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Here is a list of all published papers related to ORYZA2000 / ORYZA v3 for the convenience of readers’ and users’ citation. (Updated October 2017)
1. Documentation of ORYZA2000 / ORYZA
Bouman, B.A.M., Kropff, M.J., Tuong, T.P., Wopereis, M.C.S., Ten Berge, H.F.M., & Van Laar, H.H. (2001). ORYZA2000: modeling lowland rice. International Rice Research Institute, Los Baños, Philippines, and Wageningen University and Research Centre, Wageningen, Netherlands, 235 pp.
Bouman, B.A.M., & Van Laar, H. H. (2006). Description and evaluation of the rice growth model ORYZA2000 under nitrogen-limited conditions. Agricultural Systems 87, 249-273.
Li, T., Angeles, O., Marcaida, M. III, Manalo, E., Manalili, M. P., Radanielson, A., Mohanty, S. (2017). From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments. Agricultural and Forest Meteorology, 237-238, 246–256. (http://doi.org/10.1016/j.agrformet.2017.02.025)
2. Papers on the use of ORYZA2000 / ORYZA
Amiri, E. (2008). Evaluation of the rice growth model ORYZA2000 under water management. Asian Journal of Plant Sciences, 7, 291-297.
Amiri, E., & Rezaei, M. (2009). Testing the modelling capability of ORYZA2000 under water-nitrogen limit conditions in northern Iran. World Applied Sciences Journal, 6, 1113–1122.
Amiri, E., & Rezaei, M. (2010). Evaluation of water–nitrogen schemes for rice in Iran, using ORYZA2000 model. Communications in Soil Science and Plant Analysis, 41, 2459–2477.
Amiri, E., Razavipour, T., Farid, A., & Bannayan, M. (2011). Effects of Crop Density and Irrigation Management on Water Productivity of Rice Production in Northern Iran: Field and Modeling Approach. Communications in Soil Science and Plant Analysis, 42 (17), 2085-2099.
Amiri, E., Rezaei, M., Eyshi Rezaei, E., & Bannayan, M. (2014). Evaluation of Ceres-Rice, Aquacrop and ORYZA2000 Models in Simulation of Rice Yield Response to Different Irrigation and Nitrogen Management Strategies. Journal of Plant Nutrition, 1749-1769.
Amiri Larijani, B., Sarvestani, Z.T., Nematzadeh Gh., Manschadt, A.M., & Amiri, E. (2011). Simulating phenology, growth and yield of transplanted rice at different seedling ages in Northern Iran using ORYZA2000. Rice Science, Volume 18 (Issue 4), 321-334.
Arora, V.K. (2006). Application of a rice growth and water balance model in an irrigated semi-arid subtropical environment. Agricultural Water Management, 83, 51–57.
Artacho, P., Meza, F., & Alcalde, J.A. (2011). Evaluation of the Oryza2000 rice growth model under nitrogen-limited conditions in an irrigated Mediterranean environment. Chilean Journal of Agricultural Research, 71 (1), 23-33.
Bannayan, M., Kobayashi, K., Kim, H.Y., Lieffering, M., Okada, M., & Miura, S. (2005). Modeling the interactive effects of atmospheric CO2 and N on rice growth and yield. Field Crops Research, 93, 237–251.
Bannayan M. (2009). Crop models efficiency and performance under elevated atmospheric CO2. Journal of Water and Soil, 23 (4), 115-126.
Belder, P., Spiertz, J.H.J., Bouman, B.A.M., Lu, G., & Tuong, T.P. (2005a). Nitrogen economy and water productivity of lowland rice under water-saving irrigation. Field Crop Research, 93, 169–185.
Belder, P., Bouman, B.A.M., Spiertz, J.H.J., Peng, S., Castaneda, A.R., & Visperas, R.M. (2005b). Crop performance, nitrogen and water use in flooded and aerobic rice. Plant and Soil, 273, 167–182.
Belder, P., Bouman, B.A.M., & Spiertz, J.H.J. (2007). Exploring options for water savings in lowland rice using a modeling approach. Agricultural Systems, 92, 91-114.
Boling, A.A., Tuong, T.P., Jatmiko, S.Y., & Burac, M. A. (2004). Yield constraints of rainfed lowland rice in Central Java, Indonesia. Field Crops Research, 90, 351–360.
Boling, A.A., Bouman, B.A.M., Tuong, T.P., Murty, M.V.R., & Jatmiko, S.Y. (2007). Modeling the effect of groundwater depth on yield-increasing interventions in rainfed lowland rice in Central Java, Indonesia. Agricultural Systems, 92, 115-139.
Boling, A.A., Tuong, T.P., Van Keulen, H., Bouman, B.A.M., Suganda, H., & Spiertz, J.H.J. (2010). Yield gap of rainfed rice in farmers’ fields in Central Java, Indonesia. Agricultural Systems, 103, 307-315.
Boling, A.A., Bouman, B.A.M., Tuong, T.P., Konboon, Y., & Harnpichitvitaya, D. (2011). Yield gap analysis and the effect of nitrogen and water on photoperiod-sensitive Jasmine rice in north-east Thailand. NJAS - Wageningen Journal of Life Sciences, 58, 11-19.
Bouman, B.A.M., Feng, L., Tuong, T.P., Lu, G., Wang, H., & Feng, Y. (2007). Exploring options to grow rice using less water in northern China using a modelling approach. II: Quantifying yield, water balance components, and water productivity. Agricultural Water Management, 88, 23-33.
Cao, B., Hua, S., Ma, Y., Li, B., & Sun, C. (2017). Evaluation of ORYZA2000 for Simulating Rice Growth of Different Genotypes at Two Latitudes. Agronomy Journal, 109, 1-17. (doi:10.2134/agronj2017.03.0145)
Confalonieri, R., Bregaglio, S., Adam, M., Ruget, F., Li, T., Hasegawa, T., ... & Fumoto, T. (2016). A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation. Environmental Modelling & Software, 85, 332-341.
Das, L., Lohar, D., Sadhukhan, I., Khan, S. A., Saha, A., & Sarkar, S. (2007). Evaluation of the performance of ORYZA2000 and assessing the impact of climate change on rice production in Gangetic West Bengal. Journal of Agrometeorology, 9, 1-10.
Devkota, K.P., Manschadi, A.M., Devkota, M., Lamers, J.P.A., Ruzibaev, E, Egamberdiev, O., Amiri, E, & Vlek, P.L.G. (2013). Simulating the impact of Climate change on Rice Phenology and grain yield in irrigated drylands of Central Asia. Journal of Applied Meteorology and Climatology, 52, 2033-2050.
Espe, M. B., Yang, H., Cassman, K. G., Guilpart, N., Sharifi, H., & Linquist, B. A. (2016a). Estimating yield potential in temperate high-yielding, direct-seeded US rice production systems. Field Crops Research, 193, 123-132.
Espe, M. B., Cassman, K. G., Yang, H., Guilpart, N., Grassini, P., Van Wart, J., & McKenzie, K. (2016b). Yield gap analysis of US rice production systems shows opportunities for improvement. Field Crops Research, 196, 276-283.
Feng, L., Bouman, B.A.M., Tuong, T.P., Cabangon, R.J., Li, Y. , Lu, G., & Feng, Y. (2007). Exploring options to grow rice using less water in northern China using a modelling approach. I: Field experiments and model evaluation. Agricultural Water Management, 88, 1-13.
Gaydon, D., Lisson, S., & Xevi, E. (2006). Application of APSIM ‘multi-paddock’ to estimate whole-of-farm water-use efficiency, system water balance and crop production for a rice-based operation in the Coleambally Irrigation District, NSW. Proceedings of 13th Agronomy Conference 2006; 10-14 September 2006, Perth, Western Australia (http://www.regional.org.au/au/asa/2006/concurrent/water/4632_gaydond.htm)
Huang, W.H., Xue, C.Y., Li, Z.H., & Yang, X.G. (2009). Research progresses in yield forecasting method based on crop growth simulation model in China. Chinese Journal of Agrometeorology, 30, 140-143.
Jing, Q., Bouman, B.A.M., Hengsdijk, H., Van Keulen, H., & Cao, W. (2007). Exploring options to combine high yields with high nitrogen use efficiencies in irrigated rice in China. European Journal of Agronomy, 26, 166-177.
Jing, Q., Bouman, B.A.M., Van Keulen, H., Hengsdijk, H., Cao, W., & Dai, T. (2008). Disentangling the effect of environmental factors on yield and nitrogen uptake of irrigated rice in Asia. Agricultural Systems, 98, 177-188.
Jing, Q., Van Keulen, H., & Hengsdijk, H. (2010). Modeling biomass, nitrogen and water dynamics in rice-wheat rotations. Agricultural Systems, 103, 433-443.
Kim, J., Sang, W., Shin, P., Cho, H., & Seo, M. (2015). Optimal date to predict rice yield with ORYZA2000 in South Korea. In 日本作物学会講演会要旨集 第 240 回日本作物学会講演会 (p. 70). 日本作物学会.
Kim, J., Sang, W., Shin, P., Cho, H., Seo, M., Yoo, B., & Kim, K. S. (2015). Evaluation of regional climate scenario data for impact assessment of climate change on rice productivity in Korea. Journal of Crop Science and Biotechnology, 18(4), 257-264.
Kreye, C., Bouman, B.A.M., Castañeda, A.R., Lampayan, R.M., Faronilo, J.E., Lactaoen, A.T.,& Fernandez, L. (2009). Possible causes of yield failure in tropical aerobic rice. Field Crops Research, 111, 197–206.
Krishnan, P., Swain, D.K., Chandra Bhaskar, B., Nayak, S.K., & Dash, R.N. (2007). Impact of elevated CO2 and temperature on rice yield and methods of adaptation as evaluated by crop simulation studies. Agriculture, Ecosystems and Environment, 122, 233–242.
Lee, C. K., Kim, J., & Kim, K. S. (2015). Development and application of a weather data service client for preparation of weather input files to a crop model. Computers and Electronics in Agriculture, 114, 237-246.
Li, T., Angeles, O., Marcaida, M. III, Manalo, E., Manalili, M. P., Radanielson, A., & Mohanty, S. (2017). From ORYZA2000 to ORYZA (v3): An improved simulation model for rice in drought and nitrogen-deficient environments. Agricultural and Forest Meteorology, 237-238, 246-256. (https://doi.org/10.1016/j.agrformet.2017.02.025)
Li T, Ali J, Marcaida M, III, Angeles O, Franje NJ, Revilleza JE, et al. (2016) Combining Limited Multiple Environment Trials Data with Crop Modeling to Identify Widely Adaptable Rice Varieties. PLoS ONE 11(10): e0164456. doi:10.1371/journal.pone.0164456
Li, T., Angeles, O., Radanielson, A., Marcaida III, M., & Manalo, E. (2015). Drought stress impacts of climate change on rainfed rice in South Asia. Climatic Change, 1-12 (http://link.springer.com/article/10.1007/s10584-015-1487-y/fulltext.html)
Li, T., Hasegawa, T., Yin, X., Zhu, Y., Boote, K., Adam, M., Bregaglio, S., Buis, S., Confalonieri, R., Fumoto,T., Gaydon, D., Marcaida III, M., Nakagawa, N., Oriol, P., Ruane, A.C., Ruget, F., Singh, B., Singh, U., Tang, L., Tao, F., Wilkens, P., Yoshida, H., Zhang, Z., Bouman, B. (2015). Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Global Change Conditions, 21, 1328-1341
Li, T., Anitha K. Raman, Manuel Marcaida III, Arvind Kumar, Olivyn Angeles, Ando M. Radanielson. (2013). Simulation of genotype performances across a larger number of environments for rice breeding using ORYZA2000. Fields Crop Research, 149, 312-321
Li, T., Bouman BAM, Boling A. (2009). The calibration and validation of ORYZA2000. IRRI Web. (https://sites.google.com/a/irri.org/oryza2000/calibration-and-validation)
Li, Y., Cui, Y., Li, Y., Lu, G., Feng, Y., & Bouman, B.A.M. (2005). Growth simulation of aerobic rice and its nitrogen management on the basis of ORYZA2000. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 21, 141-146.
Liu, W.C., Zhang, X.F., Yu, W.D., Xue, C.Y., Zhang, H., & Du, Z.X. (2009). Assessment method study on high temperature damage to rice. Meteorological and Environmental Sciences, 32 (1), 33-38.Lorençoni, R., Neto, D.D., & Heinemann, A.B. (2010). Calibration and evaluation of the ORYZA-APSIM crop model for upland rice in Brazil. Revista Ciência Agronômica, 41(4), 605-613.
Luo, Y., Jiang, Y., Peng, S., Cui, Y., Khan, S., Li, Y., & Wang, W. (2015). Hindcasting the effects of climate change on rice yields, irrigation requirements, and water productivity. Paddy and Water Environment, 13(1), 81-89.
Mottaleb, K. A., Rejesus, R. M., Murty, M. V. R., Mohanty, S., & Li, T. (2016). Benefits of the development and dissemination of climate-smart rice: ex ante impact assessment of drought-tolerant rice in South Asia. Mitigation and Adaptation Strategies for Global Change, 1-23.
Pang, G., Li, Y., Xu, Z., & Gao, H. (2014). Calibration and evaluation of ORYZA2000 under water and nitrogen managements. Applied Mechanics and Materials, 641-642, 246-250
Paydar, Z., Gaydon, D., & Chen. Y. (2009). A methodology for up-scaling irrigation losses. Journal Irrigation Science, 27, 347-356.
Pazhanivelan, S., Kannan, P., Mary, P. C. N., Subramanian, E., Jeyaraman, S., Nelson, A., ... & Yadav, M. (2015). Rice Crop Monitoring and Yield Estimation Through Cosmo Skymed and TerraSAR-X: A SAR-Based Experience in India. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 85.
Pey, B., Mercat-Rommens, C., Audebert, A., & Mouret, J.C. (2009). Study of the radioecological sensitivity of rice to radioactive contamination. Radioprotection, 44, 339–343.
Sailaja, B., Voleti, S. R., Gayatri, S., Subrahmanyam, D., Kumar, R. N., Rao, P. R., & Meera, S. N. (2015). VULNERABILITY OF RICE YIELDS UNDER CHANGED CLIMATIC CONDITIONS. Int. J. Agricult. Stat. Sci. Vol,11(2), 523-526.
Sailaja, B., Voleti, S.R., Subrahmanyam, D., Nathawat, M.S., & Rao, N.H. (2013). Validation of Oryza2000 model under combined nitrogen and water limited situations. Indian Journal of Plant Physiology, Volume 18 (Issue1), 31-40.
Silva, J. V., Reidsma, P., Laborte, A. G., & van Ittersum, M. K. (2016). Explaining rice yields and yield gaps in Central Luzon, Philippines: An application of stochastic frontier analysis and crop modelling. European Journal of Agronomy.
Shao, D., Sun, C., Wang, H., Liu, H., Yuan, J., Wang, J., & Zheng, C. (2010). Simulation on regulation for efficient utilization of water and fertilizer resources in paddy fields. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 26 (12), 72-78.
Sharifi, H., Hijmans, R., Espe, M., Hill, J., & Linquist, B. (2015, December). Optimal Estimation of Phenological Crop Model Parameters for Rice (Oryza sativa). In 2015 AGU Fall Meeting. Agu.
Sheehy, J.E., Mitchell, P.L., & Ferrer, A.B. (2006). Decline in rice grain yields with temperature: Models and correlations give different estimates. Field Crops Research, 98, 151-156.
Sheinkman, M. (2015). Workshop report: Integrated Modeling of Climate Impacts on Agricultural Productivity and Socio-Economic Status (IMCASE) in the Philippines.
Shen, S.H.,Yang, S.B., Li, B.B., Zhao, X.Y., Tan, B.X., Li, Z.Y., & Le Toan, T. (2008). Study on ENVISAT ASAR data assimilation in rice growth model for yield estimation. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B8, 951-956.
Shen, S.H., Yang, S.B., Li, B.B, Tan, B.X., Li, Z.Y., & Le Toan, T. (2009). A scheme for regional rice yield estimation using ENVISAT ASAR data. Science in China Series D-Earth Sciences, 52, 1183-1194.
Shen, S.H., Yang, S.B., Zhao, Y.X., Xu, Y.L., Zhao, X.Y., Wang, Z.Y., Liu, J., & Zhang, W.W. (2011). Simulating the rice yield change in the middle and lower reaches of the Yangtze River under SRES B2 scenario. Acta Ecologica Sinica, 31, 40-48.
Shi, C.L., Feng, H.H., Jin, Z.Q., & Wang, H. (2010). Comparison of phasic development models in rice. Chinese Journal of Rice Science, 24(3) 303-308.
Soundharajan, B., & Sudheer, K.P. (2009). Deficit irrigation management for rice using crop growth simulation model in an optimization framework. Paddy Water Environment, 7, 135–149.
Sudhir-Yadav, Li, T., Humphreys, E., Gill, G., & Kukal, S.S. (2011). Evaluation and application of ORYZA2000 for irrigation scheduling of puddled transplanted rice in north west India. Field Crops Research, 122, 104–117.
Sudhir-Yadav, Humphreys, E., Li, T., Gill, G., Kukal, S.S. (2012). Evaluation of tradeoffs in land and water productivity of dry seeded rice as affected by irrigation schedule. Field Crops Research, 128, 180-190.
Sumathi, A., Mohandass, S., & Ramasamy, S. (2015). Impact of climate change scenario on rice production in two planting methods: a simulation study. International Journal of Environmental Science and Technology, 12(5), 1539-1548.
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.
Tang, L., Zhu, Y., Hannaway, D., Meng, Y., Liu, L., Chen, L., & Cao, W. (2009). RiceGrow: A rice growth and productivity model. NJAS -Wageningen Journal of Life Sciences, 57, 83–92.
Timsina, J., Jat, M.L., & Majumdar, K. (2010). Rice-maize systems of South Asia: current status, future prospects and research priorities for nutrient management. Plant and Soil, 335, 65–82.
Tuong, T.P., Phong, N.D., & Bouman, B.A.M. (2003). Assessing rice yield in rice–shrimp systems in the Mekong Delta, Vietnam: a modelling approach. In: Preston, N. and Clayton, H. (eds), Rice–shrimp farming in the Mekong Delta: biophysical and socioeconomic issues. ACIAR Technical Reports No. 52e, pp 102-110.
Vaghefi, N., Nasir Shamsudin, M., Makmom, A., & Bagheri, M. (2011). The economic impacts of climate change on the rice production in Malaysia. International Journal of Agricultural Research, 6 (1), pp. 67-74.
Van Oort, P. A., de Vries, M. E., Yoshida, H., & Saito, K. (2015). Improved climate risk simulations for rice in arid environments. PloS one, 10(3), e0118114.
Van Oort, P.A.J., Zhang, T., 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. Article in Press. doi:10.1016/j.agrformet.2011.06.012.
Wang, W., Ding, Y., Shao, Q., Xu, J., Jiao, X., Luo, Y., & 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. Agricultural and Forest Meteorology, 232, 89-105.
Wikarmpapraharn, C. & Kositsakulchai, E. (2010). Evaluation of ORYZA2000 and CERES-Rice Models under Potential Growth Condition in the Central Plain of Thailand. Thai Journal of Agricultural Science, 43(1), 17–29.
Xie, W.X., Zhao, Q.S., Wang, G.H. (2009). Advances in nitrogen simulation model of rice growth. Chinese Journal of Soil Science, 40 (3), 702-708.
Xue, C.Y., Yang, X.G., Deng, W., Zhang, T.Y., Yan, W.X., Zhang, Q.P., Rouzi, A., Zhao, J.F., Yanf, J., & Bouman, B.A.M. (2007). Yield potential and water requirement of aerobic rice in Beijing analyzed by ORYZA2000 model. Acta Agronomica Sinica, 33, 625-631.
Xue,C.Y., Yang, X.G., Bouman, B.A.M., Deng, W., Zhang, Q.P., Yan, W.X., Zhang, T., Rouzi, A., & Wang, H. (2008a). Optimizing yield, water requirements, and water productivity of aerobic rice for the North China Plain. Irrigation Science, 26, 459-474.
Xue, C.Y., Yang, X.G., Deng, W., Zhang, Q.P., Yan, W., Wang, H., & Bouman, B.A.M. (2008b). Establishing optimum irrigation schedules for aerobic rice in Beijing using ORYZA2000 model. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 24, 76-82.
Xue, C.Y., Yang, X.G., Chen, H., Feng, L., Wang, H., & Bouman, B.A.M. (2010). Determining suitable sowing dates for aerobic rice in Beijing area using the ORYZA2000 model. Shengtai Xuebao/ Acta Ecologica Sinica, 30 (24), 6970-6979.
Yang, S.B., Shen, S.H., Zhao, X.Y., Zhao, Y.X., Xu, Y.L., Wang, Z.Y., Liu, J., Zhang, W.W. (2010). Impacts of climate changes on rice production in the middle and lower reaches of the Yangtze River. Acta Agronomica Sinica, 36 (9), 1519-1528.
Ye, F.Y. , et. al. (2009). Review on development and application of rice productivity models. Journal of Anhui Agricultural Sciences, 37 (1), 85-89.Yuan, S., Peng, S., & Li, T. (2017). Evaluation and application of the ORYZA rice model under different crop managements with high-yielding rice cultivars in central China. Field Crops Research, 212, 115-125. (https://doi.org/10.1016/j.fcr.2017.07.010)
Zhang, Q., Wang, G. H., Feng, Y. K., Sun, Q. Z., Witt, C., & Dobermann, A. (2006). Changes in soil phosphorus fractions in a calcareous paddy soil under intensive rice cropping. Plant and Soil, 288, 141–154.
Zhang, T., Zhu, J., Yang, X., & Zhang, X. (2008a). Correlation changes between rice yields in North and Northwest China and ENSO from 1960 to 2004. Agricultural and Forest Meteorology, 148, 1021-1033.
Zhang, T., Zhu, J., & Yang, X. (2008b). Non-stationary thermal time accumulation reduces the predictability of climate change effects on agriculture. Agricultural and Forest Meteorology, 148, 1412-1418.
Zhang, X., Lee J.H., Abaw, Y., Kim, Y.H., McClymont, D., & Kim, H.D. (2007). Testing the simulation capability of APSIM-ORYZA under different levels of nitrogen fertiliser and transplanting time regimes in Korea. Australian Journal of Experimental Agriculture, 47, 1446-1454.
Zhang, J., Feng, L., Zou, H., & Li Liu, D. (2015). Using ORYZA2000 to model cold rice yield response to climate change in the Heilongjiang province, China. The Crop Journal, 3(4), 317-327.
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