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作物学报 ›› 2019, Vol. 45 ›› Issue (11): 1725-1734.doi: 10.3724/SP.J.1006.2019.91008

• 耕作栽培·生理生化 • 上一篇    下一篇

不同降水年型下水氮调控对小麦产量及生物量的影响

茹晓雅1,李广2,*(),陈国鹏2,张统帅2,闫丽娟3,*()   

  1. 1 甘肃农业大学信息科学技术学院, 甘肃兰州 730070
    2 甘肃农业大学林学院, 甘肃兰州 730070
    3 甘肃农业大学农学院, 甘肃兰州 730070
  • 收稿日期:2019-01-23 接受日期:2019-06-24 出版日期:2019-11-12 网络出版日期:2019-07-15
  • 通讯作者: 李广,闫丽娟
  • 作者简介:E-mail: 1553415196@qq.com
  • 基金资助:
    本研究由国家自然科学基金项目(31560378);本研究由国家自然科学基金项目(31560343);本研究由国家自然科学基金项目(31660348);甘肃省重点研发计划项目(18YF1NA070);甘肃省高等学校协同创新团队项目(2018C-16)

Regulation effects of water and nitrogen on wheat yield and biomass in different precipitation years

RU Xiao-Ya1,LI Guang2,*(),CHEN Guo-Peng2,ZHANG Tong-Shuai2,YAN Li-Juan3,*()   

  1. 1 College of Information Science and Technology, Gansu Agricultural University, Lanzhou 730070, Gansu, China
    2 College of Forestry, Gansu Agricultural University, Lanzhou 730070, Gansu, China
    3 College of Agronomy, Gansu Agricultural University, Lanzhou 730070, Gansu, China
  • Received:2019-01-23 Accepted:2019-06-24 Published:2019-11-12 Published online:2019-07-15
  • Contact: Guang LI,Li-Juan YAN
  • Supported by:
    The work was supported by the National Natural Science Foundation of China(31560378);The work was supported by the National Natural Science Foundation of China(31560343);The work was supported by the National Natural Science Foundation of China(31660348);the Gansu Provincial Key Research and Development Program(18YF1NA070);the Gansu Provincial Higher Education Collaborative Innovation Team Project(2018C-16)

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摘要：

水和氮是影响西北黄土高原雨养农业区粮食生产的主要因素, 但其增产效应受降水年型影响明显。本水氮调控试验利用APSIM模型在甘肃省定西市安定区1971—2018年气象数据, 分析了不同降水年型下水氮管理对小麦产量和生物量的变异系数、可持续性指数的影响, 明确了各年型产量与施氮量、降水量之间的关系。结果表明, 模型模拟的小麦产量和生物量的决定系数R 2均在0.90以上, 一致性指标D均在0.95以上, 归一化均方根误差(NRMSE)均在15%以下, 表明该模型在研究区具有较好的模型拟合度和适应性。通过二元二次回归方程探讨了其最优产量下的水氮优化组合, 在当年年降水总量的基础上, 干旱年小麦达潜在最优产量时(3492.6 kg hm -2), 降水需增加39.73%, 应施氮182.73 kg hm -2; 平水年小麦达潜在最优产量时(4514.5 kg hm -2), 降水需增加45.26%, 应施氮208.26 kg hm -2; 湿润年小麦达潜在最优产量时(4890.3 kg hm -2), 降水需增加46.31%, 应施氮211.15 kg hm -2。研究结果可为研究区不同降水年型下缓解小麦干旱和养分胁迫, 节约化肥资源和农业可持续性发展提供理论依据。

关键词: 降水年型, APSIM模型, 生物量, 产量

Abstract:

Water and nitrogen are the main factors affecting grain production in the rain-fed agriculture area of the Loess Plateau in Northwest China, but their yield-increasing effects will be affected by the type of precipitation. In this paper, the APSIM model was used to conduct water-nitrogen coupling test based on the meteorological data of the experimental area from 1971 to 2018. The effects of different precipitation years on the variation coefficient and sustainability index of wheat yield and biomass were analyzed. In addition, the relationship between annual yield and nitrogen application rate and precipitation was also discussed. According to the model the wheat yield and biomass determination coefficient R 2 was above 0.90, the D index was above 0.95, and the normalized root mean square error (NRMSE) was below 15%, indicating that the model has good model fitting and adaptability in the study area. Based on natural conventional rainfall in each year, we explored the optimized combination of water and nitrogen for the three types of annual yields using the binary quadratic regression equation. When the potential yield of wheat in drought year reached 3492.6 kg hm -2, the precipitation increased by 39.73% and the nitrogen consumption was 182.73 kg hm -2; when the potential yield of wheat in flat water year reached 4514.5 kg hm -2, the precipitation increased by 45.26%, the nitrogen consumption was 208.26 kg hm -2; and when the potential yield in wet year reached 4890.3 kg hm -2, the precipitation increased by 46.31%, the amount of nitrogen was 211.15 kg hm -2. Among them, precipitation increased on the basis of the total annual precipitation in that year. The research results can provide a theoretical basis for alleviating wheat drought and nutrient stresses in different precipitation years in the study area, saving fertilizer resources and keeping sustainable development of agriculture.

Key words: precipitation year pattern, APSIM model, biomass, yield

表1

土壤参数"

土层
Soil layer (cm)		 田间最大持水量
Drained upper limit (mm mm-1)		 小麦有效
水分下限
Wheat low limit
(mm mm-1)		 容重
Bulk density
(g cm-3)		 萎蔫系数
Wilting coefficient (mm mm-1)		 饱和含水量
Saturated moisture
( mm mm-1)		 有机碳
Organic carbon (%)		 铵态氮
NH4-N
(mg kg-1)		 硝态氮
NO3-N
(mg kg-1)
>0-5 0.27 0.09 1.29 0.08 0.46 0.95 6.30 19.10
>5-10 0.27 0.09 1.23 0.08 0.49 0.95 5.20 15.20
>10-30 0.27 0.09 1.32 0.08 0.45 0.96 5.10 23.10
>30-50 0.27 0.09 1.20 0.08 0.50 0.85 4.90 16.60
>50-80 0.26 0.09 1.14 0.09 0.52 0.54 4.60 16.80
>80-110 0.27 0.10 1.14 0.09 0.52 0.26 4.80 18.20
>110-140 0.27 0.11 1.13 0.11 0.48 0.20 4.80 16.40
>140-170 0.27 0.13 1.12 0.13 0.53 0.26 5.80 13.70
>170-200 0.27 0.15 1.11 0.13 0.53 0.20 4.10 15.40

表2

作物模块参数表"

参数
Parameter		 取值
Value
灌浆到成熟的积温Thermal time start filling to mature 580
春化系数Sensitivity to vernalisation 1
光周期系数Sensitivity to photoperiod 2
最大灌浆速率Maximum grain filling rate 2.30
分蘖重Weight of tiller (g tiller-1) 1.22
单株重Weight of single plant (g) 4
株高Stem length (mm) 1000
播种期地表蒸发系数(土壤) Surface evaporation coefficient (soil) during sowing 7.20
发芽期地表蒸发系数(土壤) Surface evaporation coefficient (soil) during germination 6.20

表3

不同降水年型"

年型
Model year		 平均降水量
Average
precipitation		 变异系数
Variable
coefficient		 合计(年)
Total (year)		 年份
Year
干旱年
Dry year		 136.4 0.19 13 1971 1974 1975 1976 1982 1995 1997 2000
2001 2008 2009 2011 2017
平水年
Normal year		 202.5 0.043 20 1972 1973 1980 1981 1983 1985 1987 1988
1989 1992 1994 1996 2002 2004 2006 2007
2010 2014 2015 2016
湿润年
Wet year		 270.0 0.092 15 1977 1978 1979 1984 1986 1990 1991 1993
1998 1999 2003 2005 2012 2013 2018

表4

降水量和施氮量耦合模拟试验"

因素Factor N1 N2 N3 N4 N5
P1 P1N1 P1N2 P1N3 P1N4 P1N5
P2 P2N1 P2N2 P2N3 P2N4 P2N5
P3 P3N1 P3N2 P3N3 P3N4 P3N5
P4 P4N1 P4N2 P4N3 P4N4 P4N5
P5 P5N1 P5N2 P5N3 P5N4 P5N5

图1

小麦产量和其成熟期的生物量模拟值和实测值的线性回归拟合"

图2

2002-2009年小麦生物量的模拟值和实测值对比"

图3

不同年型水氮处理下的产量及生物量"

表5

小麦平均变异系数及平均可持续性指数"

年型Model year Y-CV B-CV Y-SYI B-SYI
干旱年Dry year 54.72 55.97 29.08 27.98
平水年Normal year 54.99 50.94 32.00 28.88
湿润年Wet year 40.85 39.51 55.29 39.58

图4

不同年型小麦产量的变异系数"

图5

不同年型小麦产量的可持续性指数"

图6

不同年型下产量的三维曲面图"

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