Transaction on Informatics and Data Science
Vol. 2 No. 2 (2025)

Predicting SPAD Values in Sri Lankan Paddy Rice Fields using UAV-based Vegetation Indices

Fonseka, Ishani (Unknown)
Hewagamage, K.P. (Unknown)
Rathnayake, Upul (Unknown)
Bandara, R.M.U. S (Unknown)
Halloluwa, Thilina (Unknown)



Article Info

Publish Date
01 Oct 2025

Abstract

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

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Journal Info

Abbrev

tids

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Description

Transactions on Informatics and Data Science (TIDS), with ISSN: 3064-1772 (online), is a scientific journal that publishes the latest research in the fields of informatics and data science, focusing on both theoretical advances and practical applications. Published by the Department of Informatics, ...