Zhang Yanqun, Wang Jiandong, Zhao Yuefen, Gong Shihong, Sui Juan. Simulation and verification of photosynthesis-stomatal conductance coupled model under different nitrogen application rates in winter wheat with drip irrigation[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(10): 124-130. DOI: 10.11975/j.issn.1002-6819.2018.10.015
    Citation: Zhang Yanqun, Wang Jiandong, Zhao Yuefen, Gong Shihong, Sui Juan. Simulation and verification of photosynthesis-stomatal conductance coupled model under different nitrogen application rates in winter wheat with drip irrigation[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2018, 34(10): 124-130. DOI: 10.11975/j.issn.1002-6819.2018.10.015

    Simulation and verification of photosynthesis-stomatal conductance coupled model under different nitrogen application rates in winter wheat with drip irrigation

    • Abstract: Aiming at the phenomenon of excess nitrogen (N) application rate in winter wheat field in North China Plain, measuring and modelling photosynthetic rates under different N rates is helpful to understand the physiological basis of the influence of reducing traditional N application rates on crop yield. This study set up 3 amounts of N rates, i.e. 290, 190 and 110 kg/hm2, as high (N3), middle (N2) and low N (N1) treatments, respectively in drip irrigation winter wheat field in 2 consecutive growing seasons (2012-2014). The coupled model of photosynthesis and stomatal conductance was established to model photosynthetic rates. Photosynthetic rates to intercellular CO2 concentration response curves (An-Ci curves) were measured in 2014 to determine key parameters of the model from the heading stage to harvest stage. Daily dynamics of photosynthetic rates were measured in 2013 as the verification data of the coupled model. The results showed that the apparent maximum carboxylation rate of Rubisco (Vcmax) and maximum electron transfer rate (Jmax) was significantly affected by N treatments. The measured Vcmax varied from 84.5 to 153.3 μmol/(m2·s) and Jmax varied from 156.5 to 236.2 μmol/(m2·s) during the measurements and among treatments. Differences of Vcmax and Jmax among treatments were more significant when the measurement dates close to the harvest stage. During the filling stage (May 21st to 23rd), only Vcmax and Jmax of the low N treatment (N1) was significantly lower than that of high N treatment (N3), the corresponding values of the middle N treatment (N2) were not significant lower than those of N3. During the milking stage (June 2nd to 3rd), however, the Vcmax and Jmax of both N2 and N1 were significantly lower than those of N3. There was no significant difference in the ratio of Jmax/Vcmax among treatments during the three measurements. The ratio of Jmax/Vcmax gradually increased along with the advancing of growing stages and changed from 1.49 to 2.00 during the measurements. The differences of Vcmax among treatments could be quantified by leaf mass N content. Then the Jmax value can be calculated according to the ratio of Jmax/Vcmax. The slope (g1) and intercept (g0) of the stomatal conductance sub-model were changed with different N application. During the filling stage (May 21st to 23rd), it was found that the N3 treatment with the highest g0 and the smallest g1. The analytical solution of the photosynthesis model and the Ball-Berry stomatal conductance model was derived to solve the coupled model. Considering the difference between the key parameters, the simulation results of the coupling model for photosynthetic rate from the daily process was good, with the average absolute error were 2.11 and 2.23 μmol/(m2·s) for the 2 measurements in 2013 and the differences between simulated and measured photosynthetic rate were less than 5%. The prediction of the model also showed that different parameters have different effects on the simulation results of photosynthetic rate. For example, although the g0 of stomatal conductance sub-model is often relatively small, it will cause large error in the simulation of photosynthetic rate under low light intensity, while some researchers may neglect this parameter when running the model. The model can be used to simulate photosynthetic rates under change of single physiological or environmental factor and change of multi factors, so as to better predict the yield changes.
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