Abstract
Laser-induced breakdown spectroscopy (LIBS) is a promising alternative to conventional methods in classifying citrus huanglongbing (HLB). Mature citrus fruits with similar features were picked and divided into healthy and HLB-asymptomatic groups. LIBS spectra and images were collected by focusing a laser on fresh fruit surfaces without sample preparation. The pH value and soluble solids content of juice as the indicators of acidity and sugar were detected, and the content of Ca, Zn, and K in peel and pulp was analyzed. The characteristic lines from LIBS spectra were extracted by continuous wavelet transform and principal component analysis (PCA). The $t$-test of these indicators displayed significant difference between the two groups. Fisher discriminant analysis and multilayer perception neural network (MLP) were applied to identify the disease. The classification accuracy reached 100% by PCA-MLP. The results show that LIBS can realize in situ detection of citrus HLB fruits.
© 2021 Optical Society of America
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