Vol.32, NO.4, 2021
Turn off MathJax
Article Contents
Article Navigation >  Journal of Applied Meteorological Science  > 2021  >  32(4): 491-503
Li Hainan, Zhu Lijie, Li Mingqian, et al. Construction of soybean chilling damage indicator and its evolution characteristics in Northeast China. J Appl Meteor Sci, 2021, 32(4): 491-503. DOI:  10.11898/1001-7313.20210410.
Citation: Li Hainan, Zhu Lijie, Li Mingqian, et al. Construction of soybean chilling damage indicator and its evolution characteristics in Northeast China. J Appl Meteor Sci, 2021, 32(4): 491-503. DOI:  10.11898/1001-7313.20210410.
shu

Construction of Soybean Chilling Damage Indicator and Its Evolution Characteristics in Northeast China

DOI: 10.11898/1001-7313.20210410
  • 1.

    College of Agronomy, Shenyang Agricultural University, Shenyang 110866

  • 2.

    Heilongjiang Institute of Meteorological Science, Harbin 150030

  • 3.

    Key Laboratory of Agrometeorological Disasters, Shenyang 110166

  • Received Date: 2021-04-02
  • Rev Recd Date: 2021-06-03
  • Publish Date: 2021-07-31
    Abstract
  • Chilling damage is the major cause of soybean yield reduction in Northeast China. Chilling damage indicator is an important basis for the monitoring and early warning. Taking soybean in Northeast China as the research object, based on daily average temperature data of 98 meteorological stations from 1971 to 2020, the soybean growth period data and historical disaster data of 42 agro-meteorological stations from 1992 to 2020, using heat index as the indicator, the disaster sample sequences of soybean under 5 growth stages and 3 chilling damage levels are constructed by disaster data. Probability distribution fitting and Kolmogorov-Smirnov test methods are used to obtain the probability distribution of chilling damage indicator, and then the t-distribution interval estimation method is used to determine the damage level threshold, and finally the indicator is verified. In addition, the temporal and spatial characteristics of chilling disaster are studied by applying trend analysis, Mann-Kendallt test method and other methods. The results show that the perfect match rate of disaster level and chilling damage indicator is 84.4%. Therefore, this level threshold of the indicator can well reflect the occurrence of soybean chilling damage in Northeast China. Under the same chilling damage level, the threshold value of chilling damage level in the three-leaf-flowering-podding stage is higher, and that in the sowing-emergence-three-leaf stage is relatively lower. Soybean has higher heat demand in the middle and late stage of growth and development, and lower heat demand in the early stage of growth and development. The frequency of chilling damage is the highest in the 1970s, and the mutation occurred around 1993 and then showed a downward trend until 2004. The spatial distribution of chilling injury frequency in each development stage shows the same change characteristics, and the highest value area is the widest in podding-mature stage. The areas with high incidence of cold damage is the Greater Khingan Range in the northernmost of Heilongjiang Province and the Changbai Mountain in the southeast of Jilin Province. And the frequency of chilling damage shows a decreasing trend around this center. With the inter-decadal change, the high-value area gradually shrinks and the low-value area gradually expands northward.
    • FullText(HTML)
    References(47)

  • Fig. 1  Distribution of meteorological stations and agro-meteorological stations in the taget region

    DownLoad: Full-Size Img PowerPoint

    Fig. 2  Chilling damage frequency during the whole growth period of soybean in Northeast China from 1971 to 2020

    DownLoad: Full-Size Img PowerPoint

    Fig. 3  Chilling damage frequency in different growth stages of soybean with total chilling damage frequency in Northeast China from 1971 to 2020

    DownLoad: Full-Size Img PowerPoint

    Fig. 4  M-K statistic curves of chilling damage frequency during the whole growth period of soybean in Northeast China from 1971 to 2020

    DownLoad: Full-Size Img PowerPoint

    Fig. 5  Distribution of chilling damage frequency in the whole growth period and different growth stages of soybean in Northeast China from 1971 to 2020

    DownLoad: Full-Size Img PowerPoint

    Fig. 6  Decadal variation of chilling damage frequency in the whole growth period of soybean in Northeast China from 1971 to 2020

    DownLoad: Full-Size Img PowerPoint

    Table  1  Sample size in different growth stages of soybean with different levels of chilling damage

    发育阶段 轻度 中度 重度
    指标构建 指标检验 指标构建 指标检验 指标构建 指标检验
    播种-出苗 22 5 19 3 5 1
    出苗-三真叶 13 2 19 3 14 3
    三真叶-开花 9 2 11 2 5 1
    开花-结荚 5 1 4 1 7 1
    结荚-成熟 20 4 14 2 4 1
    DownLoad: Download CSV

    Table  2  Three physiological temperatures in different growth stages of soybean

    发育阶段 适宜温度/℃ 下限温度/℃ 上限温度/℃
    播种-出苗 15.0 7.5 26.0
    出苗-三真叶 19.0 10.0 30.0
    三真叶-开花 22.0 13.0 32.0
    开花-结荚 24.0 16.0 32.0
    结荚-成熟 21.0 11.0 28.0
    DownLoad: Download CSV

    Table  3  K-S test for results of 3 functions for fitting heat index samples of soybean

    发育阶段 冷害等级 显著性检验
    正态分布 均匀分布 指数分布
    轻度 0.739 0.144 0.000
    播种-出苗 中度 0.708 0.043 0.001
    重度 0.999 0.438 0.195
    轻度 0.964 0.319 0.000
    出苗-三真叶 中度 0.855 0.033 0.001
    重度 0.875 0.679 0.025
    轻度 0.981 0.259 0.001
    三真叶-开花 中度 0.899 0.024 0.016
    重度 0.999 0.219 0.000
    轻度 0.971 0.875 0.084
    开花-结荚 中度 0.972 0.455 0.094
    重度 0.989 0.106 0.008
    轻度 0.750 0.002 0.000
    结荚-成熟 中度 0.781 0.151 0.004
    重度 0.982 0.718 0.000
    DownLoad: Download CSV

    Table  4  Chilling damage level indicators in different growth stages of soybean in Northeast China based on heat index

    发育阶段 重度冷害 中度冷害 轻度冷害 无冷害
    播种-出苗 (0，58.0] (58.0，65.5] (65.5，71.0] (71.0，100]
    出苗-三真叶 (0，59.5] (59.5，67.5] (67.5，73.5] (73.5，100]
    三真叶-开花 (0，63.0] (63.0，68.0] (68.0，75.5] (75.5，100]
    开花-结荚 (0，63.5] (63.5，69.5] (69.5，78.0] (78.0，100]
    结荚-成熟 (0，62.5] (62.5，68.0] (68.0，75.5] (75.5，100]
    DownLoad: Download CSV

    Table  5  Verification accuracy for chilling damage indicator of soybean (unit: %)

    发育阶段 轻度 中度 重度 总冷害
    播种-出苗 80.0 66.7 100.0 77.8
    出苗-三真叶 100.0 100.0 66.7 87.5
    三真叶-开花 100.0 50.0 100.0 80.0
    开花-结荚 100.0 100.0 100.0 100.0
    结荚-成熟 75.0 100.0 100.0 85.7
    全生育期 85.7 81.8 85.7 84.4
    DownLoad: Download CSV
  • [1]
    Zha T, Zhong X B, Zhou Q Z, et al. Development status of China's soybean industry and strategies of revitalizing. Soyb Sci, 2018, 37(3): 458-463. https://www.cnki.com.cn/Article/CJFDTOTAL-DDKX201803020.htm
    [2]
    Pan X H. Spatio-temporal Variation of Soybean Production in Northeast China and Its Influencing Factors. Changchun: Northeast Institute of Geograph and Agroecology, Chinese Academy of Sciences, 2019.
    [3]
    Qu H H, Zhu H X, Wang Q J, et al. Effects of climate change on soybean growth period and yield in Northeast China. J Northwest Sci-Tech Univ Agric For(Nat Sci), 2014, 42(7): 61-69.
    [4]
    Gai Z J, Liu J Q, Cai L J, et al. Cold damage to soybean and its prevention and control measures: Research progress. J Agric, 2021, 11(1): 7-10;16.
    [5]
    Alexandrov V A, Hoogenboom G. The impact of climate variability and change on crop yield in Bulgaria. Agr Forest Meteo-rol, 2000, 104(4): 315-327. doi:  10.1016/S0168-1923(00)00166-0
    [6]
    Andaya V C, Mackill D J. Mapping of QTLs associated with cold tolerance during the vegetative stage in rice. J Exp Bot, 2003, 54(392): 2579-2585. doi:  10.1093/jxb/erg243
    [7]
    Zhang D W, Du X Y, Liu C Y, et al. Effect of low-temperature stress on physiological indexes of soybean at germination stage. Soyb Sci, 2010, 29(2): 228-232. https://www.cnki.com.cn/Article/CJFDTOTAL-DDKX201002014.htm
    [8]
    Funatsuki H, Matsuba S, Kawaguchi K, et al. Methods for evaluation of soybean chilling tolerance at the reproductive stage under artificial climatic conditions. Plant Breeding, 2010, 123(6): 558-563. doi:  10.1111/j.1439-0523.2004.01008.x
    [9]
    Ikeda T, Ohnishi S, Senda M, et al. A novel major quantitative trait locus controlling seed development at low temperature in soybean(Glycine max). Theor Appl Genet, 2009, 118(8): 1477-1488. doi:  10.1007/s00122-009-0996-3
    [10]
    Tian X, Liu Y, Huang Z, et al. Comparative proteomic analysis of seedling leaves of cold-tolerant and sensitive spring soybean cultivars. Mol Biol Rep, 2015, 42(3): 581-601. doi:  10.1007/s11033-014-3803-4
    [11]
    Chang Y X, Xu K D, Chen C, et al. Salicylic acid mitigating the inhibition of low temperature stress to soybean seedlings. Soyb Sci, 2012, 31(6): 927-931. doi:  10.3969/j.issn.1000-9841.2012.06.015
    [12]
    Zhang Q, Zhao Y X, Wang C Y. Advances in research on major agro-meteorological disaster indexes in China. J Nat Disaster, 2010, 19(6): 40-54. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH201006007.htm
    [13]
    Guo J P. Research progress on agricultural meteorological disaster monitoring and forecasting. J Appl Meteor Sci, 2016, 27(5): 620-630. doi:  10.11898/1001-7313.20160510
    [14]
    Cui Y M, Bi Y H, Zhang D D, et al. Research progress of crop low temperature chilling injury indexes. Modern Agric Sci Tech, 2015(24): 240-241;243. doi:  10.3969/j.issn.1007-5739.2015.24.140
    [15]
    Wang Y H, Wang C Y, Zhang X F. Advances in researches on indexes and risk assessments of crop cold damage. Meteor Sci Technol, 2008, 36(3): 310-317. doi:  10.3969/j.issn.1671-6345.2008.03.011
    [16]
    Wang L X, Kong J W, Li Q, et al. Summary on the main agro-meteorological disasters in Northern China index research. Adv Earth Sci, 2013, 28(6): 627-636. https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ201306002.htm
    [17]
    Ding S S. The climatic analysis of low temperature in summer over the Northeast China and influence for agricultural product. Acta Meteor Sinica, 1980, 38(3): 234-242. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB198003004.htm
    [18]
    Ma S Q, Xi Z X, Ma L W, et al. Test and comparison of suitability of meteorological indictors for rice cold damages in the north of China. Meteor Mon, 2015, 41(6): 778-785. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201506013.htm
    [19]
    Zhen X, Zhang C, Li Y P. Research progress of crop low temperature chilling injury indexes. Northern J Agric, 2017, 45(2): 94-98. https://www.cnki.com.cn/Article/CJFDTOTAL-NMGN201702020.htm
    [20]
    Wang P, Li S, Yan P, et al. Re-exploration into recent cold damage characters in Heilongjiang Province. J Nat Disaster, 2010, 19(1): 143-146. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH201001024.htm
    [21]
    Li R, Guo J P. Improving parameters of nonlinear accumulated temperature model of spring maize in Northeast China. J Appl Meteor Sci, 2018, 29(2): 154-164. doi:  10.11898/1001-7313.20180203
    [22]
    Wang C Y, Zhang J Q, Zhang J H, et al. Comprehensive Agrometeorological Disaster Risk Assessment and Regionalization Re-search. Beijing: China Meteorological Press, 2016: 46. https://www.cnki.com.cn/Article/CJFDTOTAL-ANHE201823128.htm
    [23]
    Gao S H. Dynamic monitoring of growth-delaying type cold damage for corn. J Nat Disaster, 2003, 12(2): 117-121. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH200302020.htm
    [24]
    Liu B C, Wang S L, Zhuang L W, et al. Study of low temperature damage prediction applications in Northeast China based on a scaling-up maize dynamic model. J Appl Meteor Sci, 2003, 14(5): 616-625. http://qikan.camscma.cn/article/id/20030576
    [25]
    Zhu H X, Chen L, Wang Q J, et al. Judgment of corn chilling damage year from 1980 to 2009 in Heilongjiang Province. J Catastr, 2012, 27(1): 44-47;54. https://www.cnki.com.cn/Article/CJFDTOTAL-ZHXU201201008.htm
    [26]
    Ma Y P, Wang S L, Li W J. Chilling disaster factors in maize reproductive stage based on crop growth model. Acta Agron Sin, 2011, 37(9): 1642-1649. https://www.cnki.com.cn/Article/CJFDTOTAL-XBZW201109019.htm
    [27]
    Li Y J. Technical Research in Forecasting the Chilling Damage for Maize of Jilin Provinces. Beijing: Chinese Academy of Meteorological Sciences, 2005.
    [28]
    Guo J P, Tian Z H, Zhang J J. Forecasting models of heat index for corn in Northeast China. J Appl Meteor Sci, 2003, 14(5): 626-633. http://qikan.camscma.cn/article/id/20030577
    [29]
    Wang P J, Huo Z G, Yang J Y, et al. Indicators of chilling damage for spring maize based on heat index in Northeast China. J Appl Meteor Sci, 2019, 30(1): 13-24. doi:  10.11898/1001-7313.20190102
    [30]
    Li X J, Mao W Y, Yang J F, et al. Characterization of growth-delayed cotton cool damage by heat index in the Northern Xinjiang. Cott Sci, 2005, 17(2): 88-93. https://www.cnki.com.cn/Article/CJFDTOTAL-MHXB200502004.htm
    [31]
    Xue Z D, Meng J, Wu Q F. Soybean planting division in Heilongjiang Province based on climate suitability. Soyb Sci, 2019, 38(3): 399-406. https://www.cnki.com.cn/Article/CJFDTOTAL-DDKX201903010.htm
    [32]
    Wen K G. Chinese Meteorological Disasters(Heilongjiang). Beijing: China Meteorological Press, 2007.
    [33]
    Wen K G. Chinese Meteorological Disasters(Jilin). Beijing: China Meteorological Press, 2008.
    [34]
    Wen K G. Chinese Meteorological Disasters(Liaoning). Beijing: China Meteorological Press, 2005.
    [35]
    China Meteorological Administration. China Meteorological Disasters Yearbook(2005-2019). Beijing: China Meteorological Press, 2005-2019.
    [36]
    Yang X F, Yang D G, Tang Y H, et al. Preliminary study on establishment of climate suitability index system for spring soybeans in Northeast China. Seed World, 2009(11): 36-38. https://www.cnki.com.cn/Article/CJFDTOTAL-SJZZ200911024.htm
    [37]
    Gong L J, Wu S, Tian B X, et al. Optimal meteorological indices during the growing season of soybean in Heilongjiang Province. Soyb Sci, 2019, 38(3): 391-398. https://www.cnki.com.cn/Article/CJFDTOTAL-DDKX201903009.htm
    [38]
    Yang J Y, Huo Z G, Wang P J, et al. Occurrence Characteristics of early rice heat disaster in Jiangxi Province. J Appl Meteor Sci, 2020, 31(1): 42-51. doi:  10.11898/1001-7313.20200104
    [39]
    Yang J Y, Huo Z G, Wang P J, et al. Evaluation index construction and hazard risk assessment on apple drought in northern China. J Appl Meteor Sci, 2021, 32(1): 25-37. doi:  10.11898/1001-7313.20210103
    [40]
    Wang T Y, Huo Z G, Li X H, et al. Level indicators and temporal-spatial distribution features of early rice flood disaster in Hunan Province based on different growth stages. Chin J Ecol, 2016, 35(3): 709-718. https://www.cnki.com.cn/Article/CJFDTOTAL-STXZ201603020.htm
    [41]
    Yang J Y, Huo Z G, Wang P J, et al. Dynamic identification of double-early rice heat and its spatiotemporal characteristics in Jiangxi Province, China. Chin J Appl Ecol, 2020, 31(1): 199-207. https://www.cnki.com.cn/Article/CJFDTOTAL-YYSB202001026.htm
    [42]
    Yang H Y, Huo Z G, Yang J Y, et al. Indicators and risk of spring corn waterlogging disaster in Jianghan and west region of Jiangnan. J Appl Meteor Sci, 2017, 28(2): 237-246. doi:  10.11898/1001-7313.20170211
    [43]
    Wang T Y, Huo Z G, Yang J Y, et al. Process grade indicator construction and evolution characteristics of late rice flood in Hunan. J Appl Meteor Sci, 2019, 30(1): 35-48. doi:  10.11898/1001-7313.20190104
    [44]
    Liu L, Sha Y Z, Bai Y M. Regional distribution of main agrometeorological disasters and disaster mitigation strategies in China. J Nat Disaster, 2003, 12(2): 92-97. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH200302015.htm
    [45]
    Tan Y J, Zhang J H, Yao F M, et al. Monitoring and simulation forecasting on crop chilling damage in China: Research progress. Chin J Ecol, 2013, 32(7): 1920-1927. https://www.cnki.com.cn/Article/CJFDTOTAL-STXZ201307038.htm
    [46]
    Lyu J J, Zhu H X, Gong L J, et al. Spatial-temporal characteristics of frost damage on soybean and its effect on soybean yield from 1971 to 2016 in cold regions. Soyb Sci, 2020, 39(2): 260-268. https://www.cnki.com.cn/Article/CJFDTOTAL-DDKX202002014.htm
    [47]
    Ma Y P, Wang S L, Li W J. Monitoring and predicting of maize chilling damage based on crop growth model in Northeast China. Acta Agron Sin, 2011, 37(10): 1868-1878. https://www.cnki.com.cn/Article/CJFDTOTAL-XBZW201110024.htm
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中
  • -->

Catalog

    Figures(6)  / Tables(5)

    Get Citation
    PDF
    XML
    Article views (1334) PDF downloads(110) Cited by()
    • Received : 2021-04-02
    • Accepted : 2021-06-03
    • Published : 2021-07-31
    Journal Online
    Contact

    © 2020 Journal of Applied Meteorological Science   京ICP备15006967号-1

    Supported by Beijing Renhe Information Technology Co. Ltd

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return