Türkiye is one of the countries with the most important vineyard areas in the world, where the most grape production is made. Vineyard diseases are one of the most important reasons that adversely affect the productivity in viticulture. In this study, some vineyard diseases were detected and classified using the Faster R-CNN deep learning model, which is an artificial intelligence approach. These diseases are powdery mildew, downy mildew, dead arm disease, grapevine leaf roll-associated virus disease (GLRaV) and grapevine fan leaf nepovirus (GFLV) diseases that are common and cause economic problems. The proposed method is trained and tested using 11000 images. At the end of the study, the overall accuracy rate was found to be 92%. The proposed approach gave better results than similar methods in the literature. Therefore, it was concluded that the method can be used reliably in the detection and classification of some vineyard diseases.
Agriculture is both a vital sector of activity for the sustainability of life and strategic field of activity for provides raw materials to non-agricultural sectors and contributes to national income and employment. The use of new techniques or devices in agriculture, which emerged with the rapid development of technology, makes agricultural applications easier and more effective. The use of drones in agriculture, which is one of the most popular technological developments in recent years, has become widespread and its use is increasing even more with the addition of new application areas. The popularity of drones and their use in agriculture also attract the attention of those from different disciplines other than agriculture. Due to the insufficient technical knowledge of those in different disciplines on agriculture, false information or ineffective use of drones in agriculture may occur. In this study, information is given about the drone and its components, the advantages and disadvantages of the drone, the cameras and sensors that can be used with the drone. Then, the use of drones in agriculture today is explained with sample applications and predictions are presented with the use of drones in agriculture in the future. In addition, explanations were made about the use of drones in agriculture, some misinformation and ineffective use.
Özet. ANSYS, araştırma ve geliştirme uygulamalarında analizlerin ve simülasyonların yapılabildiği bilgisayar destekli mühendislik programıdır. Mekanik, yapısal analiz, hesaplamalı akışkanlar dinamiği ve ısı transferi gibi farklı hesaplamalı uygulamalarda ANSYS programı kullanılmaktadır. Bu çalışmada, ANSYS paket yazılım programı genel hatlarıyla açıklanmaya çalışılmış, ANSYS'in tarımdaki uygulamalarına yönelik bazı çalışmalara yer verilmiş ve tarım arabası aksının modellemesi ve analizi yapılmıştır. Tarım arabalarında dikdörtgen kesitli ve dairesel kesitli akslar kullanılmaktadır. Bu nedenle çalışmada hem dikdörtgen kesitli hem de dairesel kesitli aks üzerinde statik bir analiz yapılmış ve her iki akstan elde edilen sonuçlar karşılaştırılmıştır. Bulgularda her iki aksa ait eşdeğer gerilim, eşdeğer elastik gerilim, toplam deformasyon ve güvenlik faktörü analizleri elde edilmiştir. SolidWorks programı kullanılarak aksların katı modellemesi 3 boyutlu olacak şekilde oluşturulduktan sonra ANSYS Workbench kullanılarak modelleme sonrası aksların çalışma şartları gerçeğe uygun olacak şekilde simüle edilmiş ve akslar üzerinde oluşan gerilme dağılımları incelenerek gerilmelere ait gerekli analizler yapılmıştır. Sonuç olarak ise, maksimum eşdeğer gerilim, dairesel kesitli aksta 15.892 MPa, dikdörtgen kesitli aksta ise 12.026 MPa'dır. Maksimum eşdeğer elastik gerilim, dairesel kesitli aksta 7.9463e-5 mm mm -1 , dikdötrgen kesitli aksta ise 6.8408e-5 mm mm -1 'dir. Toplam deformasyon dairesel kesitli aksta 0.077806 mm, dikdörtgen kesitli aksta ise 0.053021 mm'dir. Güvenlik faktörü ise her iki aksta da eşit olarak bulunmuştur.
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