به زراعی کشاورزی

شماره جاری

بر اساس شماره‌های نشریه

بر اساس نویسندگان

بر اساس موضوعات

نمایه نویسندگان

نمایه کلیدواژه ها

درباره نشریه

اهداف و چشم انداز

اعضای هیات تحریریه

اصول اخلاقی انتشار مقاله

بانک ها و نمایه نامه ها

پیوندهای مفید

پرسش‌های متداول

فرایند پذیرش مقالات

اطلاعات آماری نشریه

اخبار و اعلانات

داوران

عضویت و راهنمای پابلونز

دستورالعمل حذف نام داور از روی کامنت ها در برنامه Word

بررسی ضرایب ژنتیکی ارقام برنج برای کاربرد در مدل های شبیه سازی گیاه زراعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 نویسنده مسئول، بخش اصلاح و تهیه بذر، مؤسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران. رایانامه: shahram_nazari1986@yahoo.com

2 بخش اصلاح و تهیه بذر، مؤسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران. رایانامه: m.hosseini@areeo.ac.ir

3 گروه زراعت و اصلاح نباتات، دانشکده کشاورزی، دانشگاه لرستان، خرم‌آباد، ایران. رایانامه: rahimi.s@lu.ac.ir

4 مؤسسه تحقیقات برنج کشور، رشت، ایران. رایانامه: m.mohammadi57@areeo.ac.ir

چکیده

به‌منظور تعیین تفاوت­های فنولوژی برخی ارقام اصلاح­شده برنج برای کاربرد در مدل­های شبیه­سازی گیاه زراعی، آزمایشی در مزرعه پژوهشی مؤسسه تحقیقات برنج کشور (رشت) در سال 1399 به­صورت بلوک­های کامل تصادفی با سه تکرار اجرا شد. تیمار آزمایش شامل شش رقم برنج (رش، آنام، گوهر، SA1، SA6 و M7) بود. نتایج نشان داد که بالاترین سرعت نمو در مرحله رشد رویشی و مرحله پرشدن دانه در رقم آنام مشاهده شد. کم‌ترین و بیش‌ترین زمان لازم جهت شروع سبزشدن با سه و شش روز به­ترتیب در ارقام آنام و گوهر بود. بیش‌ترین مدت زمان لازم جهت دست­یابی به حداکثر گل‌دهی و رسیدگی فیزیولوژیکی با 71 و 103 روز در رقم گوهر به­دست آمد. بالاترین طول دوره گل‌دهی با 19 و 20 روز به­ترتیب در ارقام دیررس رش و گوهر به­دست آمد. بیش‌ترین درجه روز رشد از شروع پرشدن دانه تا رسیدگی فیزیولوژیکی با 401 درجه روز رشد مربوط به رقم M7 مشاهده شد. بیش‌ترین زمان دمایی تجمعی پیش از گل­دهی با 1208 درجه روز رشد به­ترتیب متعلق به رقم گوهر بود. بالاترین شاخص برداشت با 91/50 درصد در رقم گوهر به­دست آمد. هم‌چنین نتایج نشان داد که بیش‌ترین وزن تک‌دانه تحت شرایط ایده­آل با 030/0 گرم در ارقام گوهر و M7 مشاهده شد. نتایج به‌دست‌آمده نشان داد که بالاترین ارتفاع بوته مربوط به رقم M7  با 150 سانتی­متر بود. نتایج نشان داد بالاترین نیتروژن کل جذب‌شده در بوته در زمان رسیدگی مربوط به رقم آنام مشاهده شد. به­طورکلی نتایج نشان­ داد که ضرایب ژنتیکی محاسبه‌شده در مدل­های مختلف در بین ارقام متفاوت است و ضرایب در دامنه­ای که در مدل برای گروه­های مختلف رسیدگی تعریف شده است، تغییر می­کنند. هم‌چنین برای محاسبه دقیق ضرایب ژنتیکی پیشنهاد می­شود این آزمایش در تعداد سال بیش‌تر و اکوسیستم­های مختلف تحت کشت برنج نیز تکرار شود.

کلیدواژه‌ها

عنوان مقاله [English]

Investigation of genetic coefficients of rice cultivars for applying in crop simulation models

نویسندگان [English]

  • Shahram Nazari 1
  • maryam hossieni 2
  • Sajjad Rahimi-Moghaddam 3
  • Mohammad Mohammadi 4

1 Corresponding Author, Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran. E-mail: sh.nazari@areeo.ac.ir

2 Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran. E-mail: m.hosseini@areeo.ac.ir

3 Department of Agronomy and Plant Breeding, Faculty of Agriculture, Lorestan University, Khorramabad, Iran. E-mail: rahimi.s@lu.ac.ir

4 Rice Research Institute of Iran, Rasht, Iran. E-mail: m.mohammadi57@areeo.ac.ir

چکیده [English]

In order to determine the phenological differences of some improved rice cultivars in Iran for applying in crop simulation models, an experiment has been conducted in the research farm of the Rice Research Institute of Iran (Rasht) in 2020 as a randomized complete block with three replications. The experimental treatment consist of six rice cultivars (Rash, Anam, Gohar, SA1, SA6 and M7). Results show that the highest development rate can be observed in development rate in juvenile phase and grain filling phase in Anam cultivar. The minimum and maximum time required to start emergence with 3 and 6 days are in Anam and Gohar cultivars, respectively. The maximum time required to achieve maximum flowering and physiological maturity is obtained with 71 and 103 days in Gohar cultivar. The highest flowering period with 19 and 20 days is obtained in late maturing Rash and Gohar cultivars, respectively. The highest growth degree days (GDD) in beginning of grain filling to maturity stage is observed with 401 GDD for M7 cultivar. The highest growth-day for pre-flowering with 1208 GDD belongs to Gohar cultivar. The highest harvest index is obtained with 50.91% in Gohar cultivar. The results also show that the single grain weight under ideal growing conditions with 0.030 g is observed in Gohar and M7 cultivars. The highest plant height belongs to cultivar M7 with 150 cm and the highest total nitrogen uptake is observed in the plant at maturity of Anam cultivar. Overall, the estimated genetic coefficients in different models differ between cultivars and the coefficients vary in the range defined in the model for different groups of maturity. To accurately calculate the genetic coefficients, it is suggested that this experiment should be repeated over several years and in different ecosystems under rice cultivation.

کلیدواژه‌ها [English]

  • Flowering؛ Growth Degree Days؛ Harvest index
  • ؛ Plant height؛ Single grain weight
مراجع
Aggarwal, P.K., & Mall, R.K. (2002). Climate change and rice yields in diverse agro-environments of India. II. Effect of uncertainties in sce- narios and crop models on impact assessment. Climati Change, 52, 331-343.
Amarasingha, R.P.R.K., Suriyagoda, L.D.B., Marambe, B., Gaydon, D.S., Galagedra, L.W., Punyaqardena, R., Silva, G.L.L.P., Nidumold, U., & Howden, M. (2015). Simulation of crop and water productivity for rice (Oryza sativa L.) using APSIM under diverse agro-climatic conditions and water management techniques in Sri Lanka. Agricultural Water Management, 160, 132-143.
Amiri Larijani, B. (2011). Ecological and phenological simulation of rice cultivars with ORYZA2000 model related to growth, development and yield. Ph.D. Thesis in Agronomy. Faculty of Agriculture, Tarbiat Modares University, Iran, 191p. (In Persian).
Anurag, S., & Shruti, S. (2019). Calibration and validation of DSSAT model (v. 4.7) for rice in Prayagraj. Journal of Pharmacognosy and Phytochemistry, 8(4), 2916-2919.
Bakhshipour, S., Kambouzia, J., Khoshbakht, K., Mahdavi Damghani, A.M., & Hosseini Chaleshtori, M. (2017). Identification of effective morphological traits on rice cultivars yield under moisture stress condition using multivariate statistical methods. Environmental Science, 15(2), 163-180. (In Persian with English abstract).
 Bouman, B.A.M., Kropff, M.J., Tuong, T.P., Wopereis, M.C.S., ten Berge, H.F.M., & Laar, H.H. (2001). ORYZA2000: Modeling Lowland Rice. International Rice Research Institute, and Wageningen University and Research Centre, Los Baños, Philippines, Wageningen, The Netherlands.
Challinor, A.J., Wheeler, T.R., Craufurd, P.Q., & Grimes, D.I.F. (2004). Design and optimization of a large-area process-based model for annual crops. Agricultural and Forest Meteorology, 124, 99-120.
Dias, M.P.N.M., Navaratne, C.M., Weerasinghe, K.D.N., & Hettiarachchi, R.H.A.N. (2016). Application of DSSAT crop simulation model to identify the changes of rice growth and yield in Nilwala river basin for midcenturies under changing climatic conditions. Procedia Food Science, 6, 159-163.
Ding, J., Hou, G.G., Dong, M., Xiong, S., Zhao, S., & Feng, H. (2018). Physicochemical properties of germinated dehulled rice flour and energy requirement in germination as affected by ultrasound treatment. Ultrasonics Sonochemistry, 41, 484-491.
Ehdaie, B., Alloush, G., & Waines, J.G. (2006). Genotypic variation for stem reserves and mobilization in wheat. Crop Science, 46, 735-746.
Erfani, R., Sattari, M., Mohaddesi, A., Tavasoli, F., Rahim Sourosh, H., Saeedi, M., Yousefi, M.M., Fathi, N., Abadian, H., & Abbasian, A. (2020). Determination of the proper transplanting datebased on GDD and the best plant density in promising line of rice 926 (Tisa). Applied Research in Field Crops, 33(1), 1-21. (In Persian with English abstract).
Food and Agriculture Organization Corporate Statistical Database (FAOSTAT). (2019). Food and Agriculture Organization of the United Nations Database; Food and Agriculture Organization (FAO), Rome. Available online: http://www.fao.org.
Hasan, M.M., & Rahman, M. (2019). Simulating climate change impacts on T. aman (BR-22) rice yield: a predictive approach using DSSAT model. Water and Environment Journal, 34, 1-13.
Islam, M.R., & Sikder, S. (2011). Phenology and degree days of rice cultivars under organic culture. Bangladesh Journal of Botnay, 40(2), 149-153.
Khanal, R. R. (2005). Phyllochron and leaf development in field grown rice genotypes under varying thermal environments of a high altitude cropping system. MSc. Thesis. University of Zu Bonn. Germany.
Li, S., Fleisher, D., Timlin, D., Reddy, V.R., Wang, Z., & McClung, A. (2020). Evaluation of different crop models for simulations rice development and yield in the U.S. Mississippi delta. Agronomy, 10, 1-21.
Liu, J., Liu, Z., Zhu, A.X., Shen, F., Lei, Q., & Duan, Z. (2019). Global sensitivity analysis of the APSIM-Oryza rice growth model under different environmental conditions. Science of The Total Environment, 651(1), 953-968.
Mohammadi, H., Rabbani, F., & Mazaheri, D. (2015). Simulation of the effect of climate change on rice plant phenology under different irrigation managements in the Caspian region: Rasht station. Journal of Applied researches in Geographical Sciences, 15(38), 187-206. (In Persian with English abstract).
Nadimi Dafrazi, M.H., Esfahani, M., & Aalami, A. (2018). Effect of transplanting time on grain yield, yield components and remobilization of three rice varieties in Roudbar region. Cereal Research, 7(4), 471-483. (In Persian with English abstract).
Nawaz, A., Farooq, M., Ahmad, R., Basra, S.M.A., & Lal, R. (2016). Seed priming improves stand establishment and productivity of no till wheat grown after direct seeded aerobic and transplanted flooded rice. European Journal of Agronomy, 76, 130-137.
Nezamzadeh, S.E., Pirdashti, H., & Babaeian Jelodar, N. (2010). Comparison of grain filling rate and duration among some old, modern and promising rice cultivars under different nitrogen levels. Electronic Journal of Crop Production, 4(3), 79-101. (In Persian with English abstract).
Nissanka, S.P., Karunaratne, A.S., Perera, R., Weerakoon, W.M.W., Thorburn, P.J., & Wallach, D. (2015). Calibration of the phenology sub-model of APSIM-Oryza: Going beyond goodness of fit. Environmental Modelling & Software, 70, 128-137.
Paoli, E., Welch, S.M., & Vanderlip, R.L. (2000). Comparing genetic coefficient estimation methods using the CERES-Maize model. Agricultural Systems, 65, 29-41.
Pirdashti, H., Tahmasebi Sarvestani, Z., & Nasiri, M. (2003). Study on dry matter and nitrogen remobilization in rice (Oryza sativa L.) genotypes under different transplanting dates. Iranian Journal of Crop Sciences, 5, 46-55. (In Persian with English abstract).
Pourgholam-Amiji, M., Liaghat, A.M., & Khoshravesh, M. (2020). Evaluation of AquaCrop model for estimating rice yield under alternative irrigation. International Water and Irrigation, 11(1), 305-320. (In Persian with English abstract).
Rahimi Moghadam, S., Deihimfard, R., Soufizadeh, S., Kambouzia, J., Nazariyan Firuzabadi, F., & Eyni Nargeseh, H. (2015). Determination of genetic coefficients of some maize cultivars of Iran for application in crop simulation models. Field Crop Research, 13(2), 328-339. (In Persian with English abstract).
Rahman, A., Mojid, M.A., & Banu, S. (2018). Climate change impact assessment on three major crops in the north-central region of Bangladesh using DSSAT. International Journal of Agricultural and Biological Engineering, 11(4), 135-143.
Rani, B.A., & Maragatham, N. (2013). Effect of elevated temperature on rice phenology and yield. Indian Journal of Science and Technology, 6(8), 5095-5097.
Rehman, H.U., Kamran, M., Basra, S.M.B., Afzal, I., & Farooq, M. (2015). Influence of seed priming on performance and water productivity of direct seeded rice in alternating wetting and drying. Rice Science, 22(4), 189-196.
Saeidzadeh, F., Taghizadeh, R., & Molazem, D. (2010). Effect of plant density on yield and yield components of rice (Oryza sativa L.) in climatic of the west part of Guilan province,Iran. Agroecology Journal, 6(1), 37-46. (In Persian with English abstract).
Seyed Raoufi, R., Soufizadeh, S., Amiri Lariani, B., AghaAlikhani, M., & Kamouzia, J. (2017). Simulation of growth and yield of various irrigatedrice (Oryza sativa L.) genotypes by AquaCrop under different seedling ages. Natural Resource Modeling, 31(4), 1-23.
Singh, P.K., Singh, K.K., Bhan, S.C., Baxla, A.K., Singh, S., Rathore, L.S., & Gupta, A. (2017). Impact of projected climate change on rice yield using CERSR-rice model in different agroclimatic zones of India. Current Science, 112(1), 108-115.
Singh, S.P., Mishra, S.R., Jena, A.K., Deuri, R., & Sharma, P. (2018). Evaluation of DSSAT model of rice genotypes under different weather conditions. The Pharma Innovation Journal, 7(10), 516-518.
Swain, D.K., & Yadav, A. (2009). Simulating the impact of climate change on rice yield using CERES-Rice model. Journal of Environmental Informatics, 13(2), 104-110.
Tan, J., Cui, Y., & Luo, Y. (2016). Global sensitivity analysis of outputs over rice-growth process in ORYZA model. Environmental Modelling & Software, 83, 36-46.
Van oort, P. A. J., Zhang, T. Y., De Vries, M. E., Heinemann, A. B., & Meinke, H. (2011). Correlation between temperature and phenology prediction error in rice (Oryza sativa L.). Agricultural and Forest Meteorology, 151, 1545–1555.
Wallach, D., Buis, S., Lecharpentier, P., Bourges, J., Clastre, P., Launay, M., Bergez, J.E., Guerif, M., Soudias, J., & Justes, E. (2011). A package of parameter estimation methods and implementation for the STICS crop-soil model. Environmental Modelling and Software, 26, 386-394.
Yin, X., & Struik, P.C. (2017). Can increased leaf photosynthesis be converted into higher crop mass production? A simulation study for rice using the crop model GECROS. Journal of Experimental Botany, 68(9), 2345-2360.
Zand, E., Jalal-Kamali, M.R., & Nazari, Sh. (2014). Some frontiers of knowledge in crop sciences and their impacts on food security. First International & 13 Iranian Crop Science Congress, Karaj, Iran, 26-28 Aug. (In Persian).
به زراعی کشاورزی
دوره 24، شماره 4
دی 1401
صفحه 1085-1100
فایل ها
هم رسانی
ارجاع به این مقاله
آمار