پارامتریابی و ارزیابی مدل SSM_iCrop2 برای شبیه‌سازی رشد و عملکرد لوبیا (Phaseolus vulgaris L.) در ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه زراعت، دانشکده تولید گیاهی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

چکیده

به منظور مدل‌سازی مراحل رشد و عملکرد لوبیا با استفاده از آمار هواشناسی سطح کشور (دمای حداقل و حداکثر، مقدار تابش و میزان بارندگی) مطالعه‌ای در دانشگاه علوم کشاورزی و منابع طبیعی گرگان در سال 1395 صورت گرفت. هدف از این مطالعه پارامتریابی و ارزیابی مدل SSM_iCrop2 برای شبیه‌سازی رشد و عملکرد لوبیای معمولی به‌ منظور بررسی اثرات عوامل آب و هوایی، خاک، مدیریت زراعی و تعیین ضرایب ژنتیکی با استفاده از زیرمدل‌های مربوط به فنولوژی، تولید و توزیع ماده خشک، روابط آب و تغییرات سطح برگ در شرایط کشور بود. برای برآورد ضرایب و ارزیابی مدل از داده‌های آزمایش‌های انجام‌شده در نقاط مختلف کشور استفاده شد. ابتدا پارامترها برآورد و سپس مدل با استفاده از یک سری داده‌های مستقل، ارزیابی شد. مقایسه مقادیر شبیه‌­سازی‌‎شده و مشاهده‌‎شده روز تا رسیدگی در پارامتریابی با RMSE، CV و r به ترتیب برابر با 14 روز، 13 درصد و 76/0 و برای عملکرد دانه به ترتیب 62 گرم در متر مربع، 20درصد و 84/0 درستی پارامترهای مورد استفاده را نشان داد. همچنین مقادیر RMSE، CV و r در ارزیابی مدل برای روز تا رسیدگی به ترتیب برابر با 8 روز، 8 درصد و 74/0 و برای عملکرد دانه به ترتیب 53 گرم در متر مربع، 19 درصد و 77/0، دقت شبیه‌­سازی مدل را تأیید نمود. بنابراین، می‌توان از مدل SSM_iCrop2 به‌­عنوان ابزار مناسبی برای بررسی سیستم‌های زراعی و تفسیر نتایج در شرایط محیطی و مدیریتی متفاوت در جهت بهبود مدیریت مزارع لوبیا در کشور استفاده نمود.

کلیدواژه‌ها

موضوعات


  1. Aiking, H. 2011. Future protein supply. Trends in Food Science & Technology 22: 112-120.
  2. Amir, , and Sinclair, T.R. 1991. A model of water limitation on spring wheat growth and yield. Field Crops Research 28(1-2): 59-69.
  3. Assady, B., Dorri, H.R., and Ghadiri, A. Evaluation of chitti bean genotyps to drought stress using stress tolerance indices. Seed and Plant Improvement Journal 27-1(4): 615-630. (In Persian with English Summary).
  4. Beebe, S.E., Rao, I.M., Blair, M.W., and Acosta-Gallegos, J.A. 2013. Phenotyping common beans for adaptation to drought. Frontiers in Physiology 4:
  5. Dadrasi, A., Torabi, B., Rahimi, A., Soltani, A., and Zeinali, E. 2020. Parameterization and evaluation of a simple simulation model (SSM_iCrop2) for potato (Solanum tuberosum) growth and yield in Iran. Potato Research 63: 545-563.
  6. Ghanbari Motlaq, M., Rastgoo, M., Pouryousef, M., and Saba, J. 2012. The effect of sowing date and weed interference on growth indices of different red bean (Phaseolus vulgaris) cultivars. Journal of Plant Protection 25(4): 378-390. (In Persian with English Summary).
  7. Ghanbari, A.A. 2015. Developmental stages and phenology of common bean genotypes under normal irrigation and water deficit conditions. Agronomy Journal 28(107): 190-199. (In Persian with English Summary).
  8. Ghanbari, A.A., Mousavi, S.H., Keshavarz, S., and Abbasian, A. 2014. Assessment of variation in physiological growth indices in common bean genotypes under water deficit condition. Seed and Plant Production 30(2): 199-222. (In Persian with English Summary).
  9. Godfray, H.C.J., Beddington, J.R., Crute, I.R., Haddad, L., Lawrence, L., Muir, J.F., Pretty, J., Robinson, S., Thomas, S.M., and Toulmin, C. 2010. Food Security: the challenge of feeding 9 billion people. Science 327: 812-
  10. Hoogenboom, G., Jones, J.W., and Wilkens, P.W. 2004. Decision Support System for Agrotechnology Transfer Version 4.0. Honolulu, HI: Univ. Hawaii.
  11. Hydari, S., Sajedi, N.A., and Madani, M.J. 2015. The effects of integrated management on yield, yield components and weed control of bean. Iranian Journal of Pulses Research 6(2): 139-150. (In Persian with English Summary).
  12. Jamieson, P.D., Semenov, M.A., Brooking, I.R., and Francis, G.S. 1998. Sirius: a mechanistic model of wheat response to environmental variation. European Journal of Agronomy 8: 161-
  13. Jamshidi, M., Danesh-Shahraki, A., and Hashemi-Jazi, M. 2016. Effect of foliar application of manganese and zinc on grain yield and yield components of red bean (Phaseolus vulgaris) in drought conditions. Iranian Journal of Pulses Research 7(2): 164-174. (In Persian with English Summary).
  14. Karimzadeh, H., Nezami, A., Kafi, M., and Tadayon, M.R. 2017. Effects of deficit irrigation on yield and yield components of pinto bean genotypes in Shahrekord. Iranian Journal of Pulses Research 8(1): 113-126. (In Persian with English Summary).
  15. Koo, J., and Dimes, J. 2013. HC27 Generic Soil Profile Database. http://hdl.handle.net/1902.1/20299, Harvard Data verse, V4.
  16. Lobell, D.B., Cassman, K.G., and Field, C.B. 2009. Crop yield gaps: Their importance, magnitudes, and causes. Annual Review of Environment and Resources 34: 179-204.
  17. Majnoon Hosseini, N. 2008. Agriculture and Production of L Tehran University Jahad Publications. (In Persian)
  18. Marrou, H., Sinclair, T.R., and Metral, R. 2014. Assessment of irrigation scenarios to improve performances of Lingot bean (Phaseolus vulgaris) in southwest France. European Journal of Agronomy 59: 22-28.
  19. Mehrpouyan, M., Faramarzi, A., Jaefari, A., and Siyami, K. 2010. The effect of different methods and different dates of sowing on yield and yield components in two cultivars of common bean (Phaseolus vulgaris). Iranian Journal of Pulses Research 1(1): 9-17. (In Persian with English Summary).
  20. Mehrpoyan, M., and Shirani Rad, A.H. 2011. Comparing the biological nitrogen fixation efficiency, in native and non-native strains of Rhizobium leguminosarum; bv. phaseoli in common bean. Iranian Journal of Pulses Research 2(2): 109-120. (In Persian with English Summary).
  21. Ministry of Agriculture Jahad. 2016. Agricultural Statistics. [WWW Document], n.d. URL https://www.maj.ir/ (Accessed 6/29/20).
  22. Mirhashemi Aghdam, R.S., Tadyon, M.S., and Zade Bagheri, M. 2014. Evaluation of competitiveness of different bean cultivars and pigweed as affected by nitrogen. Plant Ecophysiology 5(15): 49-62. (In Persian with English Summary).
  23. Mohajerani, S.S., Alavi Fazel, M., Madani, H., Lack, S., and Modhej, A. 2016. Yield and physiological response of red bean genotypes (Phaseolus vulgaris) to cutting irrigation off at different growth stages. Journal of Crop Ecophysiology 10(1): 213-224. (In Persian with English Summary).
  24. Nehbandani, A., Soltani, A., Nourbakhsh, F., and Dadrasi, A. 2020. Estimating crop model parameters for simulating soybean production in Iran conditions. Oilseeds and Fats, Crops and Lipids 27:
  25. Nehbandani, A., Soltani, A., Zeinali, E., Raisi, S., and Rajabi, R. 2016. Parameterization and evaluation of SSM-soybean model for prediction of growth and yield of soybean in Gorgan. Journal of Plant Production Research 22(3): 1-26. (In Persian with English Summary).
  26. Noorhosseini, A., Soltani, A., and Ajamnoroozi, H. 2018. Simulating peanut (Arachis hypogaea) growth and yield with the use of the Simple Simulation Model (SSM). Computers and Electronics in Agriculture 145: 63-75.
  27. Omidi, F., and Sepehri, A. 2015. Effect of Sodium Nitroprusside application on leaf area, growth and water use efficiency of Kidney bean under water deficit stress. Journal of Crops Improvement 6(4): 871-885. (In Persian with English Summary).
  28. Parvizi, S., Amirnia, R., Bernosy, I., Paseban Islam, B., Hasanzadeh Gorttapeh, A., and Raeii, Y. 2011. Evaluation of different plant densities effects on rate and process of grain filling, yield and yield components in varieties of dry bean. Journal of Plant Production 18(1): 69-86. (In Persian with English Summary).
  29. Rahmani, T., Heidari Sharifabad, H., and Madani, H. 2012. Effect of planting date and comparing yield between red bean cultivars in Ali-Ggoudarz , Lorestan, Iran. New Finding in Agriculture 6(4): 321-335. (In Persian with English Summary).
  30. Rucell, G., Javis, P.G., and Monteith, J.L. 1989. Absorption of radiation by canopies and stand growth. 21-39 In: G. Russell, B. Marshall and P.G. Jarvis (Eds.). Plant Canopies: Their Growth, Form and Function. Cambridge University Press.
  31. Sadeghipour, O., Ghaffari Khaligh, H., and Monem, R. 2005. Effect of plant density on yield and yield components of common bean determinate and indeterminate cultivars. Journal of Agricultural Sciences 11(1): 149-160. (In Persian with English Summary).
  32. Sadeghipur, O., and Ghafarikhaligh, H. 2002. Effects of weeding and different herbicides on weed control in common bean (Phaseolus vulgaris). Iranian Journal of Crop Sciences 4(4): 277-282. (In Persian with English Summary).
  33. Safapour, M., Khaghani, Sh., and Teymoori, M. 2012. Comparison of drought tolerance index on morphological and agronomical traits in black bean (Phaseolus vulgaris). New Finding in Agriculture 6(4): 337-349. (In Persian with English Summary).
  34. Salehi, F. 2015. Principles of bean cultivation. Agricultural Education and Natural Resources Research Publications p. 2. (In Persian).
  35. Salehi, M., Akbari, R., and Khorshidi Benam, M.B. 2008. A study on response of yield and seed yield components of red bean (Phaseolus vulgaris) genotypes to delay in planting in Miyaneh region. Journal of Water and Soil Science 12(43): 105-115. (In Persian with English Summary).
  36. Sinclair, T.R. 2006. A reminder of the limitations in using Beer's law to estimate daily radiation interception by vegetation. Crop Science 46: 2343-2347.
  37. Sinclair, T.R., Kitani, S., Hinson, K., Bruniard, J., and Horie, T. 1991. Soybean flowering date: linear and logistic models based on temperature and photoperiod. Crop Science 31: 786-790.
  38. Sinclair, TR., Soltani, A., Marrou, H., Ghanem, M., and Vadez, V. 2020. Geospatial assessment for crop physiological and management improvements with examples using the simple simulation model. Crop Science 60: 700-
  39. Singh, S.P. 1999. Developments in plant breeding: Common Bean Improvement in the Twenty-First C Kluwer Academic Publishers, the Netherlands. 409 p.
  40. Soltani, A. 2009. Mathematical Modeling of the C Mashhad University Jahad Publications, p. 175. (In Persian)
  41. Soltani, A., and Hoogenboom, G. 2007. Assessing crop management options with crop simulation models based on generated weather data. Field Crops Research 103: 198-
  42. Soltani, A., and Sinclair, T. 2015. A comparison of four wheat models with respect to robustness and transparency: Simulation in a temperate, sub-humid environment. Field Crops Research 175: 37-
  43. Soltani, A., and Sinclair, T.R. 2012. Modeling Physiology of Crop Development, Growth and Y Cabi, P. 322.
  44. Soltani, A., Alimagham, M., Nehbandani, A., Zand, E., Bagheri, A.R., Rahimian, H., Fattah-Taleghani, D., and Ahmadi, K. 2016. Preparing a model for simulating the country's agricultural policy and evaluating food security with it by 2050. Agricultural Research Education and Extension Organization. (In Persian).
  45. Soltani, A., Alimagham, S., Nehbandani, A., Torabi, B., Zeinali, E., and Dadrasi, A. 2020a. SSM_iCrop2: A simple model for diverse crop species over large areas. Agricultural Systems 182: 102855.
  46. Soltani, A., Alimagham, S.M., Nehbandani, A., Torabi, B., Zeinali, E., Zand, E., Vadez, V., van Loon, M.P., and van Ittersum, M.K. 2020b. Future food self-sufficiency in Iran: A model-based analysis. Global Food Security 24: 100351.
  47. Soltani, A., Alimagham, S.M., Nehbandani, A., Torabi, B., Zeinali, E., Zand, E., Ghassemi, S., Vadez, V., Sinclair, T.R., and van Ittersum, M.K. 2020c. Modeling plant production at country level as affected by availability and productivity of land and water. Agricultural Systems 183: 102859.
  48. Soltani, A., and Sinclair, T.R. 2011. A simple model for chickpea development, growth and yield. Field Crops Research 124: 252-260.
  49. Soltani, A., Gholipoor, M., and Hajizadeh, H. 2005. SBEET: A simple model to simulate growthand yield of sugar beet. Agricultural Science and Technology 19: 11-26.
  50. Torabi, B., Ebrahimi, N., Soltani, A., and Zeinali, E. 2020. Parameterization and evaluation of SSM-iCrop model for prediction of growth and development of faba bean in climatic conditions of Gorgan. Journal of Crops Improvement 22(4): 531-542. (In Persian with English Summary).
  51. Van Ittersum, M.K., Cassman, K.G., Grassini, P., Wolf, J., Tittonell, P., and Hochman, Z. 2013. Yield gap analysis with local to global relevance. A R Field Crops Research 143: 4-17.
  52. Williams, J.R., Jones, C.A., Kiniry, J.R., and Spanel, D.A. 1989. The EPIC crop growth model. Transactions of ASAE 32: 497-510.
  53. Zhang, H., Tao, F., and Zhou, G. 2019. Potential yields, yield gaps, and optimal agronomic management practices for rice production systems in different regions of China. Agricultural Systems 171: 100-
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