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Optimizing water, nitrogen and crop density in canola cultivation using response surface methodology and central composite design

Abstract Optimisation of water and nitrogen use is an effective management tool to conserve resources and reduce environmental pollutions. Response surface methodology (RSM) is defined as a collection of mathematical and statistical methods that are used to develop, to improve or to optimize a product or process. In order to determine optimum levels of water, nitrogen and planting density of canola (Brassica napus L.), a 2-year experiment (2010–2011) was carried out by central composite design as RSM at the research station of Ferdowsi University of Mashhad. The treatments were designed based on low and high levels of irrigation (1500 and 4000 m3 ha−1), nitrogen (0 and 400 kg N ha−1) and density (50 and 150 plant m−2) as independent variables. Furthermore, seed yield, nitrogen losses, nitrogen use efficiency (NUE) and water use efficiency (WUE) were measured as response variables in a full quadratic polynomial model. Optimum levels of irrigation, nitrogen and planting density were suggested to achieve the target range of dependent variables based on three scenarios: economic, environmental and eco-environmental. The results showed that increasing irrigation and fertilizer led to an increase in seed yield and nitrogen losses, whereas increasing canola density resulted in an increase in seed yield but a decrease in nitrogen losses. The optimum levels of water, fertilizer and density based on environmental scenario were 1802 m3 ha−1, 11 kg N ha−1 and 122 plant m−2, respectively. To achieve optimum conditions under the economic scenario, it is necessary to use 3411 m3 water ha−1, 178 kg N ha−1 and 119 plant m−2. Amounts of 2347 m3 water ha−1, 92 kg N ha−1 and 114 plant m−2 were found to be the optimum conditions for the eco-environmental scenario. In general, it seems that resource use based on the eco-environmental scenario may be the most favorable cropping strategy for canola production.