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).