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Spatial variation of yield response and fertilizer requirements on regional scale for irrigated rice in China
Xinpeng Xu1, Ping He2,3, Mirasol F Pampolino4
1Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, P.R. China.
Abstract:
A large number of on-farm experiments (n = 5556) were collected for the period 2000-2015 from the major rice (Oryza sativa L.) producing regions in China, to study the spatial variability of attainable yield, yield response, relative yield and fertilizer requirements at regional scale, by coupling geographical information system with the Nutrient Expert for Rice decision support system. Results indicated that average attainable yield was 8.8 t ha-1 across all sites, with 18.3% variation. There were large variations in yield response to nitrogen (N), phosphorus (P), and potassium (K) fertilizer application with coefficients of variation of 39.2%, 57.0%, and 53.4%, and the sites of 73.4%, 85.8%, and 87.6% in the study area ranged from 2.0 to 3.0, from 0.7 to 1.3, and from 0.7 to 1.3 t ha-1, respectively. Mapping the spatial variability of relative yield to N, P, and K indicated that the sites of 78.6%, 92.4%, and 88.7% in the study area ranged from 0.65 to 0.75, from 0.80 to 0.92, and from 0.84 to 0.92, respectively. The high yield response and low relative yield to N and P were mainly located in the Northeast (NE), Northwest (NW), and north of the Middle and Lower Reaches of Yangtze River (MLYR) regions. The spatial distribution of N, P, and K fertilizer requirements ranged 140-160 kg N ha-1, 50-70 kg P2O5 ha-1 and 35-65 kg K2O ha-1 which accounted for 66.4%, 85.5% and 73.0% of sites in the study area, respectively. This study analyzed the spatial heterogeneity of attainable yield, soil nutrient supply capacity and nutrient requirements based on a large database at regional or national scale by means of geographical information systems and fertilizer recommendation systems, which provided a useful tool to manage natural resources, increase efficiency and productivity, and minimize environmental risk.
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