ارزیابی مدل ORYZA2000 در شبیه‌سازی عملکرد و بهره‌وری تولید برنج تحت مدیریت‌های زراعی.

1.Agricultural Statistics 2017. Volume I: Crop products. 2015-16. Office of Statistics and Information -Technology, Deputy Director of Planning and Economic Affairs. Ministry of Agricultural Jihad. 90p. (In Persian)

2.Amiri Larijani, B., Sarvestani, Z.T., Nematzadeh, G., Manschadi, A.M., and Amiri, E. 2011. Simulating phenology, growth and yield of transplanted rice at different seedling ages in northern
Iran using ORYZA2000. Rice Sci.18: 4. 321-334.

3.Amiri Larijani, B., Tahmasebi, S.Z., and Nematzade, G.A. 2013. Simulation of leaf area index, biomass and grain yield of rice cultivars at different seedling ages using ORYZA2000 model. Seed and plant production. 29: 3. 283-302.

4.Amiri, E. 2008. Evaluation of the rice growth model ORYZA2000 underwater managements. Asian J. Plant Sci.7: 3. 291-297.

5.Amiri, E. 2011. Simulation of rice growth and development under irrigation constraints. Biology science. 5: 4. 1-13. (In Persian).

6.Amiri, E., and Rezaei, M. 2010. Evaluation of water–nitrogen schemes for rice in Iran, using ORYZA2000 model. Commun. Soil Sci. Plan. 41: 20. 2459-2477.

7.Amiri, E., Razavipour, T., and Bannayan, M. 2011a. Evaluation of yield and water productivity in rice under irrigation management and plant density with use ORYZA2000 model. Crop production.
4: 3. 1-19. (In Persian)

8.Amiri, E., Razavipour, T., Farid, A., and Bannayan, M. 2011b. Effects of crop density and irrigation management on water productivity of rice production in Northern Iran: Field and Modeling Approach. Commun. Soil Sci. Plan.42: 17. 2085-2099.

9.Amiri, E., Rezaei, M., Rezaei, E.E., and Bannayan, M. 2014. Evaluation ofCeres-Rice, Aquacrop and Oryza2000 models in simulation of rice yield response to different irrigation and nitrogen management strategies. J. Plant Nutr. 37: 11. 1749-1769.

10.Bouman, B.A.M., Kropff, M.J., Tuong, T.P., Wopereis M.C.S., Ten Berge, H.F.M., and Van Laar, H.H. 2001. ORYZA2000: modeling lowland rice. International Rice Research Institute, Los Banos. 245p.

11.Bouman, B.A.M., and Van Laar, H.H. 2006. Description and evaluation of the rice growth model ORYZA2000 under nitrogen-limited conditions. Agric, Syst. 87: 3. 249-273.

12.Brar, S.K., Mahal, S.S., Brar, A.S., Vashist, K.K., Sharma, N., and Buttar, G.S. 2012. Transplanting time and seedling age affect water productivity, rice yield and quality in north-west India. Agr. Water manage. 115: 217-222.

13.Cao, B., Hua, S., Ma, Y., Li, B.,and Sun, C. 2017. Evaluation of ORYZA2000 for Simulating Rice Growth of Different Genotypes at Two Latitudes. Agron, J. 109: 6. 2613-2629.

14.Chahal, G.B.S., Sood, A., Jalota,S.K., Choudhury, B.U., and Sharma, P.K. 2007. Yield, evapotranspirationand water productivity of rice–wheat system in Punjab (India) as influenced by transplanting date of rice and weather parameters. Agr. Water Manage.88: 1-3. 14-22.

15.Drenth, H., ten Berge, F.F.M., and Riethoven, J.J.M. 1994. ORYZA simulation modules for potential and nitrogen limited rice production SARP Research Proceedings. Wageningen, the Netherlands. 223p.

16.FAO. 2016. Food and Agricultural Organization of the United Nations (sited in: http://www.fao.org/ index_ en.htm/, 11/4/2018.

17.Jabran, K., Ullah, E., Hussain, M., Farooq, M., Haider, N., and Chauhan, B.S. 2015. Water saving, water productivity and yield outputs of fine-grain rice cultivars under conventional and water-saving rice production systems. Exp, Agr. 51: 4. 567-581.

18.Lampayan, R.M., Samoy-Pascual, K.C., Sibayan, E.B., Ella, V.B., Jayag, O.P., Cabangon, R.J., and Bouman, B.A.M. 2015. Effects of alternate wetting and drying (AWD) threshold level and plant seedling age on crop performance, water input, and water productivity of transplanted rice in Central Luzon, Philippines. Paddy and water Environ. 13: 3. 215-227.

19.Mahajan, G., Bharaj, T.S., and Timsina, J. 2009. Yield and water productivity of rice as affected by time of transplanting in Punjab, India. Agr. Water Manage. 96: 3. 525-532.

20.Majumder, D., and Das, L. 2018. Simulating the yield attributes of Boro rice under nitrogen and irrigation management at Mohanpur, West Bengal using ORYZA2000. J. Agrometeorol. 20: 1. 72-74.

21.Pang, G.B., Li, Y., Xu, Z.H., and Gao, H.Z. 2014. Calibration and Evaluation of ORYZA2000 under Water and Nitrogen managements. In Applied Mechanics and Materials. 641: 246-250.

22.Pazoki, A.R., Karimi Nejad, M., and Foladi Toroghi, A.R. 2010. Effect of planting dates on yield of ecotypes of saffron (Crocus sativus L.) in Natanz region. Crop Physiology. 2: 8. 3-12.
(In Persian)

23.Rinaldi, M., Losavio, N., and Flagella, Z. 2003. Evaluation of OIL CROP-SUN model for sun flower in southern Italy. Agric. Sys. 78: 17-30.

24.Sailaja, B., Voleti, S.R., Subrahmanyam, D., Nathawat, M.S., and Rao, N.H. 2013. Validation of Oryza2000 model under combined nitrogen and water limited situations. Ind. J. Plant Physiol. 18: 1. 31-40.

25.Singh, M.C., Jain, A.K., and Jalota, S.K. 2017. Impact of Transplanting Date and Irrigation Scheduling on Water Balance, Water Productivity and Soil Moisture Movement. J. Agric. Eng. 54: 1. 28-32.

26.Singh, R., Van Dam, J.C., and Feddes, R.A. 2006. Water productivity analysis of irrigated crops in Sirsa district, India. Agr. Water Manage. 82: 253-278.

27.Soltani, A., Rahimzadeh Khoei, F., Ghassemi-Golezani, and Moghaddam, M. 1999. Cicer: A computerized model for simulating chickpea growthand yield. Agric. Sci. 9: 3. 89-106.(In Persian)

28.Soundharajan, B., and Sudheer,K.P. 2013. Sensitivity analysis andauto-calibration of ORYZA2000
using simulation-optimization framework. Pady Water Environ. 11: 1-4. 59-71.

29.Tari, D.B., Amiri, E., and Daneshian, J. 2017. Simulating the Impact of Nitrogen Management on Rice Yield and Nitrogen Uptake in Irrigated Lowland by ORYZA2000 Model. Common. Soil Sci. Plan. 48: 2. 201-213.

30.Van Oort, P.A.J., Balde, A., Diagne, M., Dingkuhn, M., Manneh, B., Muller, B., ... and Stuerz, S. 2016. Intensification of an irrigated rice system in Senegal: Crop rotations, climate risks, sowing dates and varietal adaptation options. Eur. J. Agron. 80: 168-181.

31.Wang, W., Ding, Y., Shao, Q., Xu, J., Jiao, X., Luo, Y., and Yu, Z. 2017. Bayesian multi-model projection of irrigation requirement and water use efficiency in three typical rice plantation region of China based on CMIP5. Agr. Forest Meteorol. 232: 89-105.

32.Wang, X., Lu, W., Jun Xu, Y., Zhang, G., Qu, W., and Cheng, W. 2016. The positive impacts of irrigation schedules on rice yield and water consumption: synergies in Jilin Province, Northeast China. Int. J. Agr. Sustain. 14: 1. 1-12.

33.Wopereis, M.C.S., Bouman, B.A.M., Tuong, T.P., ten Berge, H.F.M.,and Kropff, M.J. 1996. ORYZA W:
rice growth model for irrigated and rain fed environments. SARP Research proceeding. Wageningen. The Netherlands. 164p.

34.Wopereis, M.C.S. 1993. Quantifying the impact of soil and climate variability on rainfed rice production. PhD thesis. Wageningen (Netherlands): Wageningen Agricultural University. 188p.

35.Xue, C.Y., Yang, X.G., Bouman, B.A.M., Deng, W., Zhang, Q.P., Yan, W.X., Zhang, T., Rouzi, A., and Wang, H. 2008. Optimizing yield, water requirements, and water productivity of aerobic rice for the North China Plain. Irrigation Sci. 26: 6. 459-474.

36.Zhang, S., Tao, F., and Zhang, Z. 2017. Uncertainty from model structure is larger than that from model parameters in simulating rice phenology in China. Eur. J. Agron. 87: 30-39.

37.Zolfagari, H., Farhadi, B., and Rahimi. H. 2016. Climatic Potentials in Iran for Soybean Cultivation Geogr. Plann. 20: 56. 89-105. (In Persian).