نوع مقاله : مقاله پژوهشی
نویسنده
استادیار بخش ابیاری و فیزیک خاک موسسه تحقیقات خاک و اب
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسنده [English]
The application of crop models to simulate crop responses to water and nitrogen (N) is crucial for improving agricultural management. The majority of these models involve complex equations and require several input parameters for calibration. AquaCrop simulates crop response to different N levels using a semi-quantitative approach, which simulates the effect of N stress on transpiration and biomass production during the growing season. This model does not provide information on the optimal timing and quantity of N fertilizer application for efficient farm management. In the present study, a direct simulation approach based on the concept of a critical nitrogen curve was applied to simulate the effect of N deficiency on transpiration and biomass production. The main objective of this study was to evaluate a direct simulation approach and compare its results with those derived from the semi-quantitative approach. For this purpose, experimental data were collected from two years of maize cultivation. Biomass and plant nitrogen concentrations were measured during the growing season. The results showed that the RRMSE (relative root mean square error) index in biomass simulation by the direct method was, on average, 4% lower for each treatment compared to the semi-quantitative approach. In addition, increased N stress led to increased errors in simulating biomass. Thus, the RRMSE for biomass simulation using the direct method was 26.48 % and 30.96% for treatments under the highest stress, and 9.57% and 15.75 % for non-stressed treatments. In general, these findings show that integrating the critical nitrogen concentration concept into crop models provides more accurate estimates for crops under nitrogen stress.
کلیدواژهها [English]
EXTENDED ABSTRACT
The application of crop models to simulate crop responses to water and nitrogen (N) is crucial for improving agricultural management. The majority of these models involve complex equations and require several input parameters for calibration. They are used to simulate the water flow and N transport in soil and plants. AquaCrop as a user-friendly model, simulates the crop response to different amounts of N using a semi-quantitative approach which simulates the effect of N stress on transpiration and biomass production during the growing season. In this method, the effect of N deficiency on biomass production is simulated based on several constant reduction coefficients for each stress level during the growing season. This model cannot determine the proper time and amount of N fertilizer for efficient farm management. In the present study, a direct simulation approach based on the concept of a critical nitrogen curve was applied to simulate the effect of N deficiency on transpiration and biomass production. In this method, biomass values were simulated based on the effect of N deficiency on canopy resistance (rc), transpiration (Tr), and normalized water productivity (WP*) parameters, during the growing season. The main objective of this study was to evaluate a direct simulation approach and compare its results with the AquaCrop semi-quantitative approach.
For this purpose, field experiments were conducted at the research farm located in Tehran, during the 2015 and 2016 growing seasons. Five N treatments were investigated including no nitrogen (N0), 50(N1), 100(N2), 150(N3) and 200 kg N. ha−1 (N4) for each year. Biomass and plant nitrogen concentrations were measured during the growing season.
The results showed an inverse relationship between N stress and both Tr and WP*. In other words, increasing N stress led to decreased values of Tr and WP*. Moreover, in the direct simulation approach, WP* changes during the growing season based on the nitrogen nutrition index. In the AquaCrop model, WP* is obtained from a linear regression equation, which is assumed to be constant during the growing season. This factor may cause more errors in biomass simulation. The RRMSE (relative root mean square error) index in biomass simulation by the direct method was, on average, 4% lower for each treatment compared to the semi-quantitative approach. In addition, increased N stress led to increased errors in simulating biomass. Thus, the RRMSE for biomass simulation using the direct method was 26.48 % and 30.96% for treatments under the highest stress, and 9.57% and 15.75 % for non-stressed treatments.
In general, these findings show that integrating the critical nitrogen concentration concept into crop models provides more accurate estimates for crops under nitrogen stress. Therefore, the integration of a direct simulation approach and critical nitrogen concentration concept proves highly effective in examining nitrogen management scenarios for agriculture.
The author contributed to the conceptualization of the article and writing of the original and subsequent drafts.
Data available on request from the author.
The author would like to thank all participants of the present study.
The author avoided from data fabrication and falsification.
The author declare no conflict of interest.
)