• Research in Plant Disease
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• v.24 no.1
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• pp.41-51
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• 2018

Since fire blight disease on apple and pear was produced in Korea in 2015, there were no registered chemicals to control against this disease. Instead, several antibacterial chemicals that were registered for other bacterial diseases such as soft rot and bacterial spot have been authorized by Rural Development Administration (RDA). However, these chemicals are not tested efficacy for fire blight disease except damage by those treatments on apple and pear in Korea. Thus, we evaluated efficiency using in vitro and in planta assays of antibacterial chemicals such as antibiotics and copper compounds including kasugamycin, oxytetracycline, oxolinic acid and streptomycin, and copper hydroxide, copper sulfate, oxine copper and tribasic copper sulfate, respectively. We also tested two kinds of biological agents. As expected, significant antibacterial effect was observed in vitro test of both antibiotics and copper-based chemicals. In planta test based on disease severity including ooze and water-soaked formation on immature pears, bacterial populations on blooms, and blight lesion formation in artificially inoculated shoots, kasugamycin, oxytetracycline and streptomycin have been shown the most efficiency among tested antibiotics. Four copper-based chemicals tested in this study, control effects are little bit lower than agricultural antibiotics but they seem to be available to use in terms of winter season. Biocontrol agents were also shown possibility to treat in eco-friendly farms. In addition, there are no antibiotic resistance genes in Korean isolates against antibiotics, which were selected for suppression of fire blight in this study.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.