Scientia Agricultura Sinica ›› 2023, Vol. 56 ›› Issue (10): 1859-1870.doi: 10.3864/j.issn.0578-1752.2023.10.004

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Effects of Changing Normal and Extreme Climate States on Maize Meteorological Yield in Northeast China

ZHANG WenJing(), ZHAO Jin(), CUI WenQian, LI ManYao, LI E, GONG XiaoYa, YANG XiaoGuang   

  1. College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193
  • Received:2022-04-13 Accepted:2022-06-06 Online:2023-05-16 Published:2023-05-17

Abstract:

【Objective】Northeast China is the main grain production base in China, which has been significantly affected by climate change in recent years. It was of great significance to understand the impact of normal and extreme climate states changes on crop yield in Northeast China for regional crop production and national food security.【Method】In this study, the maize in Northeast China was used as research object, and the main climate factors affecting maize yield were screened to analyze the effects of normal and extreme climate states changes on maize yield in 81 counties in Northeast China from 1980 to 2018.【Result】(1) The average temperature, growing degree-days (GDD), and heat degree-days (HDD) during the maize growth period showed an increasing trend, and the rising rates were 0.34 ℃·(10 a)-1, 47.07 ℃·d·(10 a)-1, and 5.15 ℃·d·(10 a)-1, respectively. The precipitation showed a decreasing trend, with the rate of 7.0 mm·(10 a)-1; the average temperature, GDD, and HDD increased from northeast to southwest, while the precipitation increased from northwest to southeast. (2) The meteorological yield of maize in Northeast China showed an increasing trend from 1980 to 1999, with a rate of 80.93 kg·hm-2·a-1, while it showed a decreasing trend of 46.25 kg·hm-2·a-1 from 2000 to 2018. In terms of spatial distribution, it showed an increasing trend from the middle to the surrounding areas. The area with high yield was concentrated in the eastern part of Heilongjiang. The change of Liaoning was the most stable, and the fluctuation range was stable in the middle area. (3) By the multiple linear regression model, HDD contributed the most to meteorological yield from 1980 to 2018, and the effect was negative, which meant extreme high temperature had the greatest impact on maize yield in Northeast China and caused maize yield reduction; GDD had a positive effect, that is, the average temperature increased maize yield, and the greater GDD, the more yield increased; the precipitation had a negative effect; the interaction between temperature and precipitation had a positive impact on maize yield in Northeast China.【Conclusion】Normal and extreme climate states changes and its impact on maize meteorological yield in Northeast China from 1980 to 2018 were as follow: the normal and extreme temperature showed an overall increasing trend, while the normal precipitation showed a decreasing trend. Extreme high temperatures and normal precipitation led to a decrease in maize yield, but the average temperature increased maize yield, and the extreme high temperature had the greatest impact. In the future, it was necessary to make full use of the average temperature state and minimize the harm caused by extreme high temperature to ensure a high-stable maize production.

Key words: climate change, Northeast China, maize meteorological yield, contribution rate

Fig. 1

Distribution of experimental stations in study areas"

Fig. 2

Changes in the main climate factors during maize growth period in Northeast China from 1980 to 2018"

Fig. 3

Spatial distribution characteristics of climatic factors in Northeast China"

Fig. 4

Variation characteristics of maize yield in Northeast China from 1980 to 2018"

Fig. 5

Spatial distribution characteristics of maize yield in Northeast China"

Table 1

Annual statistics of maize climate yield in Northeast provinces from 1980 to 2018"

省份
Province
气候丰年 Climate abundant year 气候歉年 Climate poor year 正常年份 Normal year
统计基数
Statistical base
占比
Proportion
统计基数
Statistical base
占比
Proportion
统计基数
Statistical base
占比
Proportion
辽宁Liaoning 361 0.367 298 0.303 324 0.329
吉林Jilin 292 0.308 346 0.365 308 0.308
黑龙江Heilongjiang 366 0.356 343 0.334 317 0.325

Table 2

Regression results of meteorological yield of maize in Northeast China"

东北地区 Northeast 省份 Province 时间段 Time period
有交互项
Interactive
无交互项
No interaction
黑龙江
Heilongjiang
吉林
Jilin
辽宁
Liaoning
1980-1999 2000-2018
相关系数
Correlation coefficient
0.167** 0.165** 0.092* 0.195** 0.279** 0.192** 0.2**
PP value <0.001 <0.001 0.037 <0.001 <0.001 <0.001 <0.001

Fig. 6

Contribution rate of climatic factors to meteorological yield"

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