Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data

By Helmi Zulhaidi Mohd Shafri, M. Anuar, Idris Abu Seman, N. M. Noor. 2011

81 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/a3bfccfd494736f8606e39161fdd8e2b5778d88f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Reza Ehsani

In Ecology

1. Helmi Zulhaidi Mohd Shafri
2. Reza Ehsani

In Global and Planetary Change

1. Helmi Zulhaidi Mohd Shafri
2. Shattri Mansor

Citations in the corpus

• Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms (2014, methodology): “Shafri et al. (2011) tested a maximum likelihood classifier as a supervised classification method to classify the Ganoderma-sensitive wavelengths extracted from the spectral reflectance of healthy and infected six-month-old oil palm trees in the nursery.”