Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)
Septa Primananda
Wilmar International Plantation, Central Kalimantan Region
Agriculture, Biological Sciences & Forestry Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
The Use of the Normalized Difference Red Edge (NDRE) Vegetation Index from Multispectral Cameras Mounted on Unmanned Aerial Vehicle to Estimate the Nutrient Content in Oil Palm Leaves Badi Hariadi; Hermantoro Sastrohartono; Andreas Wahyu Krisdiarto; Sukarman Sukarman; Tri Haryo Sagoro; Septa Primananda; Arief Rahmad Maulana Akbar; Arief Ika Uktoro
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 4 (2024): December 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i4.1051-1063

Abstract

This study aimed to develop a prediction model for the nutrient content of N, P, K, Mg, and Ca in oil palm leaves using the Normalized Difference RedEdge (NDRE) vegetation index derived from multispectral camera data. Data acquisition was carried out by an unmanned aerial vehicle (UAV), which was correlated to leaf sample analysis of the 17th frond number. Results showed that simple regression analysis successfully represented nutrient content (N, P, K, Mg, and Ca) based on NDRE values. Based on the MAPE and Correctness values, the nutrient content prediction model for N and P yields reliable results, while for K, Mg, and Ca, they are considered good, with Correctness values of 95.5%, 96.6%, 88.8%, 87.3%, and 90.0% for N, P, K, Mg, and Ca, respectively. The study found that the NDRE vegetation index can be used to predict the nutrient content of oil palm leaves with  reliable results in accuracy for N and P, and good accuracy for K, Mg, and Ca. This is a promising finding, as it could lead to the development of a non-destructive and rapid method for monitoring the nutrient status of oil palm trees, with the validation models for N, P, K, Mg, and Ca are yN = 1.1089x - 0.2497, yP = 0.99x + 0.002, yK = 1.204x - 0.1576, yMg = 0.9149x + 0.0183, and yCa = 1.0418x - 0.0218. Keywords: Multispectral Cameras, Oil Palm, Leaf Nutrient Contents, Prediction.
Co-Authors Andreas Wahyu Krisdiarto Arief Ika Uktoro Arief Rahmad Maulana Akbar Badi Hariadi Hermantoro Sastrohartono Sukarman Sukarman Tri Haryo Sagoro