Department of Biosystems Engineering, Tokat Gaziosmanpaşa University, 60150, Tokat, Turkey.
Department of Plant Protection, Tokat Gaziosmanpaşa University, 60150, Tokat, Turkey.
Exp Appl Acarol. 2020 Nov;82(3):335-346. doi: 10.1007/s10493-020-00561-8. Epub 2020 Oct 21.
This study uses an image-processing technique to determine the damage level caused by two-spotted spider mite (Tetranychus urticae Koch) to cucumber plants and changes in the number of mites in a greenhouse. Firstly, a new agricultural platform was developed to ensure camera stability for capturing quality images. The images of 50 leaves infested with T. urticae were captured weekly for 5 weeks with the platform, which resulted in 250 images. Fifty of these captured images were randomly selected and processed with an image-processing algorithm developed using an image processing toolbox module of MATLAB. The results obtained from the image processing algorithm were compared with expert observations. The image-processing method predicted the damage with 3.91 root mean squared error (RMSE). A highly significant positive relationship was found between image processing and expert observations. The results indicate that this new image-processing method may be successfully used in place of expert observation to determine T. urticae damage in greenhouses.
本研究使用图像处理技术来确定二斑叶螨（Tetranychus urticae Koch）对黄瓜植株造成的损害程度以及温室中螨虫数量的变化。首先，开发了一个新的农业平台，以确保相机稳定，从而拍摄到高质量的图像。使用该平台每周拍摄 50 片受 T. urticae 感染的叶片，共拍摄 5 周，得到 250 张图像。随机选择其中的 50 张进行图像处理，使用 MATLAB 的图像处理工具箱模块开发的图像处理算法进行处理。将图像处理算法得到的结果与专家观察结果进行比较。图像处理方法的预测误差为 3.91 均方根误差（RMSE）。图像处理与专家观察之间存在高度显著的正相关关系。结果表明，这种新的图像处理方法可以成功替代专家观察，用于确定温室中 T. urticae 的损害程度。
