Drone-Based Multispectral Imaging for Precision Monitoring of Crop Growth Variables
This study aimed to demonstrate the efficacy of drone-assisted crop monitoring in precision agriculture by evaluating the relationships between the NDVI, leaf area index (LAI), and leaf nitrogen content (LNC) in three wheat varieties (DBW-187, HD-3086, PBW-826) under eight nitrogen treatments (N0–N210). The NDVI was derived from drone-based multispectral imagery at the flowering (90 DAS) and grain-filling (108 DAS) stages. Strong correlations were observed between the NDVI, LAI, and LNC, with the R2 values improving from 0.78–0.86 at flowering to 0.88–0.90 at grain filling. These findings highlight the potential of drone-derived indices for efficient crop monitoring, resource use optimization, and yield prediction in precision agriculture.
Authors
- S. C. Tripathi (ORCID: https://orcid.org/0000-0003-3917-9645)
- R. G. Rejith (ORCID: https://orcid.org/0000-0001-7870-8744)
- Rajeev Ranjan (ORCID: https://orcid.org/0000-0003-2233-9147)
- Tarun Teja Kondraju (ORCID: https://orcid.org/0000-0001-7999-7592)
- Ali RA Moursy (ORCID: https://orcid.org/0000-0002-2796-1720)
- Nitesh Kumar (ORCID: https://orcid.org/0000-0002-4929-3954)
- Rabi N. Sahoo
- D. Venkata Reddy (ORCID: https://orcid.org/0009-0005-7326-0035)
- Amrita Bhandari (ORCID: https://orcid.org/0000-0001-7654-2138)
Institutions
- Indian Council of Agricultural Research (IN)
- Indian Institute of Wheat and Barley Research (IN)
- Indian Agricultural Research Institute (IN)
- Sohag University (EG)
Publication Details
- Published
- 2025-05-23
- DOI
- https://doi.org/10.3390/blsf2025041010
- Citations
- 2
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 3.43