Optimization of Irrigation and Nitrogen Levels on Yield, Water Use Efficiency, and Nitrogen Use Efficiency of Quinoa (Chenopodium quinoa Willd.) by Using the Surface-Response Methodology

 The optimum resource level in agro-ecosystems should be determined to decrease production costs, conserve resources, and mitigate environmental pollutions. Optimization is an effective and sustainable management approach to conserve resources and decline environmental pollutions. Response surface methodology (RSM) is defined as a collection of mathematical and statistical techniques used to develop, improve, or optimize a product. RSM is a statistical technique for optimization of multiple factors that determine optimum rates by combining experimental designs. Quinoa (Chenopodium quinoa Willd.) is a pseudocereal, seed-producing annual crop, and a staple food in South America in ancient times, indigenous to the Andean region of South America, particularly Bolivia, Peru, Ecuador, and parts of Chile, which has the potential to grow with low inputs, mostly water and tolerate a variety of biotic and abiotic stresses. Quinoa seed is gluten-free foods, good sources of carbohydrates, good-quality proteins, lipids, vitamins, minerals, and bioactive compounds, with all the essentials, trace elements, and many vitamins. In this work, optimization of nitrogen and water rates on quinoa was done.

An experiment was conducted using Central Composite Design (CCD) with 13 treatments and two replications at the Research Field of the Ferdowsi University of Mashhad during the growing season of 2017-2018. The treatments were allocated based on low and high water (2500 and 7500 m3 ha-1, respectively) and nitrogen (0 and 200 kg ha-1, respectively) levels. Seed yield, biological yield, N recovery, N use efficiency (NUE), and water use efficiency (WUE) were calculated as dependent variables, and changes of these variables were evaluated by a regression model. A lack-of-fit test was used to evaluate the quality of the fitted model. The adequacy of the model was tested by analysis of variance. The quality of the fitted models was judged using the determination coefficient (R2). Finally, the optimum nitrogen and water rates were computed based on economic, environmental, and economic-environmental scenarios.

The results showed that the effect of linear and square components was significant on all studied characteristics. The interaction effect of full quadratic was significant on NUE and WUE. Lack of fit test had no significant effect on the studied traits. The full square model for the response variables gave insignificant lack-of-fit, indicating that the data were satisfactorily explained. Surface-response results of the effect of irrigation and nitrogen levels on grain yield and biological yield showed that with increasing nitrogen consumption and irrigation, quinoa yield indices increased, but in terms of nitrogen use, with increasing nitrogen consumption more than 100 kg ha-1, the grain yield increased with more slope. The highest value of seed yield was observed for 7500 m3 ha-1 irrigation and 200 kg nitrogen ha-1 with 3835.4 kg ha-1. Optimum nitrogen and water rates were suggested to determine the target range of dependent variables based on three scenarios: economic, environmental, and eco-environmental. It is necessary to use 169.7 kg nitrogen ha-1 and 7500 m3 ha-1 irrigation to obtain optimum conditions under the economic scenario. The optimum nitrogen and irrigation rates based on environmental scenarios were computed from 18.18 kg nitrogen ha-1 and 3409 m3 ha-1 irrigation water. Application of 88.57 kg nitrogen ha-1 and 5909 m3 ha-1 irrigation water was found to be the optimum conditions for the eco-environmental scenario (NUE, N recovery, seed yield, and WUE were calculated with 15.93 kg seed kg-1 N, 50.04%, 3120.76 kg ha-1, and 0.5 kg seed m-3 water, respectively).

Increasing nitrogen led to increased seed yield and decreased nitrogen use efficiency, whereas increasing irrigation caused an increase in seed yield and nitrogen use efficiency. In general, it seems that resource use based on the eco-environmental scenario may be a suitable cropping approach for the sustainable production of quinoa as a new crop.