Abstract. The eddy-covariance technique is applied worldwide to acquire information about carbon exchange between a variety of ecosystems and atmosphere, but the data acquisition only covers, on average, two-thirds of the whole year due to system failures and data rejection. Therefore, data must be corrected and data gaps must be filled to provide seasonal or annual budgets. The gap-filing strategies, however, are still under discussion within the research community. Presently the major gap-filling methods work quite well for long-time running sites over slow-developing biosphere surfaces such as long-living evergreen forests, but difficulties appear for short-living and fast-growing croplands. In this study we developed a new Multi-Step Error Filter procedure to gain good-quality data as input for different parameterizations of the light response function of plants for two cropland sites (rice and potatoes), and we could prove that the conventional temperature binning approach is inadequate. The presented time-window scheme showed best results with a four-day time window for the potato field and an eight-day time window for the rice field. The influence of vapor pressure deficit was tested as well, but in our case it plays a minor role at both the potato and the rice fields with the exception of the early growing stage of the potatoes. Completing our research, we suggest an innovative method by introducing a Leaf Area Index factor to capture the seasonal vegetation development. With this method we are now able to fill the large gaps between observation periods when conventional methods are invalid.