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In this study, we collected data of meteorology, soil property, agricultural management and corn yield from five representative sites in Jilin Province, China, and integrated these data into a crop growth model of CERES-maize to simulate the potential productivity of five corn varieties. Our objectives were to simulate, calibrate and validate genetic parameters of the corns based on the analyses of climatic effects on the productivity, and to establish best practices for enhancing crop production in response to climatic change. The results showed that the projected days of sowing-flo-wering and flowering-maturing stages and yields of corn were well consistent with the measured va-lues with normalized mean variances being 2.96%, 3.40% and 9.37%, respectively, and the stan-dard deviation ranged from -10.6% to 15.2%. The mean projected light-temperature potential productivity (LTPP) of corns ranged from 7799.60 to 12902.83 kg·hm -2 ·a -1 , which decreased by 128.6-880.3 kg·hm -2 every 10 years. The correlation analysis suggested that climate change, i.e. temperature rising and significant decline of total radiation during the growth of corns, dominated the decrease of LTPP of corns in the region. The simulated genetic parameters indicated that the LTPP of the corns increased linearly with the increase of P5 (filling stage characteristic parameter referred to silking to physiological maturity of more than 8 ℃ heat time). Our model estimated that the LTPP might increase 154.44-261.10 kg·hm -2 for every 10 ℃·d increase of P5. The simulated sowing date delay showed that five days' sowing delay would maximize the LTPP of corns in Dunhua and Liaoyuan with 0.47% and 1.32% increase, respectively, while 15 days' delay would maximize the LTPP in Huadian and Yushu with 1.10% and 4.06% increase, respectively.