Please use this identifier to cite or link to this item: https://scholar.ptuk.edu.ps/handle/123456789/108
Title: Visible/Near infrared (VIS/NIR) spectroscopy and multivariate data analysis (MVDA) for identification and quantification of olive leaf spot (OLS) disease
Authors: Abu-Khalaf, Nawaf
Salman, Mazen
Keywords: olives, Olive Leaf Spot (OLS), disease severity, VIS/NIR spectroscopy, Multivariate Data, Analysis (MVDA) (i.e. chemometrics), Partial Least Squared-Discrimination Analysis (PLS-DA), Support Vector Machine (SVM)-classification
Issue Date: 9-Feb-2014
Publisher: PTUK
Citation: Abu-Khalaf Nawaf ,Salman, Mazen. 2014. Visible/Near infrared (VIS/NIR) spectroscopy and multivariate data analysis (MVDA) for identification and quantification of olive leaf spot (OLS) disease. Palestine Technical University Research Journal . 2 (1);1-8 . www.ptuk.edu.ps
Series/Report no.: 2 (1);1-8
Abstract: Early detection of plant disease requires usually elaborating methods techniques and especially when symptoms are not visible. Olive Leaf Spot (OLS) infecting upper surface of olive leaves has a long latent infection period. In this work, VIS/NIR spectroscopy was used to determine the latent infection and severity of the pathogens. Two different classification methods were used, Partial Least Squared-Discrimination Analysis (PLS-DA) (linear method) and Support Vector Machine (SVM) (non-linear). SVM-classification was able to classify severity levels 0, 1, 2, 3, 4, and 5 with classification rates of 94, 90, 73, 79, 83 and 100%, respectively The overall classification rate was about 86%. PLS-DA was able to classify two different severity groups (first group with severity 0, 1, 2, 3, and second group with severity 4, 5), with a classification rate greater than 95%. The results promote further researches, and the possibility of evaluation OLS in-situ using portable VIS/NIR devices
URI: https://scholar.ptuk.edu.ps/handle/123456789/108
ISSN: 2307-809x
Appears in Collections:2014

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