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 m 3 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 m 3 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 m 3 water ha −1 , 178 kg N ha −1 and 119 plant m −2 . Amounts of 2347 m 3 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.

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“…roots and improve plant growth Koocheki et al, 2014) therefore reducing N amounts decrease the performance too. According to Figure 1 it is clear that reducing of input resources, lead to yield loss, also the tuber yield reduction slope is more when reducing water than reducing nitrogen.…”

“…Therefore RSM has been suggested to determine the effects of individual factors and the effects of their interaction (Koocheki et al, 2014).…”

“…The CCD provides data equivalent to three-level factorial, but by reducing the number of experiments (less than full factorial experimental) and also arranges experiments with different combinations of the independent variables (Koocheki et al, 2014). Table 1 shows maximum, minimum and average values limits of independent variables and their coded values .…”

“…Determination coeffi cient is a measure of the strength of the linear relationship between two variables, which at best should be equal to 1. Lack of fi t test calculations obtain by comparing the sum of the remaining squares and the sum of the squares (F-test) which non signifi cance of this parameter indicates the appropriateness of the model Koocheki et al, 2014). Table 3 represents the details of the analysis of the quadratic polynomial model variance fi tted for yield response and water use effi ciency response variables.…”

“…Koocheki et al (2014) used of the RSM to determine the optimum values of water, nitrogen and the crop density in canola cultivation. The results showed that increasing the amount of irrigation water and fertilizer leads to increased yield and nitrogen losses, while increasing crop density increased the yield and reduce nitrogen loss.…”