Scientia Agricultura Sinica ›› 2022, Vol. 55 ›› Issue (15): 2973-2987.doi: 10.3864/j.issn.0578-1752.2022.15.009


Quantitative Study on Effective Accumulated Temperature and Dry Matter and Nitrogen Accumulation of Summer Maize Under Different Nitrogen Supply Levels

CHEN Yang(),XU MengZe,WANG YuHong,BAI YouLu,LU YanLi(),WANG Lei()   

  1. Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture and Rural Affairs, Beijing 100081
  • Received:2021-06-25 Accepted:2021-09-10 Online:2022-08-01 Published:2022-08-02
  • Contact: YanLi LU,Lei WANG;;


【Objective】This paper explored the dynamic prediction model and characteristic parameters of dry matter and nitrogen accumulation in summer maize with different nitrogen supply levels based on effective accumulated temperature, in order to provide a theoretical basis for using effective accumulated temperature to predict summer maize dry matter and nitrogen accumulation.【Method】This study was based on a two-year field experiment in Langfang, Hebei Province (2019-2020), using Zhengdan 958 as the test material, and using the normalization method to fit the dry matter and nitrogen accumulation of summer maize with different nitrogen supply levels through model screening. Based on the normalized Gompertz model of effective accumulated temperature after sowing, and using the growth rate curve and its characteristic parameters, the dry matter and nitrogen accumulation characteristics of summer maize were quantitatively analyzed.【Result】(1) Under the experimental conditions, when the amount of phosphorus and potassium fertilizer was appropriate, the maximum dry matter and nitrogen accumulation of summer maize continued to increase with the increase of nitrogen application rate. (2) The normalized Gompertz model of summer maize dry matter and nitrogen accumulation established with effective accumulated temperature as the independent variable had the good biological significance. The coefficients of determination of the equation were 0.9962-0.9988 and 0.9887-0.9922, respectively. Using the second-year data for model verification, the correlation coefficients of the simulated and measured values were 0.9933-0.9959 and 0.9830-0.9923, and the standardized root mean square errors were 6.64%-16.86% and 7.31%-12.68%, respectively. The prediction effect was good. (3) The growth rate of dry matter and nitrogen accumulation of summer maize at different nitrogen supply levels all showed a “single peak curve”, and its change was closely related to the nitrogen supply level. The performance between treatments was: under the condition of moderate fertilization, the growth rate curve had the characteristics of fast rising and falling, and the growth rate curve of weight loss treatment had the characteristics of slow rising and falling. (4) The effective accumulated temperature ranges of dry matter and nitrogen accumulation during the rapid increase period of summer maize after sowing were 709.35-1 722.54 and 482.50-1 507.61 ℃·d, respectively, and the effective accumulated temperature required for the maximum rate showed that nitrogen accumulation (995.05 ℃·d) was less than dry matter accumulation (1 215.94 ℃·d). Nitrogen supply level obviously affected the accumulation of dry matter and nitrogen in summer maize to enter the accumulation temperature required for the rapid increase period, the accumulated temperature required for the slow increase period, the accumulated temperature required for the maximum increase rate, the maximum increase rate, and the average increase rate during the rapid increase period. Compared with nitrogen fertilizer treatment, the effective accumulated temperature required for summer maize to enter each critical period was significantly reduced, and the growth rate during the critical period increased significantly.【Conclusion】The normalized Gompertz model could not only simulate and predict the dynamic changes of summer maize dry matter and nitrogen accumulation with effective accumulated temperature with different nitrogen supply levels, but also clarify the quantitative relationship between effective accumulated temperature and dry matter and nitrogen accumulation. The Gompertz model based on effective accumulated temperature could be used to predict crop growth and optimal fertilization period, and had strong application value..

Key words: effective accumulated temperature, nitrogen supply level, summer maize, dry matter accumulation, nitrogen accumulation, quantification

Table 1

Nonlinear regression equation"

编号Number 方程Equation 公式Formula 参数个数Number of parameters
1 MMF方程 MMF equation y=(ab+cxd)/(b+xd) 4
2 Gompertz方程 Gompertz equation y=ae-exp(b-cx) 3
3 Richards方程 Richards equation y=a/(1+eb-cx)1/d 4
4 余弦函数 Cosine function y=a+b×cos(cx+d) 4
5 有理方程 Rational equation y=(a+bx)/(1+cx+dx2) 4
6 三次方程 Cubic equation y=a+bx+cx2+dx3 4

Fig. 1

Dynamic changes of dry matter accumulation of summer maize with different nitrogen supply levels with effective accumulated temperature"

Fig. 2

Dynamic changes of nitrogen accumulation in summer maize with different nitrogen supply levels with effective accumulated temperature"

Table 2

Effects of different nitrogen supply levels on the dry matter and nitrogen accumulation of summer maize"

Maximum dry matter accumulation (kg·hm-2)
Maximum nitrogen accumulation (kg·hm-2)
2019 2020 2019 2020
N0 26862.31±1634.69b 24111.16±1880.32b 264.87±29.92b 201.84±17.84b
N1 29271.52±1806.12ab 28996.05±340.83a 314.32±26.66ab 273.14±23.92a
N2 30714.31±580.10a 30089.04±1831.44a 342.93±5.98a 280.08±23.28a
N3 30936.35±1896.94a 29624.14±313.14a 343.09±23.74a 292.98±30.90a
平均 Average 29446.12 28205.1 316.3 262.01

Table 3

Relative dry matter accumulation model of summer maize"

Simulation model
参数 Parameter 标准差
a b c d
1 y=(ab+cxd)/(b+xd) -0.0055 0.4904 1.5119 3.5484 0.0095 0.9996
2 y=ae-exp(b-cx) 1.4484 2.3009 3.3307 0.0098 0.9996
3 y=a/(1+eb-cx)1/d 1.3829 0.1135 3.6825 0.0884 0.0101 0.9996
4 y=a+b×cos(cx+d) 0.6370 0.6553 2.6040 2.7469 0.0148 0.9992
5 y=(a+bx)/(1+cx+dx2) -0.0524 0.2708 -1.7309 0.9534 0.0163 0.9990
6 y=a+bx+cx2+dx3 0.0334 -0.8299 3.1237 -1.2881 0.0181 0.9987

Table 4

Model of relative nitrogen accumulation in summer maize"

Simulation model
参数 Parameter 标准差
a b c d
1 y=(ab+cxd)/(b+xd) -0.0453 0.7468 1.6946 2.1874 0.0300 0.9959
2 y=a+bx+cx2+dx3 -0.0350 -0.1294 2.4306 -1.3177 0.0320 0.9953
3 y=a+b×cos(cx+d) 0.4984 0.5434 2.5225 3.1609 0.0329 0.9951
4 y=ae-exp(b-cx) 1.1717 1.8794 3.3462 0.0341 0.9945
5 y=a/(1+eb-cx)1/d 1.1435 -0.6146 3.5800 0.0715 0.0357 0.9942
6 y=(a+bx)/(1+cx+dx2) -0.0949 0.6130 -1.0822 0.6260 0.0377 0.9935

Table 5

Dynamic equation parameters of RDMA and RNA in summer maize with different nitrogen supply levels"

参数Parameter 标准差
a b c
Relative dry matter
N0 1.53 2.32 3.22 0.0268 0.9969**
N1 1.39 2.40 3.52 0.0298 0.9962**
N2 1.36 2.26 3.48 0.0174 0.9988**
N3 1.54 2.26 3.19 0.0253 0.9975**
Relative nitrogen
N0 1.32 1.84 2.99 0.0481 0.9887**
N1 1.22 1.86 3.22 0.0460 0.9893**
N2 1.05 2.01 4.01 0.0412 0.9922**
N3 1.26 1.82 3.29 0.0451 0.9907**

Table 6

Inspection and evaluation of the measured and simulated values of summer maize RDMA and RNA"

Relative dry matter
N0 0.9958 0.0535 12.00
N1 0.9933 0.0751 16.86
N2 0.9959 0.0296 6.64
N3 0.9944 0.0482 10.82
Relative nitrogen
N0 0.9882 0.0529 10.58
N1 0.9888 0.0564 11.19
N2 0.9923 0.0384 7.31
N3 0.9830 0.0644 12.68

Fig. 3

Measured and simulated values of summer maize RDMA and RNA"

Fig. 4

The growth rate of summer maize RDMA and RNA with different nitrogen supply levels changes dynamically with the relative effective accumulated temperature"

Table 7

The characteristic parameters of the Gompertz model for the dynamic changes of DMA and NA of summer maize"

速率峰值参数 Rate peak parameter 快增期参数 Rapid increase period parameters
T1 (℃·d)
T2 (℃·d)
T3 (℃·d)
V2 (kg·hm-2·(℃·d)-1)
相对值 实际值 相对值 实际值 相对值 实际值 相对值 实际值 相对值 实际值
Dry matter
N0 1.8112 27.64c 0.7229 1269.82a 0.4234 743.71a 1.0225 1795.94a 1.5597 23.80c
N1 1.8014 29.95b 0.6821 1198.17ab 0.4084 717.40a 0.9559 1678.94ab 1.5512 25.79b
N2 1.7350 30.33ab 0.6509 1143.27b 0.3745 657.75b 0.9273 1628.79b 1.4940 26.12ab
N3 1.8027 31.66a 0.7131 1252.50a 0.4091 718.52a 1.0171 1786.49ab 1.5523 27.26a
平均Average 1.7876 29.90 0.6923 1215.94 0.4038 709.35 0.9807 1722.54 1.5393 25.74
Nitrogen accumulation
N0 1.4512 0.2129c 0.6152 1101.93a 0.2934 521.40a 0.9369 1682.47a 1.2496 0.1833c
N1 1.4459 0.2561b 0.5788 1021.59ab 0.2801 492.50a 0.8775 1550.68ab 1.2451 0.2205b
N2 1.5470 0.2999a 0.5007 884.90b 0.2610 458.53a 0.7405 1311.27b 1.3321 0.2583a
N3 1.5269 0.2988a 0.5530 971.79ab 0.2603 457.57a 0.8456 1486.01ab 1.3148 0.2573a
平均Average 1.4927 0.2669 0.5619 995.05 0.2737 482.50 0.8501 1507.61 1.2854 0.2299
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