Evaluation of performances of different types of spray nozzles in site-specific pesticide spraying

Ali Bolat, Ömer Baris Özlüoymak


In recent years, site-specific spraying methods, which are capable of combining the image processing technologies with electronic and information technologies, have been started to be used in the weed control and target-oriented spraying. In this study, in addition to the site-specific spraying in laboratory conditions; a mobile spraying system, which can also perform broadcast application as a reference method, was set up. The spraying performance of the mobile system was tested for three different nozzle types (standard flat fan nozzle, cone nozzle, air induction nozzle) and at speeds of 0.48, 0.60, 0.72 and 0.84 km h-1. The mobile system was operated as both broadcast and site-specific for each nozzle type and travel speed. Three artificial weed samples were used at 75 cm intervals as sampling surfaces on the movement of the mobile system in the spraying operations; filter papers (FP) and water-sensitive papers (WSP) were placed behind them on the bars. While deposition values were measured with the filter papers, water-sensitive papers were used to measure the coverage rates. The spray distribution of the site-specific method in comparison with the reference method was investigated. According to the results, site-specific spraying applications did not cause any negative impact on depositions and coverage rates. The nearest results compared with the broadcast spraying were obtained with the air induction nozzle type at a speed of 0.48 km h-1 with a 60.5% deposition amount and 95.9% coverage rate.


Air induction nozzle; Broadcast spraying; Cone nozzle; Flat fan nozzle; Site-specific spraying.;

Full Text:



Baran, M. F., Polat, R., & Gökdo?an, O. (2016). Comparison of energy use efficiency of different tillage methods on the secondary crop sunflower production. Fresenius Environmental Bulletin, 25(11), 4937-4943.

Bolat, A. (2010). Çukurova bölgesinde m?s?r yeti?tiricili?inde baz? ilaç uygulama yöntemlerinin etkinliklerinin saptanmas?. Doctoral thesis, Çukurova Üniversitesi Fen Bilimleri Enstitüsü Tar?m Makinalar? Anabilim Dal? Adana, Turkey.

Bolat, A., Bayat, A., Tetik, O., Karaagac, H. A., Cerit, I., & Sevilmis, U. (2018). Performance of herbicide spraying methods at different application volumes in maize. Fresen?us Environmental Bulletin, 27(5), 2963-2967.

Christensen, S., Søgaard, H. T., Kudsk, P., Nørremark, M., Lund, I., Nadimi, E. S., & Jørgensen, R. (2009). Site specific weed control technologies. Weed Research, 49(3), 233-241. doi: 10.1111/j.1365-3180.2009.00696.x

Doruchowski, G., ?wiechowski, W., Masny, S., Maciesiak, A., Tartanus, M., Bryk, H., & Ho?ownicki, R. (2017). Low-drift nozzles vs. standard nozzles for pesticide application in the biological efficacy trials of pesticides in apple pest and disease control. Science of the Total Environment, 575(5), 1239-1246. doi: 10.1016/j.scitotenv.2016.09.200

Loni, R., Loghavi, M., & Jafari, A. (2014). Design, development and evaluation of targeted discrete-flame weeding for inter-row weed control using machine vision. American Journal of Agricultural Science and Technology, 2(1), 17-30. doi: 10.7726/ajast.2014.1003

Martín, C. S., Andújar, D., Barroso, J., Fernández-Quintanilla, C., & Dorado, J. (2016). Weed decision threshold as a key factor for herbicide reductions in site-specific weed management. Weed Technology, 30(4), 888-897. doi: 10.1614/WT-D-16-00039.1

Özlüoymak, Ö. B., Bolat, A., Bayat, A., & Güzel, E. (2019). Design, development, and evaluation of a target oriented weed control system using machine vision. Turkish Journal of Agriculture and Forestry, 43(2), 164-173. doi: 10.3906/tar-1803-8

Perez, A. J., Lopez, F., Benlloch, J. V., & Christensen, S. (2000). Colour and shape analysis techniques for weed detection in cereal fields. Computers and Electronics in Agriculture, 25(3), 197-212. doi: 10.1016/S0168-1699(99)00068-X

Sabanc?, K., & Ayd?n, C. (2014). Image processing based precision spraying robot. Tarim Bilimleri Dergisi, 20(4), 406-414. doi: 10.1501/Tarimbil_0000001299

Shirzadifar, A. M., Loghavi, M., & Raoufat, M. H. (2015). Development and evaluation of a real time site-specific inter-row weed management system. Iran Agricultural Research, 32(2), 39-54.

Soysal, A., & Bayat, A. (2006). Herbisit uygulamalar?nda kullan?lan dü?ük sürüklenme potansiyelli memelerin püskürtme tekni?i aç?s?ndan de?erlendirilmesi. Tar?m Makinalar? Bilimi Dergisi, 2(3), 189-195.

Tang, J. L., Chen, X. Q., Miao, R. H., & Wang, D. (2016). Weed detection using image processing under different illumination for site-specific areas spraying. Computers and Electronics in Agriculture, 122(3), 103-111. doi: 10.1016/j.compag.2015.12.016

Tian, L., Reid, J. F., & Hummel, J. W. (1999). Development of a precision sprayer for site-specific weed management. Transactions of the ASAE, 42(4), 893-901. doi: 10.13031/2013.13269

Yang, C. C., Prasher, S. O., Landry, J., & Ramaswamy, H. S. (2002). Development of neural networks for weed recognition in corn fields. Transactions of the ASAE, 45(3), 859-866. doi: 10.13031/2013.8854

DOI: http://dx.doi.org/10.5433/1679-0359.2020v41n4p1199

Semina: Ciênc. Agrár.
Londrina - PR
E-ISSN 1679-0359
DOI: 10.5433/1679-0359
E-mail: semina.agrarias@uel.br
Este obra está licenciado com uma Licença Creative Commons Atribuição-NãoComercial 4.0 Internacional