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Impact of Climate Warming on Cotton Growth and Yields in China and Pakistan: A Regional Perspective

Author

Listed:
  • Adnan Arshad

    (College of Resources and Environmental Sciences, China Agricultural University, Yuanmingyuan West Rd. No.2, Haidian District, Beijing 100193, China)

  • Muhammad Ali Raza

    (College of Agronomy, Sichuan Agricultural University, Chengdu 625014, China)

  • Yue Zhang

    (College of Resources and Environmental Sciences, China Agricultural University, Yuanmingyuan West Rd. No.2, Haidian District, Beijing 100193, China)

  • Lizhen Zhang

    (College of Resources and Environmental Sciences, China Agricultural University, Yuanmingyuan West Rd. No.2, Haidian District, Beijing 100193, China)

  • Xuejiao Wang

    (Xinjiang Agro-meteorological Observatory, Urumqi 830002, China)

  • Mukhtar Ahmed

    (Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, P.O. Box 7070, SE-750 07 Uppsala, Sweden
    Department of Agronomy, Pir Mehr Ali Shah, Arid Agriculture University, Rawalpindi 46000, Pakistan)

  • Muhammad Habib-ur-Rehman

    (Institute of Crop Science and Resource Conservation (INRES) University Bonn, 53115 Bonn, Germany
    Department of Agronomy, Muhammad Nawaz Shareef Agriculture University, Multan 60800, Pakistan
    AgWeatherNet Program, Washington State University, Prosser, Washington, DC 99350, USA)

Abstract

Year to year change in weather poses serious threats to agriculture globally, especially in developing countries. Global climate models simulate an increase in global temperature between 2.9 to 5.5 °C till 2060, and crop production is highly vulnerable to climate warming trends. Extreme temperature causes a significant reduction in crop yields by negatively regulating the crop phenology. Therefore, to evaluate warming impact on cotton ( Gossypium hirsutum L.) production and management practices, we quantified agrometeorological data of 30 years by applying multiple crop modelling tools to compute the expected rise in temperature, impact of crop phenology, yield loss, provision of agrometeorology-services, agronomic technologies, and adaptation to climate-smart agriculture. Model projections of 15 agrometeorology stations showed that the growing duration of the sowing-boll opening and sowing-harvesting stages was reduced by 2.30 to 5.66 days decade −1 and 4.23 days decade −1 , respectively, in Pakistan. Temperature rise in China also advanced the planting dates, sowing emergence, 3–5 leaves, budding anthesis, full-bloom, cleft-boll, boll-opening, and boll-opening filling by 24.4, 26.2, 24.8, 23.3, 22.6, 15.8, 14.6, 5.4, 2.9, and 8.0 days. Furthermore, present findings exhibited that the warming effect of sowing-harvest time was observed 2.16 days premature, and delayed for 8.2, 2.4, and 5.3 days in the 1970s, 1980s, and 1990s in China. APSIM-cotton quantification revealed that the sowing, emergence, flowering, and maturity stages were negatively correlated with temperature −2.03, −1.93, −1.09, and −0.42 days °C −1 on average, respectively. This study also provided insight into the adaptation of smart and better cotton by improving agrotechnological services.

Suggested Citation

  • Adnan Arshad & Muhammad Ali Raza & Yue Zhang & Lizhen Zhang & Xuejiao Wang & Mukhtar Ahmed & Muhammad Habib-ur-Rehman, 2021. "Impact of Climate Warming on Cotton Growth and Yields in China and Pakistan: A Regional Perspective," Agriculture, MDPI, vol. 11(2), pages 1-22, January.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:2:p:97-:d:486514
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    References listed on IDEAS

    as
    1. Muhammad Ali Imran & Asghar Ali & Muhammad Ashfaq & Sarfraz Hassan & Richard Culas & Chunbo Ma, 2018. "Impact of Climate Smart Agriculture (CSA) Practices on Cotton Production and Livelihood of Farmers in Punjab, Pakistan," Sustainability, MDPI, vol. 10(6), pages 1-20, June.
    2. Amin, Asad & Nasim, Wajid & Mubeen, Muhammad & Ahmad, Ashfaq & Nadeem, Muhammad & Urich, Peter & Fahad, Shah & Ahmad, Shakeel & Wajid, Aftab & Tabassum, Fareeha & Hammad, Hafiz Mohkum & Sultana, Syeda, 2018. "Simulated CSM-CROPGRO-cotton yield under projected future climate by SimCLIM for southern Punjab, Pakistan," Agricultural Systems, Elsevier, vol. 167(C), pages 213-222.
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    Cited by:

    1. Zoia Arshad Awan & Tasneem Khaliq & Muhammad Masood Akhtar & Asad Imran & Muhammad Irfan & Muhammad Jarrar Ahmed & Ashfaq Ahmad, 2021. "Building Climate-Resilient Cotton Production System for Changing Climate Scenarios Using the DSSAT Model," Sustainability, MDPI, vol. 13(19), pages 1-26, September.
    2. Li, Na & Li, Yi & Yang, Qiliang & Biswas, Asim & Dong, Hezhong, 2024. "Simulating climate change impacts on cotton using AquaCrop model in China," Agricultural Systems, Elsevier, vol. 216(C).
    3. Yanxi Zhao & Dengpan Xiao & Huizi Bai & Jianzhao Tang & De Li Liu & Yongqing Qi & Yanjun Shen, 2022. "The Prediction of Wheat Yield in the North China Plain by Coupling Crop Model with Machine Learning Algorithms," Agriculture, MDPI, vol. 13(1), pages 1-19, December.
    4. Yanxi Zhao & Dengpan Xiao & Huizi Bai & Jianzhao Tang & Deli Liu, 2022. "Future Projection for Climate Suitability of Summer Maize in the North China Plain," Agriculture, MDPI, vol. 12(3), pages 1-20, February.

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