Understanding regional relationships between climate change and crop yield will help with making the strategic decisions for food security in China under climate change. In this study, the contributions of climate change to spring maize yield over the past three decades in Northeast China were decoupled based on the daily climate variables gathered from 68 meteorological stations and detailed observed data of spring maize from 55 agricultural meteorological experimental stations for the period 1978-2010 in Northeast China, analyzed with a linear statistical model. Then, the key climatic factors limiting the climate-induced yield of spring maize were identified. The agro-climatic similarity theory was applied. Finally, the relationships between the climatic variables and the climate-induced yield of spring maize were further explored by provinces. The results show that: from 1978 to 2010, the observed yields of spring maize in Northeast China increased markedly, with inter-annual fluctuations. Compared with the methods of moving average and harmonic average, Logistic regression optimally decoupled the climate-induced yield of spring maize. The key meteorological factors limiting the climate-induced yield were temperature, precipitation and sunshine, varying in the different regions. In Heilongjiang Province, the climate-induced yields of spring maize were mainly affected by maximum temperatures in August and precipitation in June. In Jilin Province, climate-induced yield was closely related to precipitation during daily the average temperature stably passing 10°C (?10°C). In Liaoning Province, when the maximum temperature was high and the sunshine was abundant in June, the climate-induced yield of spring maize significantly increased. Finally, the regression models between climatic variables and climate-induced yield of spring maize in 11 representative zones in Northeast China also established geographical differences.
