Introduction
Quinoa (Chenopodium quinoa) is native plant in Bolivia, Chile and Peru, which is widely adapted to different climatic conditions and can grow in all soils. This plant has shown adequate adaptation to arid and semi-arid areas conditions and is planted from areas with low elevation (sea level) to areas with an altitude of 4000 meters above sea level. Quinoa is often cultivated in areas with limited water resources, and it is rare to find quinoa cultivation under full irrigation conditions. Some studies have shown that quinoa yields slightly better under full irrigation (without water restriction) than quinoa under deficit irrigation. Crop growth models are very important tools in the study of agricultural systems and they can be used to simulate the yield of crop in different conditions. Given that the study of performance limiting factors requires numerous and costly research and experiments in different areas, so finding a way to reduce the number, time and cost of these experiments is worthwhile. Aquacrop model is one of the applied models that are used to simulate yield variations in different water and soil management.
Materials and Methods
This investigation was carried out in two growing seasons of 2019 and 2020 to determine the efficiency of Aquacrop model for simulating Quinoa grain yield and biomass under imposing three stress treatments of 30, 50 and 70% of water consumption in development and mid-growth stages. Plant spacing was 40 cm between rows and 7 cm between plants within rows. Seeds of quinoa (Titicaca cultivar) were cultivated in the first decade of August 2019 and in the third decade of July 2020. The experiment was a randomized complete block design with three replications. Three deficit irrigation treatments including 30, 50 and 70% of available water were considered in two growth stages (development and mid-growth) in 18 experimental plots (3 × 4 m). Soil moisture in rooting depth (about 40 cm) was measured by TDR and after the soil moisture of the treatments reached the desired values, plots were irrigated until the soil moisture reached the field capacity. The results of grain and biomass yield in the first year were used to calibrate the Aquacrop model and the results of the second year were used to validate the model. Root mean square error (RMSE), normalized root mean square error (NRMSE), Willmott index (D), model efficiency (EF) and mean error deviation (MBE) were used to compare the simulated and observed values.
Results and Discussion
The results of the first and second year were used to calibrate and validate the model, respectively. The results of the first year showed that irrigation with 50 and 70% of available water in the development stage reduced quinoa grain yield by 17 and 33%, respectively, compared to the control treatment. The application of these two deficit irrigation treatments in the middle stage reduced the yield by about 12 and 28%, respectively. The results of comparing the statistical indices of grain yield, biomass and water use efficiency showed that the NRMSE for grain, biomass and water use efficiency were 9, 8 and 14% in the first year and 9, 6 and 9% in the second years. Furthermore, the EF for these traits were 0.81, 0.77 and 0.64 in the first year and 0.68, 0.71 and 0.62, in the second year, respectively.
Conclusion
The results of calibration and validation of the model showed the accuracy and efficiency of the Aquacrop model in simulating grain yield, biomass and water use efficiency of quinoa. This model can be used to provide the most appropriate scenario and irrigation management for different levels of deficit irrigation managements. |
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