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| Effects of meteorological factors on different grades of winter wheat growth in the Huang-Huai-Hai Plain, China |
| HUANG Qing, WANG Li-min, CHEN Zhong-xin, LIU Hang |
| Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China |
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Abstract The sown area of winter wheat in the Huang-Huai-Hai (HHH) Plain accounts for over 65% of the total sown area of winter wheat in China. Thus, it is important to monitor the winter wheat growth condition and reveal the main factors that influence its dynamics. This study assessed the winter wheat growth condition based on remote sensing data, and investigated the correlations between different grades of winter wheat growth and major meteorological factors corresponding. First, winter wheat growth condition from sowing until maturity stage during 2011–2012 were assessed based on moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) time-series dataset. Next, correlation analysis and geographical information system (GIS) spatial analysis methods were used to analyze the lag correlations between different grades of winter wheat growth in each phenophase and the meteorological factors that corresponded to the phenophases. The results showed that the winter wheat growth conditions varied over time and space in the study area. Irrespective of the grades of winter wheat growth, the correlation coefficients between the winter wheat growth condition and the cumulative precipitation were higher than zero lag (synchronous precipitation) and one lag (pre-phenophase precipitation) based on the average values of seven phenophases. This showed that the cumulative precipitation during the entire growing season had a greater effect on winter wheat growth than the synchronous precipitation and the pre-phenophase precipitation. The effects of temperature on winter wheat growth varied according to different grades of winter wheat growth based on the average values of seven phenophases. Winter wheat with a better-than-average growth condition had a stronger correlation with synchronous temperature, winter wheat with a normal growth condition had a stronger correlation with the cumulative temperature, and winter wheat with a worse-than-average growth condition had a stronger correlation with the pre-phenophase temperature. This study may facilitate a better understanding of the quantitative correlations between different grades of crop growth and meteorological factors, and the adjustment of field management measures to ensure a high crop yield.
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Received: 30 September 2015
Accepted:
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| Fund: This project was financially supported by the National Nonprofit Institute Research Grant of Chinese Academy of Agricultural Sciences (IARRP-2015-8) and the European Union seventh framework “MODEXTREME” (modelling vegetation response to extreme events) programme (613817). |
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Corresponding Authors:
HUANG Qing, Tel: +86-10-82105052, E-mail: huangqing@caas.cn
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Cite this article:
HUANG Qing, WANG Li-min, CHEN Zhong-xin, LIU Hang.
2016.
Effects of meteorological factors on different grades of winter wheat growth in the Huang-Huai-Hai Plain, China. Journal of Integrative Agriculture, 15(11): 2647-2657.
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| Arnella N W, Livermore M J L, Kovats S, Levy P E, Nicholls R, Parry M L, Gaffin S R. 2004. Climate and socio-economic scenarios for global-scale climate change impacts assessments: Characterising the SRES storylines. Global Environmental Change, 14, 3–20.Bachelet D, Gay C A. 1993. The impacts of climate change on rice yield: A comparison of four model performances. Ecological Modelling, 65, 71–93.Barnwal P, Kotani K. 2013. Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh, India. Ecological Economics, 87, 95–109.Bolton D K, Friedl M A. 2013. Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics. Agricultural and Forest Meteorolology, 173, 74–84.Challinor A J, Simelton E S, Fraser E D G, Hemming D, Collins M. 2010. Increased crop failure due to climate change: assessing adaptation options using models and socio-economic data for wheat in China. Environmental Research Letters, 5, 144–152.Cihlar J. 2000. Land cover mapping of large areas from satellites: Status and research priorities. International Journal of Remote Sensing, 21, 1093–1114.Eklundh L. 2012. Estimating relations between AVHRR NDVI and rainfall in East Africa at 10 days and monthly time scales. International Journal of Remote Sensing, 19, 563–570.Falloon P, Betts R. 2010. Climate impacts on European agriculture and water management in the context of adaptation and mitigation-the importance of an integrated approach. Science of the Total Environment, 408, 5667–5687.Giupponi C, Ramanzin M, Sturaro E, Fuser S. 2006. Climate and land use changes, biodiversity and agri-environmental measures in the Belluno Province, Italy. Environmental Science and Policy, 9, 163–173.Gornall J, Betts R, Burke E, Clark R, Camp J, Willett K, Wiltshire A. 2010. Implications of climate change for agricultural productivity in the early twenty-first century. Philosophical Transactions of the Royal Society of London, 365, 2973–2989.Hmimina G, Dufrêne E, Pontailler J Y, Delpierre N, Aubinet M, Caquet B, de Grandcourt A, Burban B, Flechard C, Granier A, Gross P, Heinesch B, Longdoz B, Moureaux C, Ourcival J M, Rambal S, Saint André L, Soudani K. 2013. Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements. Remote Sensing of Environment, 132, 145–158.Howden S M, Soussana J F, Tubiello F N, Chhetri N, Dunlop M, Meinke H. 2007. Adapting agriculture to climate change. Proceedings of the National Academy of Sciences of the United States of America, 104, 19691–19696.Huang Q, Wu W B, Zhang L, Li D D. 2010. MODIS-NDVI-based crop growth monitoring in China agriculture remote sensing monitoring system. Proceedings of the Institute of Electrical and Electronics Engineers. Second Intelligent Information Technology Application International Conference on Geoscience and Remote Sensing (IITA-GRS). IEEE, Qingdao, China. pp. 287–290.Huang Q, Zhou Q B, Wang L M, Li D D. 2014. Relationship between winter wheat growth grades obtained from remote-sensing and meteorological factor. Transactions of the Chinese Society for Agricultural Machinery, 45, 301–307. (in Chinese)Huang Q, Zhou Q B, Wu W B, Wang L M, Zhang L. 2012. Extraction of planting areas of major crops and crop growth monitoring in Northeast China. Intelligent Automation and Soft Computing, 18, 1023–1033. Iglesias A, Mougou R, Moneo M, Quiroga S. 2011. Towards adaptation of agriculture to climate change in the Mediterranean. Regional Environmental Change, 11, 159–166.Jiang X J, Tang L, Liu X J, Cao W X, Zhu Y. 2013. Spatial and temporal characteristics of rice potential productivity and potential yield increment in main production regions of China. Journal of Integrative Agriculture, 12, 45–56.JRC-MARS. 2005. The monitoring agricultural resources unit mission. [2010-10-20]. http://mars.jrc.ec.europa.euJu H, Lin E D, Wheeler T, Challinor A, Jiang S. 2013. Climate change modelling and its roles to Chinese crops yield. Journal of Integrative Agriculture, 12, 892–902.Kutcher H R, Warland J S, Brandt S A. 2010. Temperature and precipitation effects on canola yields in Saskatchewan, Canada. Agricultural & Forest Meteorology, 150, 161–165.Lee J J, Phillips D L, Benson V W. 1999. Soil erosion and climate change: Assessing potential impacts and adaptation practices. Journal of Soil and Water Conservation, 54, 529–536.Liu L L, Xu H M. 2007. Change of NDVI of main vegetation and their relationship with meteorological factors in Yellow River Basin. Chinese Journal of Agrometeorology, 28, 334–337. (in Chinese)Liu M G. 1997. Atlas of Physical Geography of China. China Map Publishing House, Beijing. pp. 40–50. (in Chinese)Li X T, Huang S F, Li J R, Mu M, Yang H B, Sun T. 2007. Correlation analysis on NDVI variation and climatic factor of the yellow river delta in recent years. Yellow River, 29, 20–22. (in Chinese)Meng J H, Wu B F, Li Q Z, Zhang L. 2006. Design and implementation of a global crop growth monitoring system by remote sensing. World Science-Technology Research and Development, 28, 41–44. (in Chinese)Mo X G, Liu S X, Lin Z H, Guo R P. 2009. Regional crop yield, water consumption and water use efficiency and their responses to climate change in the North China Plain. Agriculture, Ecosystems & Environment, 134, 67–78.Mo Y. 2007. Changes of vegetation cover in the Huang-Huai-Hai basin and the correlation with climate factors. MSc thesis. Nanjing University of Information Science and Technology, China. pp. 31–38. (in Chinese)Moriondo M, Bindi M, Kundzewicz Z W, Szwed M, Chorynski A, Matczak P, Radziejewski M, McEvoy D, Wreford A. 2010. Impact and adaptation opportunities for European agriculture in response to climatic change and variability. Mitigation and Adaptation Strategies for Global Change, 15, 657–679.NAZC (National Agricultural Zoning Committee). 1989. Agricultural Natural Resources and Regional Planning of China. Agricultural Press, Beijing. pp. 50–80. (in Chinese)Olesen J E, Bindi M. 2002. Consequences of climate change for European agricultural productivity, land use and policy. European Journal of Agronomy, 16, 239–262.Preston B L, Yuen E J, Westaway R M. 2011. Putting vulnerability to climate change on the map: A review of approaches, benefits, and risks. Sustainability Science, 6, 177–202.Raskin P D. 2005. Global scenarios: Background review for the millennium ecosystem assessment. Ecosystytem, 8, 133–142.Reilly J. 1995. Climate change and global agriculture: Recent findings and issues. American Journal of Agricultural Economics, 77, 727–733.Schultz P A, Halpert M S. 1993. Global correlation of temperature, NDVI and precipitation. Advances in Space Research, 13, 277–280.Smit B, McNabb D, Smithers J. 1996. Agricultural adaptation to climatic variation. Climatic Change, 33, 7–29.Smit B, Skinner M W. 2002. Adaptation options in agriculture to climate change: A typology. Mitigation and Adaptation Strategies for Global Change, 7, 85–114.Smith W N, Grant B B, Desjardins R L, Kroebel R, Li C, Qian B, Worth D E, McConkey B G, Drury C F. 2013. Assessing the effects of climate change on crop production and GHG emissions in Canada. Agriculture, Ecosystems and Environent, 179, 139–150.Southworth J, Randolph J C, Habeck M, Doering O C, Pfeifer R A, Rao D G, Johnston J J. 2000. Consequences of future climate change and changing climate variability on maize yields in the Midwestern United States. Agriculture, Ecosystems & Environment, 82, 139–158.Sr R A P. 2005. Land use and climate change. Science, 310, 1625–1626.Stuczyiński T, Demidowicz G, Deputat T, Górski T, Krasowicz S, Ku? J. 2000. Adaptation scenarios of agriculture in Poland to future climate changes. Environmental Monitoring and Assessment, 61, 133–144.Thomas A. 2006. Climatic change and potential agricultural productivity in China. Erdkunde, 60, 157–172.Trnka M, Eitzinger J, Hlavinka P, Dubrovsky M, Semeradova D, Stepanek P, Thaler S, Zalud Z, Mozny M, Formayer H. 2009. Climate-driven changes of production regions in Central Europe. Plant, Soil and Environment, 55, 257–266.USDA (United States Department of Agruculture). 2005. Research, science, and technology. [2011-05-10]. http://www.nass.usda.gov/Research_and_ Science/index.aspViglizzo E F, Roberto Z E, Filippin M C, Pordomingo A J. 1995. Climate variability and agro-ecological change in the Central Pampas of Argentina. Agriculture Ecosystems and Environment, 55, 7–16.Walther G R, Post E, Convey P, Menzel A, Parmesan C, Beebee T J, Fromentin J M, Hoegh-Guldberg O, Bairlein F. 2002. Ecological responses to recent climate change. Nature, 416, 389–395.Wang J H, Zhao C J, Huang W J. 2008. Basis and Application of Quantitative Remote Sensing in Agriculture. Science Press, Beijing. pp. 259–287. (in Chinese)Xiao G J, Zheng F J, Qiu Z J, Yao Y B. 2013. Impact of climate change on water use efficiency by wheat, potato and corn in semiarid areas of China. Agriculture, Ecosystems and Environment, 181, 108–114.Xiong W, Conway D, Holman I, Lin E D. 2008. Evaluation of CERES wheat simulation of wheat production in China. Agronomy Journal, 100, 1720–1728.Xiong W, Matthews R, Holman I, Lin E D, Xu Y L. 2007. Modelling China’s potential maize production at regional scale under climate change. Climatic Change, 85, 433–451. Xu J W, Ju H, Mei X R, Liu Q, Yang J Y. 2015. Simulation on potential effects of drought on winter wheat in Huang-Huai-Hai Plain from 1981 to 2010. Transactions of the Chinese Society of Agricultural Engineering, 31, 150–158. (in Chinese)Xu Y L, Zhang Y, Lin E D, Lin W T, Dong W J, Jones R, Hassell D, Wilson S. 2006. Analyses on the climate change responses over China under SRES B2 scenario using PRECIS. Chinese Science Bulletin, 51, 2260–2267.Ye L M, Xiong W, Li Z G, Yang P, Wu W B, Yang G X, Fu Y J, Zou J Q, Chen Z X, Ranst E V, Tang H J. 2013. Climate change impact on China food security in 2050. Agronony for Sustainable Development, 33, 363–374.Yohe G, Dowlatabadi H. 1999. Risk and uncertainties, analysis and evaluation: Lessons for adaptation and integration. Mitigation and Adaptation Strategies for Global Change, 4, 319–329.Zhai H Q. 1999. Introduction to Agriculture. Higher Education Press, Beijing. pp. 389–391. (in Chinese)Zhang Y H, Lv H Q, Qian Y L. 2014. Spatial-temporal distributions of climatic suitability index of winter wheat over the huanghuaihai region of China in 1987–2012. Chinese Agricultural Science Bulletin, 30, 48–54. (in Chinese) |
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