Predicting SPAD Values in Sri Lankan Paddy Rice Fields using UAV-based Vegetation Indices - Fonseka, Ishani; Hewagamage, K.P.; Rathnayake, Upul; Bandara, R.M.U. S; Halloluwa, Thilina (Transactions on Informatics and Data Science, 2025)
In Sri Lanka, the overuse of fertilizers by farmers leads to financial losses and environmental concerns. Due to the high cost and limited availability of SPAD equipment, UAV-based imagery presents a practical and cost-effective alternative for monitoring nitrogen levels in crops. This study evaluates the use of UAV-based multispectral imagery to assess the nitrogen status of rice crops and compares various vegetation indices with SPAD readings. Focusing on the BG300 rice variety. several vegetation indices were compared with SPAD readings using a Linear Regression (LR) model. Among them, NDVI showed the strongest correlation (R = 0.81106), confirming its reliability as an indicator of nitrogen status. This approach offers a cost-effective solution for Sri Lanka’s rice farming sector, aiding farmers in making more informed decisions to reduce fertilizer use and mitigate environmental impacts