimate biomass and canopy cover. The variation range for R2, MBE and RRMSE indices for crop biomass were 0.95-0.98, 1.72-21.56 g m-2, 17/42-19.07% and for canopy cover were 0.66-0.78, 6.44-12.86% and 19.66-21.83%, respectively. According to the results, the AquaCrop model and the semi-quantitative method can be used as a suitable tool to simulate crop growth under soil fertility stress conditions.

کلیدواژه‌ها [English]

  • AquaCrop model
  • semi-quantitative method
  • Basil
Abi Saab, M.T., Todorovich, M., Albrizio, R. (2015). Comparing AquaCrop and CropSyst models in simulating barley growth and yield under different water and nitrogen regimes. Does calibration year influence the performance of crop growth models? Agric Water Manag. 147:21-33
Adler, P.R., Simon, J.E., Wilcox, G.E. (1989). Nitrogen form alters basil growth and essential oil content and composition. Hort Sci. 24: 789–790.
Akumaga, U., Tarhule, A. and Yusuf, A.A. (2017). Validation and testing of the FAO AquaCrop model under different levels of nitrogen fertilizer on rainfed maize in Nigeria, West Africa. Agricultural and Forest Meteorology. 232: 225–234.
Amiri, E., Rezaei, M., Eyshi Rezaei, E., Bannayan, M. (2014) Evaluation of Ceres-rice, AquaCrop and Oryza2000 models in simulation of rice yield response to different irrigation and nitrogen management strategies. J Plant Nutr 37:1749–1769.
Beven, K. A. (1979) Sensitivity analysis of the Penman-Monteith actual evapotranspiration estimates. J. Hydrol. 44: 169–190.
Boogard, H.L., C.A. van Diepen, R.P. Rotter, J.M.C.A. Cabrera, and H.H.van Laar. (1998). User’s guide for the WOFOST 7.1 crop growth simulation model and WOFOST Control Center 1.5.Tech. Doc.52. DLOWin and Staring Centre, Wageningen, the Netherlands.
De Wit, C.T. (1958). Transpiration and crop yields. Agric. Res. Rep. 64.6. PUDOC, Wageningen, the Netherlands.
FAO, 2017. The future of food and agriculture – Trends and challenges. Food and Agriculture Organization of the United Nations, Rome, Italy.
Geerts, S., Raes, D., Garcia, M., Miranda, R., Cusicanqui, J.A., Taboada, C., Mendoza, J., Huanca, R., Mamani, A., Condori, O., Mamani, J., Morales, B., Osco, V. and Steduto, P. (2009). Simulating yield response of quinoa to water availability with AquaCrop. Agron. J. 101:499–508.
Greaves, Geneille E., Wang and Yu-Min, (2016). Assessment of FAO AquaCrop model for simulating maize growth and productivity under deficit irrigation in a tropical environment. Water .8 (557). doi:10.3390/w8120557
Hsiao, T. C., Heng, L., Steduto, P., Rojas-lara, B., Raes, D. and Fereres, E. (2009). AquaCrop the FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal. 101(3): 448–459.
Jamieson, P. D., Porter, J. R. and Wilson, D. R. (1991). A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field Crops Research. 27(4): 337-350.
Jones, C.A., P.T. Dyke, J.R. Williams, J.R. Kiniry, C.A. Benson, and R.H. Griggs. (1991). EPIC: An operational model for evaluation of agricultural sustainability. Agric Syst. 37:341–350.
Muniandy, J.M., Yusop, Z. and Askari, M. (2016). Evaluation of reference evapotranspiration models and determination of crop coefficient for Momordica charantia and Capsicum annuum. Agric Water Manage. 169: 77–89.
Patrignani, A. and Ochsner, T.E. (2015). Canopeo: A Powerful New Tool for Measuring Fractional Green Canopy Cover. Agronomy Journal. 107(6): 2312-2320.
Raes, D., Steduto, P., Hsiao, T. C. and Fereres, E. (2012). AquaCrop Reference Manual, AquaCrop version 4.0. Rome, Italy: FAO.
Raes, D., Steduto, P., Hsiao, T. C. and Fereres, E. (2009). AquaCrop - the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agronomy Journal. 101(3): 438–447.
Ranjbar, A., Rahimikhoob, A. and Ebrahimian, H. (2017). Evaluating Semi-Quantitative Approach of the AquaCrop Model for Simulating Maize Response to Nitrogen Fertilizer. Iranian Journal of Irrigation and Drainage, 11(2), 286-298. (In Farsi)
Ritchie, J.T., D.C. Godwin, and S. Otter-Nacke. (1985). CERES-Wheat: A simulation model of wheat growth and development. Texas A&M Univ.Press, College Station.
Sandhu, R. and Irmak, S. (2019). Performance of AquaCrop Model in Simulating Maize Growth, Yield, and Evapotranspiration under Rainfed, Limited and Full Irrigation. Agricultural Water Management. 223. 10.1016/j.agwat.2019.105687.
Sifola, M.I. and Barbieri, G. (2006). Growth, yield and essential oil content of three cultivars of basil grown under different levels of nitrogen in the field. Sci. Hortic. 108, 408–413. doi:10.1016/j.scienta.2006.02.002
 Singh, K., Chand, S. and Yaseen, M. (2014). Integrated nutrient management in Indian basil (Ocimum basilicum). Ind. Crops Prod. 55: 225–229.
Steduto, P., Hsiao, T. C., Raes, D. and Fereres, E. (2009). AquaCrop: The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agronomy Journal. 101(3): 426-437.
Todorovic,M., Albrizio, R., Zivotic, L., Abi Saab, M., Stwckle, C. and Steduto, P. (2009). Assessment of AquaCrop, CropSyst, and WOFOST models in the simulation of sunflower growth under different water regimes. Agron.J. 101: 509–521.
Van Gaelen, H., Tsegay, A., Delbecque, N., Shrestha, N., Garcia, M., Fajardo, H., Miranda, R., Vanuytrecht, E., Abrha, B., Diels, J. and Raes, D. (2015). A semi-quantitative approach for modelling crop response to soil fertility: evaluation of the Aquacrop procedure. Journal of Agricultural Science. 153(7): 1218-1233.
Vanuytrecht, E., Raes, D. and Willems, P. (2014). Global sensitivity analysis of yield output from the water productivity model. Environ Model Softw. 51: 232-332.
Zeinali, E., Soltani, A., Galeshi, S. and Movahedi Naeeni, S.A. (2012). Evaluating Nitrogen Nutrition Index of Wheat (Triticum aestivum L.) Fields in Gorgan. J. of Plant Production. 19(4). (In farsi).