IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v307y2025ics037837742400533x.html
   My bibliography  Save this article

Productivity of water and heat resources and cotton yield response to cropping pattern and planting density in cotton fields in arid area

Author

Listed:
  • Dong, Zhenlin
  • Wan, Sumei
  • Ma, Yunzhen
  • Wang, Jinbin
  • Feng, Lu
  • Zhai, Yunlong
  • Li, Tiantian
  • Cui, Zhengjun
  • Wang, Jian
  • Yang, Beifang
  • Yang, Ze
  • Zhao, Zhan
  • Yan, Fei
  • Xiong, Shiwu
  • Li, Yabing
  • Chen, Guodong

Abstract

The individual effects of cropping patterns and planting densities on cotton yield formation and resource utilization have been extensively studied in the arid regions of western China, but research on their combined impacts remains limited. This study hypothesized that optimizing cropping patterns and planting densities would enhance hydrothermal resource productivity and cotton yield in the region. To test this, a two-year field experiment (2022–2023) employed a split-plot design with two main planting patterns (four rows per film and six rows per film) and three planting densities (low, medium, and high) as subplots. Using internet of sensor technology, soil temperature and moisture were monitored to assess their spatial and temporal distributions. The effects of planting pattern, density, and their interactions on cotton yield, yield components, biomass accumulation, and water and heat utilization were evaluated. The interaction between pattern and density significantly influenced cotton yield, harvest index, and water productivity, with planting density exerting a stronger effect on water productivity than planting pattern. In 2023, the four-row pattern at low and medium densities produced higher yields than the high-density treatment. Over the two-year period, the four-row, low-density treatment achieved 8.77 % and 13.40 % greater water productivity than the medium- and high-density treatments, respectively, while the six-row, medium-density treatment outperformed low and high densities, increasing water productivity by 3.64 % and 8.74 %. Seed cotton yield was also higher, with a 2.88 % and 6.15 % increase in the four-row, low-density treatment and an 8.51 % and 4.79 % increase in the six-row, medium-density treatment compared to higher-density treatments. The study further analyzed spatial and temporal variations in soil moisture and temperature and their link to resource productivity and cotton yield. Soil water content differences ranged from 0.10 to 0.90 mm in the four-row pattern and from 0.20 to 0.70 mm in the six-row pattern between low- and high-density treatments. Planting density significantly affected soil temperature during flowering and boll-setting stages. Lint and seed cotton yields showed positive correlations with soil heat production efficiency (PEsoil) and negative correlations with water production efficiency (WPc), with optimal patterns observed in the four-row, low-density and six-row, medium-density treatments. These findings explain why these configurations led to a higher harvest index and enhanced hydrothermal resource productivity. This study provides valuable insights into the optimal configurations for maximizing cotton yield and resource efficiency in arid regions, supporting sustainable cotton production under resource-limited conditions.

Suggested Citation

  • Dong, Zhenlin & Wan, Sumei & Ma, Yunzhen & Wang, Jinbin & Feng, Lu & Zhai, Yunlong & Li, Tiantian & Cui, Zhengjun & Wang, Jian & Yang, Beifang & Yang, Ze & Zhao, Zhan & Yan, Fei & Xiong, Shiwu & Li, Y, 2025. "Productivity of water and heat resources and cotton yield response to cropping pattern and planting density in cotton fields in arid area," Agricultural Water Management, Elsevier, vol. 307(C).
  • Handle: RePEc:eee:agiwat:v:307:y:2025:i:c:s037837742400533x
    DOI: 10.1016/j.agwat.2024.109197
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037837742400533X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2024.109197?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. Fernández, J.E. & Alcon, F. & Diaz-Espejo, A. & Hernandez-Santana, V. & Cuevas, M.V., 2020. "Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard," Agricultural Water Management, Elsevier, vol. 237(C).
    2. Liu, Kai & Liao, Huan & Hao, Haibo & Hou, Zhenan, 2024. "Water and nitrogen supply at spatially distinct locations improves cotton water productivity and nitrogen use efficiency and yield under drip irrigation," Agricultural Water Management, Elsevier, vol. 296(C).
    3. Song, Qilong & Zhang, Fangfang & Li, Xin & Yue, Shanchao & Luo, Zhuzhu & Li, Shiqing, 2024. "Understanding of maize root responses to changes in water status induced by plastic film mulching cultivation on the Loess Plateau, China," Agricultural Water Management, Elsevier, vol. 301(C).
    4. Jian, Huajian & Gao, Zhen & Guo, Yingying & Xu, Xinyan & Li, Xiaoyu & Yu, Meijia & Liu, Guangzhou & Bian, Dahong & Cui, Yanhong & Du, Xiong, 2024. "Supplemental irrigation mitigates yield loss of maize through reducing canopy temperature under heat stress," Agricultural Water Management, Elsevier, vol. 299(C).
    5. Ozturk, Omer Faruk & Shukla, Manoj K. & Stringam, Blair & Picchioni, Geno A. & Gard, Charlotte, 2018. "Irrigation with brackish water changes evapotranspiration, growth and ion uptake of halophytes," Agricultural Water Management, Elsevier, vol. 195(C), pages 142-153.
    6. Kuang, Naikun & Hao, Chuangchuang & Liu, Dazhong & Maimaitiming, Maitusong & Xiaokaitijiang, Kasmu & Zhou, Yunpeng & Li, Yunkai, 2024. "Modeling of cotton yield responses to different irrigation strategies in Southern Xinjiang Region,China," Agricultural Water Management, Elsevier, vol. 303(C).
    7. Zong, Rui & Wang, Zhenhua & Wu, Qiang & Guo, Li & Lin, Henry, 2020. "Characteristics of carbon emissions in cotton fields under mulched drip irrigation," Agricultural Water Management, Elsevier, vol. 231(C).
    8. Chen, Zongkui & Niu, Yuping & Zhao, Ruihai & Han, Chunli & Han, Huanyong & Luo, Honghai, 2019. "The combination of limited irrigation and high plant density optimizes canopy structure and improves the water use efficiency of cotton," Agricultural Water Management, Elsevier, vol. 218(C), pages 139-148.
    9. Ai, Pengrui & Ma, Yingjie & Hai, Ying, 2021. "Influence of jujube/cotton intercropping on soil temperature and crop evapotranspiration in an arid area," Agricultural Water Management, Elsevier, vol. 256(C).
    10. Satoh, Yuhi & Kakiuchi, Hideki, 2021. "Calibration method to address influences of temperature and electrical conductivity for a low-cost soil water content sensor in the agricultural field," Agricultural Water Management, Elsevier, vol. 255(C).
    11. 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).
    12. Akbari, Fatemeh & Shourian, Mojtaba & Moridi, Ali, 2022. "Assessment of the climate change impacts on the watershed-scale optimal crop pattern using a surface-groundwater interaction hydro-agronomic model," Agricultural Water Management, Elsevier, vol. 265(C).
    13. Shareef, Muhammad & Gui, Dongwei & Zeng, Fanjiang & Waqas, Muhammad & Zhang, Bo & Iqbal, Hassan, 2018. "Water productivity, growth, and physiological assessment of deficit irrigated cotton on hyperarid desert-oases in northwest China," Agricultural Water Management, Elsevier, vol. 206(C), pages 1-10.
    14. Ruixiu Sui & Daniel K. Fisher & Edward M. Barnes, 2012. "Soil Moisture and Plant Canopy Temperature Sensing for Irrigation Application in Cotton," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 4(12), pages 1-93, November.
    15. Antonio M. Silva Filho & José R. S. Silva & Glaciano M. Fernandes & Lucas D. S. Morais & Antonio P. Coimbra & Wesley P. Calixto, 2021. "Root System Analysis and Influence of Moisture on Soil Electrical Properties," Energies, MDPI, vol. 14(21), pages 1-17, October.
    Full references (including those not matched with items on IDEAS)

    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. Xue, Run & Zhang, Chuan & Yan, Haofang & Disasa, Kinde Negessa & Lakhiar, Imran Ali & Akhlaq, Muhammad & Hameed, Muhammad Usman & Li, Jun & Ren, Jiangtao & Deng, Shuaishuai & Wang, Biyu & Bao, Rongxua, 2025. "Determination of the optimal frequency and duration of micro-spray patterns for high-temperature environment tomatoes based on the Fuzzy Borda model," Agricultural Water Management, Elsevier, vol. 307(C).
    2. Zhang, Yuehong & Li, Xianyue & Šimůnek, Jiří & Shi, Haibin & Chen, Ning & Hu, Qi, 2023. "Quantifying water and salt movement in a soil-plant system of a corn field using HYDRUS (2D/3D) and the stable isotope method," Agricultural Water Management, Elsevier, vol. 288(C).
    3. Li, Nannan & Shi, Xiaojuan & Zhang, Humei & Shi, Feng & Zhang, Hongxia & Liang, Qi & Hao, Xianzhe & Luo, Honghai & Wang, Jun, 2024. "Optimizing irrigation strategies to improve the soil microenvironment and enhance cotton water productivity under deep drip irrigation," Agricultural Water Management, Elsevier, vol. 305(C).
    4. Nicolette Matthews & Bennie Grové & Johannes Hendrikus Barnard, 2025. "Economic Analysis of Segmented Soil Salinity Management Using Current Irrigation Technology," Agriculture, MDPI, vol. 15(8), pages 1-14, April.
    5. Arbizu-Milagro, Julia & Castillo-Ruiz, Francisco J. & Tascón, Alberto & Peña, Jose M., 2023. "Effects of regulated, precision and continuous deficit irrigation on the growth and productivity of a young super high-density olive orchard," Agricultural Water Management, Elsevier, vol. 286(C).
    6. Cameira, Maria do Rosário & Rodrigo, Isabel & Garção, Andreia & Neves, Manuela & Ferreira, Antónia & Paredes, Paula, 2024. "Linking participatory approach and rapid appraisal methods to select potential innovations in collective irrigation systems," Agricultural Water Management, Elsevier, vol. 299(C).
    7. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    8. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    9. Feng, Z.Y. & Qin, T. & Du, X.Z. & Sheng, F. & Li, C.F., 2021. "Effects of irrigation regime and rice variety on greenhouse gas emissions and grain yields from paddy fields in central China," Agricultural Water Management, Elsevier, vol. 250(C).
    10. Giulio Sperandio & Mauro Pagano & Andrea Acampora & Vincenzo Civitarese & Carla Cedrola & Paolo Mattei & Roberto Tomasone, 2022. "Deficit Irrigation for Efficiency and Water Saving in Poplar Plantations," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    11. Wesley P. Calixto & Carlos L. B. Silva & Viviane M. Gomes & Marcio R. C. Reis & Antonio M. Silva Filho & Antonio P. Coimbra & Gabriel A. Wainer, 2022. "Application of the Horizontal Soil Stratification and Lateral Profiling Methods for 3D Mapping of the Soil Electrical Resistivity," Energies, MDPI, vol. 15(6), pages 1-24, March.
    12. Wen, Shenglin & Cui, Ningbo & Wang, Yaosheng & Gong, Daozhi & Xing, Liwen & Wu, Zongjun & Zhang, Yixuan & Zhao, Long & Fan, Junliang & Wang, Zhihui, 2024. "Optimizing deficit drip irrigation to improve yield,quality, and water productivity of apple in Loess Plateau of China," Agricultural Water Management, Elsevier, vol. 296(C).
    13. Guodong Chen & Yunlong Zhai & Jianguo Zhou & Yanfang Li & Jiao Lin & Sumei Wan & Quanzhong Wu, 2022. "Optimizing Maize Belt Width Enhances Productivity in Wheat/Maize Intercropping Systems," Sustainability, MDPI, vol. 14(23), pages 1-16, December.
    14. Hafiz Shahzad Ahmad & Muhammad Imran & Fiaz Ahmad & Shah Rukh & Rao Muhammad Ikram & Hafiz Muhammad Rafique & Zafar Iqbal & Abdulaziz Abdullah Alsahli & Mohammed Nasser Alyemeni & Shafaqat Ali & Tanve, 2021. "Improving Water Use Efficiency through Reduced Irrigation for Sustainable Cotton Production," Sustainability, MDPI, vol. 13(7), pages 1-12, April.
    15. Hou, Chenli & Tian, Delong & Xu, Bing & Ren, Jie & Hao, Lei & Chen, Ning & Li, Xianyue, 2021. "Use of the stable oxygen isotope method to evaluate the difference in water consumption and utilization strategy between alfalfa and maize fields in an arid shallow groundwater area," Agricultural Water Management, Elsevier, vol. 256(C).
    16. Liu, Haijun & Yin, Congyan & Gao, Zhuangzhuang & Hou, Lizhu, 2021. "Evaluation of cucumber yield, economic benefit and water productivity under different soil matric potentials in solar greenhouses in North China," Agricultural Water Management, Elsevier, vol. 243(C).
    17. Zhang, Tibin & Zou, Yufeng & Kisekka, Isaya & Biswas, Asim & Cai, Huanjie, 2021. "Comparison of different irrigation methods to synergistically improve maize’s yield, water productivity and economic benefits in an arid irrigation area," Agricultural Water Management, Elsevier, vol. 243(C).
    18. Wang, Feng & Meng, Haofeng & Xie, Ruizhi & Wang, Keru & Ming, Bo & Hou, Peng & Xue, Jun & Li, Shaokun, 2023. "Optimizing deficit irrigation and regulated deficit irrigation methods increases water productivity in maize," Agricultural Water Management, Elsevier, vol. 280(C).
    19. Sun, Guangzhao & Chen, Shuaihong & Zhang, Shaowu & Chen, Shaomin & Liu, Jie & He, Qiong & Hu, Tiantian & Zhang, Fucang, 2024. "Responses of leaf nitrogen status and leaf area index to water and nitrogen application and their relationship with apple orchard productivity," Agricultural Water Management, Elsevier, vol. 296(C).
    20. Tomaz, Alexandra & Palma, José Ferro & Ramos, Tiago & Costa, Maria Natividade & Rosa, Elizabete & Santos, Marta & Boteta, Luís & Dôres, José & Patanita, Manuel, 2021. "Yield, technological quality and water footprints of wheat under Mediterranean climate conditions: A field experiment to evaluate the effects of irrigation and nitrogen fertilization strategies," Agricultural Water Management, Elsevier, vol. 258(C).

    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:agiwat:v:307:y:2025:i:c:s037837742400533x. 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/agwat .

    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.