Determination of Sugar Beet Leaf Spot Disease Level (Cercospora Beticola Sacc.) with Image Processing Technique by Using Drone
Journal Title: Current Investigations in Agriculture and Current Research - Year 2018, Vol 5, Issue 3
Abstract
The technical processes emerged in line with the technological advances contribute to the economical, sustainable and productive industry, which are the goals of plant and animal production. Image processing techniques have become an important tool in facilitating agricultural operations and in bringing alternative solutions to the problems that need to be solved or improved. Thanks to the developed algorithms and software, numerous studies have been carried out by researchers on disease, harmful and weed detection, plant identification and detection, determination of plant stresses, yield estimation, determination of obstacles, determination of distances between the rows and row-tops, classification of soil and land cover, estimation of botanical composition, evaluation of vegetation indexes, green area index, determination of plant growth variability, follow-up of product development, follow-up of root development, modeling of irrigation management practices, determination of soil moisture in plant production, and monitoring of animal development in a herd, movement skill scoring, measurement of body characteristics, determination of body condition score, monitoring body weight, lameness detectionThis study was conducted to determine the cercospora leaf spot disease level in the local sugar beets field in Tokat province using the image processing algorithms and to check the maching between the leaf spot disease assessment done by using the image processing algorithms and visual assessment done by expert using disease severity scale. For this purpose, 12 images showing different levels of development of the disease, taken at different times and different natural lighting conditions from the field have been determined by image processing technique using Image Processing Toolbox module of MATLAB program. As a result of the study, the disease severity results acquired; a: 100%, b: 48%, c: 42%, d: 21%, e: 80%, f: 28%, g: 74%, h: 47%, i: 29%, j: 46%, k: 20%, m: 51% with observation results; a: 100%, b: 50%, c: 45%, d: 20%, e: 80% , f: 30%, g: 75%, h: 50%, i: 30%, j: 50%, k: 20% m: 50% have been compared. These values are very close indicates that the study was successfully carried out. In addition, it has been determined that the results of the study using image processing techniques give precise and accurate value that can not be determined by observation.
Authors and Affiliations
Ziya Altas, Mehmet Metin Ozguven, Yusuf Yanar
Keywords
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- EP ID EP573814
- DOI 10.32474/CIACR.2018.05.000214
- Views 84
- Downloads 0
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