Count of main pest of Oil-Bearing (Rosa damascena Miller)’s Rose Soft Scale (Rhodococcus perornatus Cockerell & Parrott) by using image processing methods
Abstract
Harmful counting of oil roses is
carried out by agricultural experts using direct counting method (under
stereomicroscope, generally 40X Zoom). But frequent influences from human
situations such as fatigue, boredom and carelessness cause counting errors. The
method of outputting the project differs because it is a method which has not
been applied in this field before and because error rate is not reduced to
zero. Dish samples taken from the oil roses grown in Isparta central region
were separated into 1.5 cm pieces and prepared for measurement. 13 sample
branch images were taken by Leica brand Z16 APO model macroscope (1X
Magnification); (0.57 Zoom factor); (16: 1 Zoom) scaled. Acquired images were
processed in the Leica las 4.50 microscope software platform by performing the
necessary image quality enhancement operations. Images from the macroscope are
converted into countable form by Matlab program and software language using
morphological image processing methods. An algorithm has been created to determination
of the 2.nimf adults cochineal, 1.nimf cochineal and 2.nimf cochineal and
calculate average cochineal dimensions. Counting was done and schedules were
arranged according to the written algorithm.
Keywords
Image processing applications in agriculture,soft scale,pest,oil-bearing
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