Journal of Agronomy and Field Innovations

Background: Pearl millet is suffering from a lack of nitrogen, which makes nitrogen fertilizer a necessity when taking care of this crop. Using leaf tissue analysis or SPAD measurements is difficult and labor-intensive; moreover, they cannot be used in the field.
Objective: The study analyzes the efficiency of different indices derived from multispectral satellite data for the quantitative assessment of nitrogen.
Methods: The images acquired by Sentinel-2, Landsat 8, and Landsat 9 are taken at five stages of plant growth and processed with the help of Google Earth Engine and QGIS. Various indices such as NDVI, GNDVI, NDRE, SAVI, EVI, and chlorophyll index are used to analyze the correlation between nitrogen, SPAD data, and crop productivity.
Results: The NDRE and chlorophyll indices proved to be superior to the NDVI in their correlation with around leaf nitrogen content. The accuracy of the Landsat-derived results was lower due to the resolution nature of Landsat data.
Conclusion: Red-edge-based vegetation indices have demonstrated their ability to be used in pearl millet nitrogen status assessment with the least amount of negative impact on the environment.