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Use of Drones in Agriculture and Its Future

Yıl 2022, Cilt 12, Sayı 1, 64 - 83, 30.06.2022
https://doi.org/10.54370/ordubtd.1097519

Öz

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.

Kaynakça

  • Allred, B., Martinez, L., Fessehazion, M. K., Rouse, G., Williamson, T. N., Wishart, D., Koganti, T., Freeland, R., Eash, N., Batschelet, A. ve Featheringill, R. (2020). Overall results and key findings on the use of uav visible-color, multispectral, and thermal infrared imagery to map agricultural drainage pipes. Agricultural Water Management, 232, 106036. https://doi.org/10.1016/j.agwat.2020.106036
  • Altas, Z., Ozguven, M. M. ve Yanar, Y. (2018). Determination of sugar beet leaf spot disease level (cercospora beticola sacc.) with image processing technique by using drone. Current Investigations In Agriculture and Current Research, 5(3), 621-631. https://doi.org/10.32474/CIACR.2018.05.000214
  • Altaş, Z., Özgüven, M. M. ve Yanar, Y. (2019, Nisan, 24-27). Bitki hastalık ve zararlı düzeylerinin belirlenmesinde görüntü işleme tekniklerinin kullanımı: Şeker pancarı yaprak leke hastalığı örneği [Sözlü sunum]. International Erciyes Agriculture Animal & Food Sciences Conference, Kayseri, Turkiye.
  • Andrew, W., Greatwood, C. ve Burghardt, T. (2020). Fusing animal biometrics with autonomous robotics: Drone-based search and ındividual id of friesian cattle. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 38-43. https://openaccess.thecvf.com/content_WACVW_2020/papers/w2/Andrew_Fusing_Animal_Biometrics_with_Autonomous_Robotics_Drone-based_Search_and_Individual_WACVW_2020_paper.pdf
  • Apolo-Apolo, O. E., Martínez-Guanter, J., Egea, G., Raja, P. ve Pérez-Ruiz M. (2020). Deep learning techniques for estimation of the yield and size of citrus fruits using a UAV. European Journal of Agronomy, 115, 126030. https://doi.org/10.1016/j.eja.2020.126030
  • Babu, S. J., Shyam, M., Sivakumar, A., Vignesh, R. S. ve Yogapriya J. (2020). Ergonomic heavy-lift pesticide dispeller drone instilled with an intelligent atomizer to achieve optimal spray and improved pest control. European Journal of Molecular & Clinical Medicine, 7 (4). https://www.ejmcm.com/article_1825_555a87f707d98b4aa087cc961699a2a2.pdf
  • Behmann, J., Acebron, K., Emin, D., Bennertz, S., Matsubara, S., Matsubara, S., Bohnenkamp, D., Kuska, M. T., Jussila, J., Salo, H., Mahlein. A. ve Rascher, U. (2018). Specim iq: Evaluation of a new, miniaturized handheld hyperspectral camera and ıts application for plant phenotyping and disease detection. Sensors 18, 441. https://doi.org/10.3390/s18020441
  • Böhler, J. E., Schaepman, M. E. ve Kneubühler, M. (2020). Crop separability from individual and combined airborne imaging spectroscopy and uav multispectral data. Remote Sensing, 12(8), 1256. https://doi.org/10.3390/rs12081256
  • Buters, T. M., Belton, D. ve Cross, A. T. (2019). Multi-sensor uav tracking of ındividual seedlings and seedling communities at millimetre accuracy. Drones, 3 (4), 81. https://doi.org/10.3390/drones3040081
  • Chen, C. J., Huang, Y. Y., Lu, Y. S., Chen, Y. C., Chang, C. Y. ve Huang, Y.M. (2021). Identification of fruit tree pests with deep learning on embedded drone to achieve accurate pesticide spraying. IEEE Access, 9, 21986 - 21997. https://doi.org/10.1109/ACCESS.2021.3056082
  • Çetinsoy, E., Sırımoğlu, E., Öner, K. T., Ayken, T., Hançer, C., Ünel, M., Akşit, M. F., Kandemir, İ. ve Gülez, K. (2009). Yeni bir insansız hava aracının (suavi) prototip üretimi ve algılayıcı-eyleyici entegrasyonu. Otomatik Kontrol Ulusal Toplantısı 2009 (TOK'09), İstanbul, Türkiye. https://research.sabanciuniv.edu/id/eprint/12663/1/88.pdf
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  • D’Odorico, P., Besik, A., Wong, C. Y. S., Isabel, N. ve Ensminger, I. (2020). High-throughput drone-based remote sensing reliably tracks phenology in thousands of conifer seedlings. New Phytologist 226, 1667–1681. https://doi.org/10.1111/nph.16488
  • Etigowni, S., Hossain-McKenzie, S., Kazerooni, M., Davis, K. Ve Zonouz, S. (2018). Crystal (ball): I look at physics and predict control flow! just-ahead-of-time controller recovery. Proceedings of the 34th Annual Computer Security Applications Conference, 553–565. https://doi.org/10.1145/3274694.3274724
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Tarımda Drone Kullanımı ve Geleceği

Yıl 2022, Cilt 12, Sayı 1, 64 - 83, 30.06.2022
https://doi.org/10.54370/ordubtd.1097519

Öz

Tarım, yaşamın sürdürebilmesi için hayati bir faaliyet alanı olmakla birlikte, tarım dışı diğer sektörlere hammadde sağlaması, milli gelir ve istihdama katkısı nedeniyle de stratejik bir faaliyet alanıdır. Teknolojinin hızla gelişmesiyle ortaya çıkan yeni teknikler veya cihazların tarımda kullanılması tarımsal uygulamaların daha kolay ve etkin yapılabilmesini sağlamaktadır. Son yıllardaki en popüler teknolojik gelişmelerden biri olan drone’ların tarımda kullanımı yaygınlaşmakta ve yeni uygulama alanlarının da eklenmesiyle daha da popüler hale gelmektedir. Drone’ların popüler olması ve tarımda kullanımı, tarım dışı farklı disiplinlerden olanların da ilgisini çekmektedir. Farklı disiplinlerde olanların tarım konusundaki bazı teknik bilgilerinin yetersiz olmasından dolayı, drone’un tarımda kullanımı ile ilgili yanlış bilgiler veya efektif olmayan kullanımlar da oluşabilmektedir. Bu çalışmada, drone ve bileşenleri, drone’un avantaj ve dezavantajları, drone ile kullanılabilen kamera ve sensörler hakkında bilgiler verilmiştir. Daha sonra günümüzde tarımda drone kullanım alanları örnek uygulamalar ile açıklanmış ve gelecekte tarımda drone kullanımı ile öngörüler sunulmuştur. Ayrıca drone’un tarımda kullanımı ile bazı yanlış bilgiler ve efektif olmayan kullanımlar hakkında açıklamalar yapılmıştır.

Kaynakça

  • Allred, B., Martinez, L., Fessehazion, M. K., Rouse, G., Williamson, T. N., Wishart, D., Koganti, T., Freeland, R., Eash, N., Batschelet, A. ve Featheringill, R. (2020). Overall results and key findings on the use of uav visible-color, multispectral, and thermal infrared imagery to map agricultural drainage pipes. Agricultural Water Management, 232, 106036. https://doi.org/10.1016/j.agwat.2020.106036
  • Altas, Z., Ozguven, M. M. ve Yanar, Y. (2018). Determination of sugar beet leaf spot disease level (cercospora beticola sacc.) with image processing technique by using drone. Current Investigations In Agriculture and Current Research, 5(3), 621-631. https://doi.org/10.32474/CIACR.2018.05.000214
  • Altaş, Z., Özgüven, M. M. ve Yanar, Y. (2019, Nisan, 24-27). Bitki hastalık ve zararlı düzeylerinin belirlenmesinde görüntü işleme tekniklerinin kullanımı: Şeker pancarı yaprak leke hastalığı örneği [Sözlü sunum]. International Erciyes Agriculture Animal & Food Sciences Conference, Kayseri, Turkiye.
  • Andrew, W., Greatwood, C. ve Burghardt, T. (2020). Fusing animal biometrics with autonomous robotics: Drone-based search and ındividual id of friesian cattle. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 38-43. https://openaccess.thecvf.com/content_WACVW_2020/papers/w2/Andrew_Fusing_Animal_Biometrics_with_Autonomous_Robotics_Drone-based_Search_and_Individual_WACVW_2020_paper.pdf
  • Apolo-Apolo, O. E., Martínez-Guanter, J., Egea, G., Raja, P. ve Pérez-Ruiz M. (2020). Deep learning techniques for estimation of the yield and size of citrus fruits using a UAV. European Journal of Agronomy, 115, 126030. https://doi.org/10.1016/j.eja.2020.126030
  • Babu, S. J., Shyam, M., Sivakumar, A., Vignesh, R. S. ve Yogapriya J. (2020). Ergonomic heavy-lift pesticide dispeller drone instilled with an intelligent atomizer to achieve optimal spray and improved pest control. European Journal of Molecular & Clinical Medicine, 7 (4). https://www.ejmcm.com/article_1825_555a87f707d98b4aa087cc961699a2a2.pdf
  • Behmann, J., Acebron, K., Emin, D., Bennertz, S., Matsubara, S., Matsubara, S., Bohnenkamp, D., Kuska, M. T., Jussila, J., Salo, H., Mahlein. A. ve Rascher, U. (2018). Specim iq: Evaluation of a new, miniaturized handheld hyperspectral camera and ıts application for plant phenotyping and disease detection. Sensors 18, 441. https://doi.org/10.3390/s18020441
  • Böhler, J. E., Schaepman, M. E. ve Kneubühler, M. (2020). Crop separability from individual and combined airborne imaging spectroscopy and uav multispectral data. Remote Sensing, 12(8), 1256. https://doi.org/10.3390/rs12081256
  • Buters, T. M., Belton, D. ve Cross, A. T. (2019). Multi-sensor uav tracking of ındividual seedlings and seedling communities at millimetre accuracy. Drones, 3 (4), 81. https://doi.org/10.3390/drones3040081
  • Chen, C. J., Huang, Y. Y., Lu, Y. S., Chen, Y. C., Chang, C. Y. ve Huang, Y.M. (2021). Identification of fruit tree pests with deep learning on embedded drone to achieve accurate pesticide spraying. IEEE Access, 9, 21986 - 21997. https://doi.org/10.1109/ACCESS.2021.3056082
  • Çetinsoy, E., Sırımoğlu, E., Öner, K. T., Ayken, T., Hançer, C., Ünel, M., Akşit, M. F., Kandemir, İ. ve Gülez, K. (2009). Yeni bir insansız hava aracının (suavi) prototip üretimi ve algılayıcı-eyleyici entegrasyonu. Otomatik Kontrol Ulusal Toplantısı 2009 (TOK'09), İstanbul, Türkiye. https://research.sabanciuniv.edu/id/eprint/12663/1/88.pdf
  • Dantas, R. A. S., Neto, M. V. G., Zyrianoff, I. D. ve Kamienski, C. A. (2020). The swamp farmer app for IoT-based smart water status monitoring and ırrigation control. 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 20258013. https://doi.org/10.1109/MetroAgriFor50201.2020.9277588
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Ayrıntılar

Birincil Dil Türkçe
Konular Ziraat
Yayınlanma Tarihi Bahar
Bölüm Derleme Makaleler
Yazarlar

Mehmet Metin ÖZGÜVEN>
TOKAT GAZİOSMANPAŞA ÜNİVERSİTESİ
0000-0002-6421-4804
Türkiye


Ziya ALTAŞ>
TOKAT GAZİOSMANPAŞA ÜNİVERSİTESİ
0000-0001-9900-0606
Türkiye


Derya GÜVEN> (Sorumlu Yazar)
TOKAT GAZİOSMANPAŞA ÜNİVERSİTESİ
0000-0001-5363-5366
Türkiye


Arif ÇAM>
TOKAT GAZİOSMANPAŞA ÜNİVERSİTESİ
0000-0002-8067-0826
Türkiye

Yayımlanma Tarihi 30 Haziran 2022
Yayınlandığı Sayı Yıl 2022, Cilt 12, Sayı 1

Kaynak Göster

APA Özgüven, M. M. , Altaş, Z. , Güven, D. & Çam, A. (2022). Tarımda Drone Kullanımı ve Geleceği . Ordu Üniversitesi Bilim ve Teknoloji Dergisi , 12 (1) , 64-83 . DOI: 10.54370/ordubtd.1097519