Main Article Content
Abstract
An effective spray of agrochemicals is inevitable for crop production for viable agriculture. Spraying inherently suffers from drift, which has always been one of the major concerns in agriculture, affecting the intent of agrochemical spraying and posing serious environmental hazards. Complete elimination of spray drift is impractical under field conditions but can be minimized using precision spraying techniques. Agricultural spray drift has several detrimental effects, such as environmental damage, polluting water bodies, human and animal health risks, chemical exposure, and economic losses, and may also lead to conflicts between neighboring farmers. Hence, the assessment of spray drift is a salient part of the design process of plant protection equipment to achieve maximum deposition in both chemical and biological pesticide applications. The different methods used to study the drift of a sprayer include test bench, wind tunnel and phase Doppler particle analyzer (PDPA) methods. In the field-level assessment, the fluorometric tracer sampling method conforming to ISO-22866:2005 was used. Plume dispersion, particle tracking and computational fluid dynamics (CFD) are the major mathematical modeling approaches for spray drift simulation studies. Among various methodologies and techniques, an appropriate method for spray drift assessment should be adopted in accordance with factors such as crop parameters, mode of application, and environmental conditions.
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References
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Arvidsson, T., Bergstrom, L., & Kreuger, J. (2011). Comparison of collectors of airborne spray drift. Experiments in a wind tunnel and field measurements. Pest Management Science. 67, 725–733. DOI: https://doi.org/10.1002/ps.2115
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Berlinger, B., Ervik, T. K., Kandler, K., Ulvestad, B., Benker, N., Ellingsen, D. G., & Bugge, M. D. (2021). Challenge with a personal cascade impactor sampler in a silicon metal smelter. Aerosol and Air Quality Research. 21, 200577. https://doi.org/10.4209/aaqr.200577 DOI: https://doi.org/10.4209/aaqr.200577
Blocken, B., Stathopoulos, T., & Carmeliet, J. (2007). CFD simulation of the atmospheric boundary layer: wall function problems. Atmospheric Environment. 41(2), 238-252. DOI: https://doi.org/10.1016/j.atmosenv.2006.08.019
Bolz, H., Sieke, C., Michalski, B., Schafer, R. B., & Kubaik, R. (2022). Spray drift-based pesticide residues on untreated edible crops grown near agricultural areas DOI: https://doi.org/10.1007/s00003-021-01355-9
Bourodimos, G., Koutsiaras, M., Psiroukis, V., Balafoutis, A., & Fountas, S. (2019). Development and field evaluation of a spray drift risk assessment tool for vineyard spraying application. Agriculture. 9(8), 1-21. DOI: https://doi.org/10.3390/agriculture9080181
Bueno, M. R., Cunha, J. A., & Santana, D. G. (2017). Assessment of spray drift from pesticide applications in soybean crops. Biosystems Engineering. 154, 35-45. DOI: https://doi.org/10.1016/j.biosystemseng.2016.10.017
Burgers, T. A., Gaard, J. D., & Hyronimus, B. J. (2021). Comparison of three commercial automatic boom height systems for agricultural sprayers. DOI: https://doi.org/10.13031/13721716.v1
Chen, S., Lan, Y., Zhou, Z., Ouyang, F., Wang, G., Huang, X., Deng, X., & Cheng, S. (2020). Effect of droplet size parameters on droplet deposition and drift of aerial spraying by using plant protection UAV. Agronomy. 10(2), 195. DOI: https://doi.org/10.3390/agronomy10020195
Chethan C. R., Singh P. K., Dubey R. P., Chander S., & Ghosh D. (2019). Herbicide application methodologies: influence of nozzle selection, droplet size and spray drift on effective spraying – a review. Innovative Farming. 4(1): 045-053.
Cooper, J. F., Smith, D. N., & Dobson, H. M. (1996). An evaluation of two field samplers for monitoring spray drift. Crop Protection. 15(3), 249-257. DOI: https://doi.org/10.1016/0261-2194(95)00113-1
Damalas C. A., & Eleftherohorinos I. G. (2011). Pesticide Exposure, Safety Issues, and Risk Assessment Indicators. International Journal of Environmental Research and Public Health. 8(12), 1402–1419. DOI: https://doi.org/10.3390/ijerph8051402
Dean D. A., Amy R. M., Hendley P., & Guevara M. W. (2020). Impact of wind speed and direction and key meteorological parameters on potential pesticide drift mass loadings from sequential aerial applications. Integrated Environment Assessment and Managment. 16(2): 197–210. DOI: https://doi.org/10.1002/ieam.4221
Delele, M. A., Moor, D. A., Sonck, B., Ramon, H., Nicolai, B. M., & Verboven, P. (2005). Modeling and validation of the air flow generated by a cross flow air sprayer as affected by travel speed and fan speed. Biosystems Engineering. 92(2), 165-174. DOI: https://doi.org/10.1016/j.biosystemseng.2005.05.018
Donkersley, P., & Nuyttens, D. (2011). A meta-analysis of spray drift sampling. Crop Protection. 30(7), 931-936. DOI: https://doi.org/10.1016/j.cropro.2011.03.020
Duga, A. T., Delele, M. A., Ruysen, K., Dekeyser, D., Nuyttens, D., Bylemans, D., & Verboven, P. (2017). Development and validation of a 3D CFD model of drift and its application to air-assisted orchard sprayers. Biosystems Engineering. 154, 62-75. DOI: https://doi.org/10.1016/j.biosystemseng.2016.10.010
Ellis, M. C., Alanis, R., Lane, A. G., Tuck, C. R., Nuyttens, D., & Zande, J. V. (2021). Wind tunnel measurements and model predictions for estimating spray drift reduction under field conditions. Biosystems Engineering. 202, 152-164.
Ellis, M. C., & Miller, P. H. (2010). The silsoe spray drift model: A model of spray drift for the assessment of nontarget exposures to pesticides. Biosystems Engineering. 107(3), 169-177. DOI: https://doi.org/10.1016/j.biosystemseng.2010.09.003
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