IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v203y2022ics0308521x22001585.html
   My bibliography  Save this article

Historical and projected impacts of climate change and technology on soybean yield in China

Author

Listed:
  • Guo, Shibo
  • Zhang, Zhentao
  • Guo, Erjing
  • Fu, Zhenzhen
  • Gong, Jingjin
  • Yang, Xiaoguang

Abstract

Increasing soybean yield is essential for China. In order to secure the desire soybean yield gains, it is important to understand how changes in climate and technology impact soybean yield.

Suggested Citation

  • Guo, Shibo & Zhang, Zhentao & Guo, Erjing & Fu, Zhenzhen & Gong, Jingjin & Yang, Xiaoguang, 2022. "Historical and projected impacts of climate change and technology on soybean yield in China," Agricultural Systems, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:agisys:v:203:y:2022:i:c:s0308521x22001585
    DOI: 10.1016/j.agsy.2022.103522
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X22001585
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2022.103522?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hampf, Anna C. & Stella, Tommaso & Berg-Mohnicke, Michael & Kawohl, Tobias & Kilian, Markus & Nendel, Claas, 2020. "Future yields of double-cropping systems in the Southern Amazon, Brazil, under climate change and technological development," Agricultural Systems, Elsevier, vol. 177(C).
    2. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    3. Emily Burchfield & Neil Matthews-Pennanen & Justin Schoof & Christopher Lant, 2020. "Changing yields in the Central United States under climate and technological change," Climatic Change, Springer, vol. 159(3), pages 329-346, April.
    4. Xiaoshi Zhou & Wanglin Ma & Gucheng Li & Huanguang Qiu, 2020. "Farm machinery use and maize yields in China: an analysis accounting for selection bias and heterogeneity," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1282-1307, October.
    5. T.A.M. Pugh & C. Müller & J. Elliott & D. Deryng & C. Folberth & S. Olin & E. Schmid & A. Arneth, 2016. "Climate analogues suggest limited potential for intensification of production on current croplands under climate change," Nature Communications, Nature, vol. 7(1), pages 1-8, November.
    6. Deepak K. Ray & Navin Ramankutty & Nathaniel D. Mueller & Paul C. West & Jonathan A. Foley, 2012. "Recent patterns of crop yield growth and stagnation," Nature Communications, Nature, vol. 3(1), pages 1-7, January.
    7. Wang, Bin & Feng, Puyu & Chen, Chao & Liu, De Li & Waters, Cathy & Yu, Qiang, 2019. "Designing wheat ideotypes to cope with future changing climate in South-Eastern Australia," Agricultural Systems, Elsevier, vol. 170(C), pages 9-18.
    8. James Rising & Naresh Devineni, 2020. "Crop switching reduces agricultural losses from climate change in the United States by half under RCP 8.5," Nature Communications, Nature, vol. 11(1), pages 1-7, December.
    9. Zhao, Jiongchao & Wang, Chong & Shi, Xiaoyu & Bo, Xiaozhi & Li, Shuo & Shang, Mengfei & Chen, Fu & Chu, Qingquan, 2021. "Modeling climatically suitable areas for soybean and their shifts across China," Agricultural Systems, Elsevier, vol. 192(C).
    10. Sun, Shuang & Yang, Xiaoguang & Lin, Xiaomao & Sassenrath, Gretchen F. & Li, Kenan, 2018. "Climate-smart management can further improve winter wheat yield in China," Agricultural Systems, Elsevier, vol. 162(C), pages 10-18.
    11. Bernhard Schauberger & Sotirios Archontoulis & Almut Arneth & Juraj Balkovic & Philippe Ciais & Delphine Deryng & Joshua Elliott & Christian Folberth & Nikolay Khabarov & Christoph Müller & Thomas A. , 2017. "Consistent negative response of US crops to high temperatures in observations and crop models," Nature Communications, Nature, vol. 8(1), pages 1-9, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ling, Xiaoxia & Deng, Nanyan & Xiong, Dongliang & Yuan, Shen & Peng, Shaobing & Li, Tao & Huang, Jianliang, 2023. "Effect of variation in the observations on the prediction uncertainty in crop model simulation: Use ORYZA (v3) as a case study," Ecological Modelling, Elsevier, vol. 476(C).
    2. Luo, Li & Sun, Shikun & Xue, Jing & Gao, Zihan & Zhao, Jinfeng & Yin, Yali & Gao, Fei & Luan, Xiaobo, 2023. "Crop yield estimation based on assimilation of crop models and remote sensing data: A systematic evaluation," Agricultural Systems, Elsevier, vol. 210(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Emily Burchfield & Neil Matthews-Pennanen & Justin Schoof & Christopher Lant, 2020. "Changing yields in the Central United States under climate and technological change," Climatic Change, Springer, vol. 159(3), pages 329-346, April.
    2. Ren Yang & Xiuli Luo & Qian Xu & Xin Zhang & Jiapei Wu, 2021. "Measuring the Impact of the Multiple Cropping Index of Cultivated Land during Continuous and Rapid Rise of Urbanization in China: A Study from 2000 to 2015," Land, MDPI, vol. 10(5), pages 1-22, May.
    3. Kamini Yadav & Hatim M. E. Geli, 2021. "Prediction of Crop Yield for New Mexico Based on Climate and Remote Sensing Data for the 1920–2019 Period," Land, MDPI, vol. 10(12), pages 1-27, December.
    4. Haowei Sun & Jinghan Ma & Li Wang, 2023. "Changes in per capita wheat production in China in the context of climate change and population growth," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 15(3), pages 597-612, June.
    5. Chandio, Abbas Ali & Ozdemir, Dicle & Jiang, Yuansheng, 2023. "Modelling the impact of climate change and advanced agricultural technologies on grain output: Recent evidence from China," Ecological Modelling, Elsevier, vol. 485(C).
    6. Tassadit Kourat & Dalila Smadhi & Brahim Mouhouche & Nerdjes Gourari & M. G. Mostofa Amin & Christopher Robin Bryant, 2021. "Assessment of future climate change impact on rainfed wheat yield in the semi-arid Eastern High Plain of Algeria using a crop model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2175-2203, July.
    7. Yang, Meijian & Wang, Guiling, 2023. "Heat stress to jeopardize crop production in the US Corn Belt based on downscaled CMIP5 projections," Agricultural Systems, Elsevier, vol. 211(C).
    8. van Zelm, Rosalie & van der Velde, Marijn & Balkovic, Juraj & Čengić, Mirza & Elshout, Pieter M.F. & Koellner, Thomas & Núñez, Montserrat & Obersteiner, Michael & Schmid, Erwin & Huijbregts, Mark , 2018. "Spatially explicit life cycle impact assessment for soil erosion from global crop production," Ecosystem Services, Elsevier, vol. 30(PB), pages 220-227.
    9. Xiang, Mingtao & Yu, Qiangyi & Li, Yan & Shi, Zhou & Wu, Wenbin, 2022. "Increasing multiple cropping for land use intensification: The role of crop choice," Land Use Policy, Elsevier, vol. 112(C).
    10. He, Liuyue & Xu, Zhenci & Wang, Sufen & Bao, Jianxia & Fan, Yunfei & Daccache, Andre, 2022. "Optimal crop planting pattern can be harmful to reach carbon neutrality: Evidence from food-energy-water-carbon nexus perspective," Applied Energy, Elsevier, vol. 308(C).
    11. Cao, Juan & Zhang, Zhao & Tao, Fulu & Chen, Yi & Luo, Xiangzhong & Xie, Jun, 2023. "Forecasting global crop yields based on El Nino Southern Oscillation early signals," Agricultural Systems, Elsevier, vol. 205(C).
    12. Tamer Khraisha & Keren Arthur, 2018. "Can we have a general theory of financial innovation processes? A conceptual review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-27, December.
    13. Jeetendra Prakash Aryal & Tek B. Sapkota & Ritika Khurana & Arun Khatri-Chhetri & Dil Bahadur Rahut & M. L. Jat, 2020. "Climate change and agriculture in South Asia: adaptation options in smallholder production systems," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5045-5075, August.
    14. Ives, Matthew & Cesaro, Zac & Bramstoft, Rasmus & Bañares-Alcántara, René, 2023. "Facilitating deep decarbonization via sector coupling of green hydrogen and ammonia," INET Oxford Working Papers 2023-04, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    15. Meike Weltin & Silke Hüttel, 2023. "Sustainable Intensification Farming as an Enabler for Farm Eco-Efficiency?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(1), pages 315-342, January.
    16. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    17. Manogna R. L. & Aswini Kumar Mishra, 2022. "Agricultural production efficiency of Indian states: Evidence from data envelopment analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4244-4255, October.
    18. Rada, Nicholas E., 2013. "Agricultural Growth in India: Examining the Post-Green Revolution Transition," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149547, Agricultural and Applied Economics Association.
    19. Terrance Hurley & Jawoo Koo & Kindie Tesfaye, 2018. "Weather risk: how does it change the yield benefits of nitrogen fertilizer and improved maize varieties in sub‐Saharan Africa?," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 711-723, November.
    20. Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:203:y:2022:i:c:s0308521x22001585. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.