有效积温与不同供氮水平夏玉米干物质和氮素积累定量化研究

doi:10.3864/j.issn.0578-1752.2022.15.009

摘要/Abstract

摘要：

【目的】探究基于有效积温的不同供氮水平夏玉米干物质和氮素积累动态预测模型及其特征参数,以期为利用有效积温预测夏玉米干物质和氮素积累提供理论依据。【方法】在河北廊坊进行两年大田试验（2019—2020年）,以郑单958为试验材料,利用归一化法,通过模型筛选拟合不同供氮水平夏玉米干物质和氮素积累基于播种后有效积温的归一化Gompertz模型,并利用增长速率曲线及其特征参数定量分析夏玉米干物质和氮素积累特征。【结果】（1）在本试验条件下,当磷钾肥适量时,随施氮量的增加夏玉米最大干物质和氮素积累量持续增加。（2）以有效积温为自变量建立的夏玉米干物质和氮素积累量的归一化Gompertz模型具有较好的生物学意义,方程的决定系数分别为0.9962—0.9988和0.9887—0.9922。利用第2年数据进行模型验证,模拟值和实测值的相关系数分别0.9933—0.9959和0.9830—0.9923,标准化的均方根误差分别为6.64%—16.86%和7.31%—12.68%,预测效果达到良好水平。（3）不同供氮水平夏玉米干物质和氮素积累的增长速率均表现为“单峰曲线”,其变化与供氮水平关系密切,在处理间表现为：适量施肥条件下,增长速率曲线呈现上升快下降也快的特点,减肥处理增长速率曲线呈现上升慢下降也慢的特点。（4）夏玉米播种后干物质和氮素积累快增期有效积温范围分别为709.35—1 722.54 ℃·d和482.50—1 507.61 ℃·d,氮素积累达最大速率所需有效积温为995.05 ℃·d,小于干物质积累达最大速率对积温的需求（1 215.94 ℃·d）。供氮水平明显影响夏玉米干物质和氮素积累进入快增期、缓增期、达到最大增长速率所需积温,同时还影响最大增长速率和快增期平均增长速率;与不施氮肥处理相比,适量氮肥处理夏玉米进入各关键期所需有效积温明显减少,关键期增长速率明显增加。【结论】归一化Gompertz模型不仅能够很好地模拟和预测不同供氮水平夏玉米干物质和氮素积累随有效积温的动态变化,还明确了有效积温与干物质和氮素积累的定量化关系。基于有效积温的Gompertz模型可以用来预测作物长势和最佳施肥时期,具有较强的应用价值。

关键词: 有效积温, 供氮水平, 夏玉米, 干物质积累, 氮素积累, 定量化

Abstract:

【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

陈杨,徐孟泽,王玉红,白由路,卢艳丽,王磊. 有效积温与不同供氮水平夏玉米干物质和氮素积累定量化研究[J]. 中国农业科学, 2022, 55(15): 2973-2987.

CHEN Yang,XU MengZe,WANG YuHong,BAI YouLu,LU YanLi,WANG Lei. Quantitative Study on Effective Accumulated Temperature and Dry Matter and Nitrogen Accumulation of Summer Maize Under Different Nitrogen Supply Levels[J]. Scientia Agricultura Sinica, 2022, 55(15): 2973-2987.

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链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2022.15.009

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编号Number	方程Equation	公式Formula	参数个数Number of parameters
1	MMF方程 MMF equation	y=(ab+cx^d)/(b+x^d)	4
2	Gompertz方程 Gompertz equation	y=ae^-exp(^b-cx⁾	3
3	Richards方程 Richards equation	y=a/(1+e^b-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

处理 Treatment	最大干物质积累量 Maximum dry matter accumulation (kg·hm^-2)		最大氮素积累量 Maximum nitrogen accumulation (kg·hm^-2)
处理 Treatment	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

编号 Number	模型 Simulation model	参数 Parameter				标准差 SD	决定系数 R²
编号 Number	模型 Simulation model	a	b	c	d	标准差 SD	决定系数 R²
1	y=(ab+cx^d)/(b+x^d)	-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+e^b-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

编号 Number	模型 Simulation model	参数 Parameter				标准差 SD	决定系数 R²
编号 Number	模型 Simulation model	a	b	c	d	标准差 SD	决定系数 R²
1	y=(ab+cx^d)/(b+x^d)	-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+e^b-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

指标 Indicator	处理 Treatment	参数Parameter			标准差 SD	相关系数 R²
指标 Indicator	处理 Treatment	a	b	c	标准差 SD	相关系数 R²
相对干物质积累量 Relative dry matter accumulation	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**
相对氮素积累量 Relative nitrogen accumulation	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**