Equation to Predict Paddy Biomass Macronutrient Availability in Saline Soil Using Soil-Vegetation Indices from Multispectral UAV

Aditya Putra (University of Brawijaya)
Qoid Luqmanul Hakim (University of Brawijaya)
Alberth Fernando Sitorus (University of Brawijaya)
Martiana Adelyanti (University of Brawijaya)
Istika Nita (University of Brawijaya)
Sudarto (University of Brawijaya)
Michelle Talisia Sugiarto (University of Brawijaya)
Novandi Rizky Prasetya (University of Brawijaya)

Agriprima : Journal of Applied Agricultural Sciences
Vol 10 No 1 (2026): MARCH

The average paddy production in Indonesia has decreased by -6,83% in the last five years (2015-2019), and salinity is the main factor causing the problem with an effect of 42% compared to climate change (21%) and drought (9%). Salinity will inhibit the availability of macronutrients in rice biomass, which must be detected quickly to avoid crop failure. This study aimed to obtain a formula equation to quickly estimate the macronutrient content in paddy biomass due to salinity. The formula equation was formed based on an algorithm resulting from the transformation of the SR, NGRDI, NDVI, TNDVI, and GNDVI index from the multispectral UAV and Nitrogen (N), Phosphorus (P), and Potassium (K) content in paddy biomass in saline soil. When the salinity source's distance gets closer, the macronutrient content decreases, and the transformation index value increases. The SR index is the most sensitive index to macronutrient content, indicated by the highest correlation value compared to other indices. Formula to predict macronutrient content was N: -0.04149 (SR) + 1.38314, P: -0.07243 (SR) + 0.61766, and K: -0.7059 (SR) + 5.3279. There was no difference between the estimation results and the macronutrient content from the laboratory analysis.