Vol.35, NO.5, 2024
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Article Navigation >  Journal of Applied Meteorological Science  > 2024  >  35(5): 619-628
Song Yanling, Zhou Guangsheng, Guo Jianping, et al. Influence of different sowing dates on yield and quality of corn Xianyu 335. J Appl Meteor Sci, 2024, 35(5): 619-628. DOI:  10.11898/1001-7313.20240509.
Citation: Song Yanling, Zhou Guangsheng, Guo Jianping, et al. Influence of different sowing dates on yield and quality of corn Xianyu 335. J Appl Meteor Sci, 2024, 35(5): 619-628. DOI:  10.11898/1001-7313.20240509.
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Influence of Different Sowing Dates on Yield and Quality of Corn Xianyu 335

DOI: 10.11898/1001-7313.20240509
  • 1.

    State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081

  • 2.

    Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science &Technology, Nanjing 210044

  • 3.

    CMA-CAU Jointly Laboratory of Agriculture Addressing Climate Change, Beijing 100081

  • 4.

    School of Geo-Science & Technology, Zhengzhou University, Zhengzhou 450052

  • 5.

    College of Hydrology and Water Resources Engineering, Nanjing University of Information Science & Technology, Nanjing 210044

  • 6.

    Yushu Meteorological Bureau of Jilin, Yushu 130400

  • Received Date: 2024-06-13
  • Rev Recd Date: 2024-07-10
  • Publish Date: 2024-09-30
    Abstract
  • Using data from Yushu Agricultural Meteorological Station of Jilin from 2018 to 2023, the impact of different sowing dates of corn is investigated focusing on its growth and yield composition as well as grain quality under global warming. It is also debated whether adjusting the sowing date of corn could be a measure for agriculture to adapt to climate change. Results show that the utilization efficiency of accumulated temperature during the growing season of corn varies with different sowing dates. The accumulated temperature is the highest in the first sowing date and lowest in the fourth sowing date, with an average decrease of 8.3% compared to the first sowing date. Different sowing dates of corn have an impact on the growing period. The duration of the first sowing date for corn is extended by an average of 7.5 days compared to the normal sowing date, while durations of the third and fourth sowing dates are shortened by 5.7 days and 13.8 days, respectively. Different sowing dates have an impact on the yield structure of corn. In the first sowing date, there is an increase in the weight of 100 grains of corn in 2 years during 6 years, while a decrease by 4.8% and 8.7% in the third and fourth sowing dates compared to the normal sowing date. The average number of grains per plant in the first sowing date increases by 0.2%, while decreases by 6.0% and 9.3% in the third and fourth sowing date. Overall, delaying the corn sowing date by 10 days and 20 days results in an average yield reduction of 10.9% and 17.1%. Sowing corn 10 days earlier could increase the yield in some years. The change in sowing dates has little effect on the quality of grains. Therefore, an early corn sowing date can be utilized as a strategy to adapt to climate change in certain regions of Northeast China.
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    References(33)

  • Fig. 1  Accumulated temperature (no less than 10 ℃) for different sowing dates of corn from 2018 to 2023

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    Fig. 1  Accumulated temperature (no less than 10 ℃) for different sowing dates of corn from 2018 to 2023

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    Fig. 2  Precipitation for different sowing dates of corn from 2018 to 2023

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    Fig. 2  Precipitation for different sowing dates of corn from 2018 to 2023

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    Fig. 3  Growing season length for different sowing dates of corn from 2018 to 2023

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    Fig. 3  Growing season length for different sowing dates of corn from 2018 to 2023

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    Fig. 4  grain weight for different sowing dates of corn from 2018 to 2023

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    Fig. 4  grain weight for different sowing dates of corn from 2018 to 2023

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    Fig. 5  Number of grains per plant for different sowing dates of corn from 2018 to 2023

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    Fig. 5  Number of grains per plant for different sowing dates of corn from 2018 to 2023

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    Fig. 6  Yield for different sowing dates of corn from 2018 to 2023

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    Fig. 6  Yield for different sowing dates of corn from 2018 to 2023

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    Fig. 7  Relationship between yield and accumulated temperature (no less than 10 ℃) (a) as well as precipitation(b) during the growing season for different sowing dates of corn from 2018 to 2023

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    Fig. 7  Relationship between yield and accumulated temperature (no less than 10 ℃) (a) as well as precipitation(b) during the growing season for different sowing dates of corn from 2018 to 2023

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    Fig. 8  Starch content(a) and protein content(b) of corn grains for different sowing dates from 2018 to 2023

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    Fig. 8  Starch content(a) and protein content(b) of corn grains for different sowing dates from 2018 to 2023

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  • [1]
    IPCC(Intergovermental Panel on Climate Change).Climate Change, the Physical Science Basis, 2013.
    [2]
    IPCC(Intergovernmental Panel on Climate Change). Climate Change, the Physical Science Basis, 2021.
    [3]
    IPCC(Intergovermental Panel on Climate Change). Summary for Policymakers//Global Warming of 1.5 ℃, an IPCC Special Report on the Impacts of Global Warming of 1.5 ℃ above Pre-industrial Levels and Related Global Greenhouse Gas Emission Pathways in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development and Efforts to Eradicate Poverty, 2018.
    [4]
    Cheng C S, Auld H, Li Q, et al. Possible impacts of climate change on extreme weather events at local scale in south- central Canada. Climatic Change, 2012(3/4): 963-979.
    [5]
    Jiao M Y, Zhou G S, Zhang Z Q, et al. Blue Book of Agriculture for Addressing Climate Change. Beijing: Social Sciences Academic Press, 2016.
    [6]
    National Bureau of Statistics. China Statistical Yearbook. Beijing: China Statistics Press, 2023.
    [7]
    Song Y L, Wang J L. The Influence of Agriculture Meteorological Disasters on Agriculture in China under Climate Change. Beijing: China Meteorological Press, 2017.
    [8]
    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. doi:  10.3969/j.issn.1001-7313.2003.05.013
    [9]
    Wang H R, Liu D M, Chen P S, et al. Distribution of maturity types of maize based on accumulated temperature rezone in Northeast China. Chinese J Agric Resour Reg Plan, 2022, 43(5): 102-112.
    [10]
    Huo Z G, Zhang H Y, Li C H, et al. Review on high temperature heat damage of maize in China. J Appl Meteor Sci, 2023, 34(1): 1-14.
    [11]
    Yang L, Han L J, Song J L, et al. Monitoring and evaluation of high temperature and heat damage of summer maize based on remote sensing data. J Appl Meteor Sci, 2020, 31(6): 749-758.
    [12]
    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.
    [13]
    Liu B C, Wang S L, Zhuang L W, et al. Study of low temperature damage prediction applications in EN, China based on a scaling-up maize dynamic model. J Appl Meteor Sci, 2003, 14(5): 616-625. doi:  10.3969/j.issn.1001-7313.2003.05.012
    [14]
    Feng X Y, Zhou G S. Modification of leaf water content for the photosynthetic and biochemical mechanism model of C4 plant. J Appl Meteor Sci, 2022, 33(3): 375-384.
    [15]
    Lu H Q, Qian S, Yang F Y, et al. Estimation of actual evapotranspiration for maize field in North China. J Appl Meteor Sci, 2003, 14(6): 726-732.
    [16]
    Guo J P, Luan Q, Wang J X, et al. Model construction of rainfall interception by maize canopy. J Appl Meteor Sci, 2020, 31(4): 397-404.
    [17]
    Song Y L, Wang J L, Tian J F, et al. The spring maize drought index in Northeast China based on meteorological drought index. J Appl Meteor Sci, 2019, 30(1): 25-34.
    [18]
    Cai F, Mi N, Ming H Q, et al. Effects of improving evapotranspiration parameterization scheme on WOFOST model performance in simulating maize drought stress process. J Appl Meteor Sci, 2021, 32(1): 52-64.
    [19]
    Chen Y Y, Wang P J, Zhang Y D, et al. Comparison of drought recognition of spring maize in Northeast China based on 3 remote sensing indices. J Appl Meteor Sci, 2022, 33(4): 466-476.
    [20]
    Li Y, Wang Z W, Huo Z G, et al. Experiments of water stress on root/shoot growth and yield of summer maize. J Appl Meteor Sci, 2020, 31(1): 83-94.
    [21]
    Song Y L. Global research progress of drought indices. J Appl Meteor Sci, 2022, 33(5): 513-526.
    [22]
    Mi Q C, Gao X N, Li Y, et al. Application of deep learning method to drought prediction. J Appl Meteor Sci, 2022, 33(1): 104-114.
    [23]
    Wu W, Jing Y S, Ma Y P, et al. Light response characteristics of summer maize at different growth stages under drought. J Appl Meteor Sci, 2013, 24(6): 723-730. doi:  10.3969/j.issn.1001-7313.2013.06.009
    [24]
    Xu Y Q, Liu H N, Liu C S, et al. Study on risk assessment of maize rainstorm and flood disaster in Heilongjiang Province. Chinese Agric Sci Bull, 2023, 39(30): 94-100. doi:  10.11924/j.issn.1000-6850.casb2022-0880
    [25]
    Zheng J P, Wang C Y. Impact of chilling temperature and drought on corn physiological process in seedling stage. J Appl Meteor Sci, 2006, 17(1): 119-123. doi:  10.3969/j.issn.1001-7313.2006.01.017
    [26]
    Wei R J, Song Y B, Wang X. Method for dynamic forecast of corn yield based on climatic suitability. J Appl Meteor Sci, 2009, 20(5): 622-627. doi:  10.3969/j.issn.1001-7313.2009.05.014
    [27]
    Qi D L, Zhu J Q. Effects of drought-flood abrupt alternation on the characteristics of leaf senescence and grain yield of maize. Trans Chinese Soc Agric Eng, 2024, 40(5): 141-147.
    [28]
    Mu J, Zhao J F, Guo J P. Response of spring maize growth stage to climate change in Northeast China over the past 30 years. J Appl Meteor Sci, 2014, 25(6): 680-689.
    [29]
    Luan W J, Shen X J, Li W C, et al. Climate change in the growing season of maize in northern Ningxia yellow irrigation area and its impact on climate yield. Acta Agric Univ Jiangxiensis, 2023, 45(4): 841-854.
    [30]
    Xu Y H, Li S Y. Impact of climate change on climatic resources utilization efficiency of wheat and maize in Henan Province. Agric Res Arid Areas, 2019, 37(5): 218-225.
    [31]
    Zhao F, Li X F, Lin W N, et al. Impact of climate change on climate productivity potential of maize. Agric Eng, 2019, 9(8): 132-134.
    [32]
    China Meteorological Administration. Agricultural Meteorological Observation(Volume I). Beijing: China Meteorological Press, 1993.
    [33]
    National Health Commission of the People's Republic of China, National Medical Products Administration. National Standard of the People's Republic of China, National Food Safety Standards-determination of Protein in Foods. GB5009.5-2016, 2016.
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    • Received : 2024-06-13
    • Accepted : 2024-07-10
    • Published : 2024-09-30
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