Advancing sustainable agriculture through remote sensing: spectral reflectance-based prediction of pearl millet growth and yield
DOI:
https://doi.org/10.48165/jefa.2025.20.2.35Keywords:
Pearl millet, SR, NDVI, LAI, dry matter, yieldAbstract
Pearl millet (Pennisetum glaucum L.) is a crucial staple crop in arid and semi-arid regions, serving as a primary source of nutrition and income for millions. Given the increasing global emphasis on eco-friendly farming, integrating precision monitoring tools such as spectral reflectance indices into pearl millet production systems can significantly enhance sustainability. The present experiment was conducted to determine the relationship between spectral indices of various cultivars and their growth parameters and yield, demonstrating how non-invasive, spectral-based assessments can contribute to resource-efficient agriculture. The crop spectral reflectance, within wavelengths ranging from 320 nm to 1100 nm, was measured using a field-portable spectroradiometer between 1000 and 1200 hours across all treatment combinations. Growth and yield were found to be highly influenced by sowing directions, highlighting the importance of precision agronomy for maximizing resource efficiency. The findings reveal significant positive correlations between specific spectral indices (SR and NDVI) and growth parameters (LAI and dry matter) as well as yield. These relationships were analysed from emergence to maturity, with the highest correlation observed during the 50 per cent flowering to milking stage.
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