Abstract: Jianghuai region is the main doublecropping area in China, where the paddyupland rotation is a typical cultivation pattern. We conducted an experiment with three cropping systems: wheatrice (WR), rapeseedrice (RR) and fallowrice (FR) in the Anhui Lujiang National Modern Agriculture Demonstration Zone. The annual crop yield, accumulated temperature utilization rate, economic benefit and utilization efficiency for nitrogen (N), phosphorus (P) and potassium (K) under different systems were compared from 2016 to 2018. The results showed that mean annual yield of WR was 4018 and 5767 kg·hm^-2 higher than that of RR and FR, respectively. There was no significant difference in summer crops (rice) among the three systems. The difference in annual yield  mainly resulted from the difference of winter crop yield. The average yield of wheat was three times more than that of rapeseed. In terms of economic benefits, net income of WR was the highest. The average net income of WR was 6246 and 5182 yuan·hm-2 higher than that of RR and FR, with 59.69% and 44.95% of enhancement, respectively. Due to climate variability and disease, the interannual fluctuation of income of the RR was substantial. Compared with WR and FR, the utilization rate of accumulated temperature of the RR was increased by 9.98% and 39.33%, respectively. The nutrient utilization rate of WR was the lowest, as the two-year average nutrient balance index of N, P and K of WR was significantly higher than the other two systems. The FR had the highest N utilization rate, and the RR had the highest P and K utilization rate. In summary, the economic benefit of RR was significantly lower than WR. The RR had higher utilization rate of accumulated temperature and lower environmental risk. To promote the development of RR, it is necessary to improve the level of mechanized production of RR. Furthermore, the waste of light and heat in winter fallow pattern is serious and thus it is urgent to screen out the adaptable and ecofriendly crops for winter fallows.

Key words: broadband vegetation index, clearness index, leaf area index,