Plant net primary production(NPP) of agriculture vegetation represents the capacity of sequestrating atmospheric CO2 in agro-ecosystem,and plays an important role in terrestrial carbon cycling.In comparison with natural ecosystems of forest and grassland,agro-ecosystem is much complex due to human activities.To better understand the contribution of agro-ecosystem to regional carbon budget,the simulation models of crop NPP have been developed well since the 1970s.However,few models are successfully put into practice in the agro-ecosystem of China,being mainly due to the unavailability of model inputs and the verification of reliability in different regions of China.The objectives of this paper are to establish a crop NPP model that could be put into practice in the agro-ecosystem of China and to make sensitivity analysis of the model. In light of a preliminary model established by the authors that simulates NPP of rice and wheat crops,a model named as Crop-C was developed.Crop-C is dedicated to the simulation of NPP of those crops of rice,wheat,maize,cotton,rapeseed and soybean planted in approximately two-thirds of agricultural soils in China.The model includes two main functional modules:photosynthesis and respiration,and nitrogen transport within soil-plant system.The processes of photosynthesis and respiration are mainly driven by environmental variables of temperature,solar radiation,precipitation,atmospheric CO2 concentration and crop tissue nitrogen.The transportation of nitrogen within soil-plant system is determined by simulating the processes of crop nitrogen uptake,soil nitrogen mineralization and synthetic nitrogen release. Model sensitivity analysis suggests that the sensitive significance of Crop-C to input parameters is in descending order of temperature,PAR,atmospheric CO2 concentration,soil nitrogen concentration,rate of nitrogen application and precipitation when the input parameters vary at-10% and 10%,respectively.In addition,global warming would have a negative effect on NPP of agricultural vegetation in China based on the model sensitivity analysis.