بررسی کارایی مصرف آب ذرت (Zea mays L.) در اقلیم‌های گرم تحت شرایط تغییر اقلیم

نوع مقاله : علمی - پژوهشی

نویسندگان

گروه کشاورزی اکولوژیک، پژوهشکده علوم محیطی، دانشگاه شهید بهشتی، تهران، ایران.

چکیده

سابقه و هدف: کشور ایران در منطقه‎ای خشک و نیمه‎خشک قرار دارد که نسبت به تغییرات محیطی آسیب‎پذیر است. بنابراین به نظر می‎رسـد کـه وقـوع احتمـالی تغییرات اقلیمی در این منطقه تأثیر قابل‎توجهی در سیستم‎های تولید محصولات کشاورزی داشته باشد. تغییر اقلیم می­تواند بر آب قابل‌دسترس برای کشاورزی تأثیر گذاشته و منجر به خشک شدن محیط در مناطق نیمه‌خشک ایران گردد. بررسی راهکارهای سازگاری مانند تغییر تاریخ کاشت می­تواند به افزایش کارایی مصرف آب ذرت تحت شرایط تغییر اقلیم کمک کند. یکی از راه‎های کم هزینه برای اندازه‎گیری اثرات تغییر اقلیم بر محصولات کشاورزی رهیافت مدل‎سازی و استفاده از مدل‎های شبیه‎سازی است.مواد و روش‌ها: هدف از این پژوهش بررسی تاریخ کاشت­های مختلف به عنوان راهکاری برای سازگاری ذرت و بهبود کارایی مصرف آب این گیاه تحت شرایط تغییر اقلیم در استان خوزستان بود. برای این هدف شش شهرستان اهواز، بهبهان، دزفول، ایذه، رامهرمز و شوشتر در استان خوزستان انتخاب شدند. ابتدا داده­های اقلیمی بلند مدت روزانه (شامل دمای کمینه و بیشینه، بارندگی و تشعشع روزانه) دوره پایه (2009 -1980) این شهرستان­ها جمع­آوری شد. سپس با استفاده از روش AgMIP تحت دو سناریوی اقلیمی RCP4.5 و RCP8.5 داده­های اقلیمی دوره آینده (2069 -2040) این مناطق تولید شدند. در این تحقیق از رقم سینگل کراس 704 استفاده شد. تاریخ کاشت­ها شامل 15 بهمن، 1 اسفند (تاریخ کاشت مرسوم) و 15 اسفند بودند. با احتساب تاریخ کاشت­ها و مناطق مختلف (شش منطقه) و دو سناریوی اقلیمی در 30 سال، مجموعاً 1620 آزمایش شبیه­سازی در این تحقیق وجود داشت. به منظور شبیه­سازی رشد و عملکرد ذرت تحت تاریخ کاشت­های مختلف از مدل APSIM استفاده شد.نتایج و بحث: به طور کلی نتایج نشان داد که تاریخ کاشت زودهنگام 15 بهمن با 1/10117 کیلوگرم در هکتار عملکرد دانه اقتصادی در مقایسه با دو تاریخ کاشت 1 اسفند (3/10061 کیلوگرم در هکتار) و 15 اسفند (6/7194 کیلوگرم در هکتار) دارای کارکرد بالاتری بود. همچنین در دوره آینده احتمال درصد کاهش در مقدار عملکرد دانه اقتصادی تاریخ کاشت­های مختلف نسبت به تاریخ کاشت مرسوم در دوره پایه، نشان داد که درصد کاهش تاریخ کاشت زودهنگام 15بهمن (3/3- درصد و  5/4- به ترتیب تحت RCP4.5 و RCP8.5) در شرایط تغییر اقلیم در مقایسه با دو تاریخ کاشت دیگر (5/6- و  7/6- درصد به ترتیب تحت RCP4.5 و RCP8.5 برای تاریخ کاشت 1 اسفند و 1/31- و 2/23 درصد به ترتیب تحت RCP4.5 و RCP8.5 برای تاریخ کاشت 15 اسفند) در استان خوزستان بسیار کمتر می­باشد. به طور میانگین در سطح استان خوزستان تاریخ کاشت 15 بهمن (8/11 کیلوگرم عملکرد دانه بر میلیمتر آب) نسبت به دو  تاریخ کاشت 1 اسفند (7/10 کیلوگرم عملکرد دانه بر میلیمتر آب) و 15 اسفند (6/7 کیلوگرم عملکرد دانه بر میلیمتر آب) دارای کارایی مصرف آب بالاتری در دوره پایه بود. تحت شرایط تغییر اقلیم به طور کلی درصد کاهش در کارایی مصرف آب در تاریخ کاشت­های مختلف نسبت به تاریخ کاشت مرسوم در دوره پایه، نشان­دهنده برتری و اختلاف زیاد تاریخ کاشت زودهنگام 15بهمن (8/2 درصد و  3/3 به ترتیب تحت RCP4.5 و RCP8.5) در مقایسه با دو تاریخ کاشت دیگر (12- درصد و  11- به ترتیب تحت RCP4.5 و RCP8.5 برای تاریخ کاشت 1 اسفند و 1/40- و 5/32- درصد به ترتیب تحت RCP4.5 و RCP8.5 برای تاریخ کاشت 15 اسفند) در استان خوزستان بود.نتیجه­ گیری: به طور کلی نتایج این مطالعه نشان داد که تاریخ کاشت مرسوم منطقه مورد بررسی برای ذرت از نظر تولید عملکرد دانه اقتصادی و کارایی مصرف آب بهینه نیست. در نهایت نتایج نشان داد برای افزایش در عملکرد دانه اقتصادی و کارایی مصرف آب در دوره آینده و دوره پایه در استان خوزستان باید از تاریخ کاشت­های زود هنگام (15 بهمن) استفاده کرد. 

کلیدواژه‌ها


عنوان مقاله [English]

Investigating the maize (Zea mays L.) water use efficiency in hot areas under climate change conditions

نویسندگان [English]

  • Sajjad Rahimi Moghaddam
  • Jafar Kambouzia
  • Reza Deihimfard
Department of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University, G.C., Tehran, Iran
چکیده [English]

Introduction: Iran is located in an arid and semiarid region that is vulnerable to environmental changes. So, it would appear that the occurrence of climate change in this region would have a significant impact on agricultural production systems (Eyshi Rezaie and Bannayan, 2012). Climate change might affect the water available for agriculture and, consequently, lead to drought occurring in semiarid areas (Koocheki et al., 2006). Evaluating adaptation strategies, such as changing the planting of dates, can help to increase maize water use efficiency under climate change conditions (Ramprasad et al., 2016). One of the cheapest ways to measure the effects of climate change on agricultural production is through a modelling approach and application of simulation models (Manschadi et al., 2010). Materials and methods: This study aims at investigating the sowing date as a strategy for maize adaptation and improving its water use efficiency under climate change conditions in Khuzestan Province. For this purpose, six locations in Khuzestan Province were selected (Ahwaz, Behbahan, Dezful, Izeh, Ramhormoz and Shushtar). Daily long-term climatic data including minimum and maximum temperatures, rainfall and global radiation in a baseline period (1980-2010) were collected for these locations from their meteorological stations. Then, daily long-term climatic data were generated for the future period of 2040-2069 in these locations by using a method proposed by AgMIP under two climate scenarios (RCP4.5 and RCP8.5). In this study, the SC704 cultivar was used. Taking into account three sowing dates (4 February, 19 February [a common sowing date] and 5h March), six locations, and two climate scenarios over 30 years, a total of 1620 simulation experiments were carried out in this study. In order to simulate the growth and yield of maize under different sowing dates, the APSIM model was applied.Results and discussion: Results indicated that early sowing date (4 February) with 10117.1 kg ha-1 had a higher economical grain yield compared to 19 February (10061.3 kg ha-1 ) and 5 March (7194.6 kg ha-1 ). Also, in the future period, the reduction percentage in economical grain yield at the different sowing dates compared to the baseline common planting date (19 February) showed that the early sowing date of 4 February recorded less reduction (-3.3 and -4.5 percent under RCP4.5 and RCP8.5, respectively) than 19 February (-6.5 and -6.7 percent under RCP4.5 and RCP8.5, respectively) and 5st March (-31.1 and -23.2 percent under RCP4.5 and RCP8.5, respectively). On average in Khuzestan Province, an early sowing date indicated higher water use efficiency (WUE) )11.8 kg ha-1 mm-1 ) compared to 19 February (10.7 kg ha-1 mm-1 ) and 5 March (7.6 kg ha-1 mm-1 ) in the baseline period. However, under climate change conditions, reduction of WUE in different planting dates compared to the baseline common sowing date (19 February) revealed that 4 February (2.8 and 3.3 percent under RCP4.5 and RCP8.5, respectively) was superior compared with 19 February (-12 and -11 percent under RCP4.5 and RCP8.5, respectively) and 5 March (- 40.1 and -32.5 percent under RCP4.5 and RCP8.5, respectively) in term of WUE in Khuzestan Province. Conclusion: In general, according to the results found the common sowing date of maize in Khuzestan is not optimal for maize in terms of water use efficiency and economical grain yield. Accordingly, to increase economical grain yield and water use efficiency in both the future and baseline periods at Khuzestan Province, farmers should choose the early sowing date (4 February) compared to the common and late ones.

کلیدواژه‌ها [English]

  • huzestan
  • Sowing date
  • Adaptation
  • Grain yield
  1. AgMIP, 2013a. Guide for Running AgMIP Climate Scenario Generation Tools with Rin Windows. AgMIP, URL: http://www.agmip.org/wpcontent/uploads/2013/10/Guide-for-Running-AgMIPClimate-Scenario-Generation-with-R-v2.3.pdf
  2. AgMIP, 2013b. The Coordinated Climate-Crop Modeling Project C3MP: An Initiative of the Agricultural Model Intercomparison and Improvement Project. C3MP Protocols and Procedures. AgMIP, URL: http://research.agmip.org/ download/attachments/1998899/C3MP+Protocols+v2 .pdf
  3. Anonymous, 2014. Agricultural statistics. Iranian Ministry of Agriculture Jihad, Department of Planning and Economically, Center of Information and Communication Technology, first volume, 20132014, Iran. (In Persian). Available online at http://maj.ir/Portal/Home/Default.aspx?CategoryID= 95a8e7d0-e5f0-4f2d-a241-792106c74dcc
  4. Araya, A., Hoogenboom, G., Luedeling, E., Hadgu, K.M., Kisekka I. and Martorano, L.G., 2015. Assessment of maize growth and yield using crop
  5. models under present and future climate in southwestern Ethiopia. Agricultural and Forest Meteorology. 214, 252-265.
  6. Baguis, P., Roulin, E., Willems, P. and Ntegeka, V., 2010. Climate change scenarios for precipitation and crop evapotranspiration over central Belgium. Theoretical Applied Climatology. 99, 273–286.
  7. Bannayan, M., Mansoori, H. and Eyshi Rezaei, E., 2014. Estimating climatic Change, CO2 and technology development effects on wheat yield in northeast Iran. International Journal of Biometeorology. 58, 395-405.
  8. Dashtbozorgi, A., B. Alijani, Z. Jafarpur and A, Shakiba. 2015. Simulating Extreme Temperature Indicators Based on RCP Scenarios: The Case of Khuzestan Province. Geography and Environmental Hazards. 4, 105- 123. (In Persian with English Abstract).
  9. Deihimfard, R. and Rahimi Moghaddam, S., 2016. Assessing the yield of spring and autumn-sown sugar beet in Mashhad and Neyshabor, Khorasan using a simulation model. Electronic Journal of Crop
  10. Zea mays ( بررسی کارایی مصرف آب ذرت ... )در اقلیمهای گرم L.
  11. پاییز ،3 فصلنامه علوم محیطی، دوره چهاردهم، شماره 38
  12. Production. 3, 157- 180. (In Persian with English abstract).
  13. Eyni Nargeseh, H., Deihimfard, R., Soufizadeh, S., Haghighat, M. and Nouri O., 2016. Predicting the impacts of climate change on irrigated wheat yield in Fars province using APSIM model. Electronic Journal of Crop Production, 8, 203-224. (In Persian with English abstract).
  14. Eyshi Rezaei, E., Gaiser, T., Siebert, S. and Ewert, F., 2015. Adaptation of crop production to climate change by crop substitution. Mitigation and Adaptation Strategies for Global Change. 20, 1155-1174.
  15. Eyshi Rezaie, E. and Bannayan, M., 2012. Rainfed wheat yields under climate change in northeastern Iran. Meteorological Applications.19, 346– 354.
  16. Gohari, A., Eslamian, S., Abedi- Koupaei, J., Massah Bavani, A., Wang, D. and Madani, K., 2013. Climate change impacts on crop production in Iran's Zayandeh-Rud River Basin. Science of the Total Environmental. 442, 405-419.
  17. Hoogenboom, G., Jones, J.W., Porter, C.H., Wilkens, P.W., Boote, K.J., Batchelor, W.D., Hunt, L.A. and Tsuji, G.Y. (Editors). 2003. Decision Support System for Agrotechnology Transfer Version 4.0. Vol. 1: Overview. University of Hawaii, Honolulu, HI.
  18. Jones, P.G. and Thornton, P.K., 2003. The potential impacts of climate change on maize production in Africa and Latin America in 2055. Global Environmental Change 13, 51- 59.
  19. Kang, Y., Khan, S. and Ma, X., 2015. Analysing Climate Change Impacts on Water Productivity of Cropping Systems in the Murray Darling Basin, Australia. Irrigation and Drainage. 64, 443-453.
  20. Keating, B.A., Carberry, P.S., Hammer, G.L., Probert, M.E., Robertson, M.J., Holzworth, D., Huth, N.I., Hargreaves, J.N.G., Meinke, H., Hochman, Z., McLean, G., Verburg, K., Snow, V., Dimes, J.P., Silburn, M., Wang, E., Brown, S., Bristow, K.L., Asseng, S., Chapman, S., McCown, R.L., Freebairn D.M. and Smith, C. J., 2003. An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 18, 267– 288.
  21. Kirkegaard, J.A., Lilley, J.M., Howe, G.N. and Graham, J.M., 2007. Impact of subsoil water use on wheat yield. Crop and Pasture Science. 58, 303–315.
  22. Koocheki, A., Nassiri, M., Soltani, A., Sharif, H. and Ghorbani, R., 2006. Effects of climate change on growth criteria and yield of sunflower and chickpea
  23. crops in Iran. Climate Research. 30, 247-253.
  24. Lashkari, A., Alizadeh, A., Eyshi Rezaei, E. and Bannayan, M., 2012. Mitigation of climate change impacts on Maize productivity in northeast of Iran: a simulation study. Mitigation and Adaptation Strategies for Global Change. 17, 1-16.
  25. Li, X., Takahashi, T., Suzuki, N. and Kaiser, H.M., 2011. The impact of climate change on maize yields in the United States and China. Agricultural Systems. 104, 348–353.
  26. Lu, H.D., Xue, J.Q. and Guo, D.W., 2017. Efficacy of planting date adjustment as a cultivation strategy to cope with drought stress and increase rainfed maize yield and water-use efficiency. Agricultural Water Management. 179, 227-235.
  27. Lv Z., Lio X., Cao W. and Zhu, Y., 2013. Climate change impacts on regional winter wheat production in main wheat production regions of China. Agricultural of Forest Meteorology. 171-172, 234248.
  28. Manschadi, A.M., Soufizadeh, S. and Deihimfard. R., 2010. The role and importance of simulation modelling in improving crop production in Iran. In Proceedings in the 11th Iranian Crop Science Congress, 24th-26th July, Tehran, Iran. pp. 234-247. (Key paper).
  29. Mera, R.J., Niyogi, D., Buol, G.S., Wilkerson, G.G. and Semazzi, F.H.M., 2006. Potential individual versus simultaneous climate change effects on soybean (C3) and maize (C4) crops: An agrotechnology model based study. Global and Planetary Change. 54, 163–182.
  30. Mo, X., Liu, S., Lin, Z. and Guo R., 2009. Regional crop yield, water consumption and water use efficiency and their responses to climate change in the North China Plain. Agriculture Ecosystems Environment. 134, 67–78.
  31. Moradi, R., Koocheki, A., Nassiri Mahallati, M. and Mansoori, H., 2013. Adaptation strategies for maize cultivation under climate change in Iran: irrigation and planting date management. Mitigation and Adaptation Strategies for Global Change. 18, 265284.
  32. Prescott, J.A., 1940. Evaporation from a water surface in relation to solar radiation. Transactions of the Royal Society of South Australia. 64, 114-118.
  33. R Core Team, 2016. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL
  34. سجاد رحیمی مقدم و همکاران
  35. پاییز ،3 فصلنامه علوم محیطی، دوره چهاردهم، شماره 39
  36. https://www.R-project.org/.
  37. Rahimi Moghaddam, S., Kambouzia, J. and Deihimfard, R., 2017. Estimation of parameters for some dominant maize (Zea mays L.) cultivars of Iran for using in APSIM mechanistic model. Electronic Journal of Crop Production (In Press) (In Persian with English abstract).
  38. Ramprasad, C.H., Anil, G., Patil, A. and Sridhar, N., 2016. Technology approaches to increase the water use efficiency of maize under climate change: a review. International Journal of Applied Biology and Pharmaceutical Technology. 7, 43- 57.
  39. Reidsma, P., Ewert, F., Lansink, A.O. and Leemans, R., 2010. Adaptation to climate change and climate variability in European agriculture: the importance of farm level responses. European Journal of Agronomy. 32, 91–102.
  40. Ruane, A.C., Cecil, L.D. and Horton, R.M., 2013. Climate change impact uncertainties for maize in Panama: farm information, climate projections, and yield sensitivities. Agricultural and Forest Meteorology. 170, 132–145.
  41. Seifert, E., 2014. OriginPro 9.1: Scientific Data Analysis and Graphing Software—Software Review. Journal of Chemical Information and Modeling. 54, 1552–1552.
  42. Soler, C.M.T., Sentelhas, P.C. and Hoogenboom, G., 2007. Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment. European Journal of Agronomy. 27, 165-177.
  43. Stone, P., 2001. The effects of heat stress on cereal yield and quality. In: Basra, A.S. (Eds.), Crop Responses and Adaptations to Temperature Stress. Food Products Press, Binghamton, NY, USA, pp. 243–291.
  44. Wall, B.H. "TAMET". 1977: Computer program for processing meteorological data." CSIRO Australia. Division of Tropical Crops and Pastures. Tropical Agronomy Technical Memorandum, 4, 13p.
  45. Wilby, R.L., Charles, S.P., Zorita, E., Timbal, B., Whetton, P. and Mearns, L.O., 2004. Guidelines for use of climate scenarios developed from statistical downscaling methods. In: IPCC Task Group on Data and Scenario Support for Impacts and Climate Analysis.
  46. Yang, Y., Liu, D.L., Rajin Anwar, M., Leary, G., Macadam, I. and Yang, Y. 2016. Water use efficiency and crop water balance of rainfed wheat in a semi-arid environment: sensitivity of future changes to projected climate changes and soil type. Theoretical and Applied Climatology. 123, 565-579.
  47. Yano, T., Aydin, M. and Haraguchi, T., 2007. Impact of Climate Change on Irrigation Demand and Crop Growth in a Mediterranean Environment of Turkey. Sensors. 7, 2297-2315.