The estimation of carbon exchange between ecosystems and the atmosphere suffers unavoidable data gaps in eddy-covariance technique, especially for short-living and fast-growing croplands. In this study we developed a modified gap-filling scheme introducing a leaf area index factor as the vegetation status information based on the conventional light response function for two East-Asian cropland sites (rice and potatoes). This scheme’s performance is comparable to the conventional time window scheme, but has the advantage when the gaps are large compared to the total length of the time series. To investigate how the time binning approach performs for fast-growing croplands, we tested different widths of the time window, showing that a four-day window for the potato field and an eight-day time window for the rice field perform the best. The insufficiency of the conventional temperature binning approach was explained as well as the influence of vapor pressure deficit. We found that vapor pressure deficit plays a minor role in both the potato and the rice fields under Asian monsoon weather conditions with the exception of the early pre-monsoon growing stage of the potatoes. Consequently, we recommend using the conventional time-window scheme together with our new leaf-light response function to fill data gaps of net ecosystem exchange in fast-growing croplands.