IDEAS home Printed from https://ideas.repec.org/a/abq/ijasd1/v6y2024i1p43-51.html
   My bibliography  Save this article

Optimizing Winter Wheat Nitrogen Management: A Remote Sensing Approach for Tiller Density Estimation and Precision Fertilization

Author

Listed:
  • Sadain Raza

    (University of Peshawar)

Abstract

Addressing the global demand for increased cereal productivity and quality, particularly in winter wheat cultivation, necessitates careful nitrogen (N) fertilization management. In high-input systems, improper N fertilizer use contributes to environmental pollution. To enhance N use efficiency, continuous monitoring of N status during crop growth is essential. Manual data collection for biomass and N status is labor-intensive and costly, urging the exploration of rapid and nondestructive techniques. Remote sensing, particularly with sensors on Unmanned Aerial Vehicles (UAVs), offers real-time monitoring with advantages of spatial and temporal flexibility. Tiller density in winter wheat significantly impacts yield, emphasizing the need for accurate and real-time assessment methods. Current tiller density measurement methods are laborious and prone to errors. Remote sensing, offering quantitative biophysical parameters, presents a promising alternative, yet challenges remain in achieving the required accuracy. This study explores the use of aerial indices, specifically NDVI and NDRE, for estimating tiller density in winter wheat. The research integrates field experiments, georeferencing, aerial mapping, UAV data collection, and advanced statistical analyses, conducted in Gujranwala, Pakistan. Results show a strong correlation between aerial NDVI/NDRE and tiller density, providing an alternative to direct measurements. The study proposes nitrogen rate recommendations based on NDVI and NDRE, offering a nuanced approach for effective nitrogen application. The methodology, results, and recommendations contribute valuable insights for optimizing wheat cultivation practices, particularly in nitrogen management, on a larger spatial scale.

Suggested Citation

  • Sadain Raza, 2024. "Optimizing Winter Wheat Nitrogen Management: A Remote Sensing Approach for Tiller Density Estimation and Precision Fertilization," International Journal of Agriculture & Sustainable Development, 50sea, vol. 6(1), pages 43-51, March.
  • Handle: RePEc:abq:ijasd1:v:6:y:2024:i:1:p:43-51
    as

    Download full text from publisher

    File URL: https://journal.xdgen.com/index.php/ijasd/article/view/212/227
    Download Restriction: no

    File URL: https://journal.xdgen.com/index.php/ijasd/article/view/212
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:abq:ijasd1:v:6:y:2024:i:1:p:43-51. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Iqra Nazeer (email available below). General contact details of provider: .

    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.