Developing an algorithm to geographically estimate the available time for agricultural field spraying in the state of Mato Grosso do Sul
pdf

Keywords

Agricultural pesticides
Soil compaction
Weather conditions.

How to Cite

Scarpim, I. M., Baio, F. H. R., Alvarez, R. de C. F., Gava, R., Teodoro, P. E., Silva Junior, C. A., … Wassolowski, C. R. (2023). Developing an algorithm to geographically estimate the available time for agricultural field spraying in the state of Mato Grosso do Sul. Semina: Ciências Agrárias, 44(2), 469–484. https://doi.org/10.5433/1679-0359.2023v44n2p469

Abstract

The dimensions of mechanized agricultural systems depend on the edaphoclimatic conditions, crops, and work regimes. This study aimed to geographically estimate the monthly available time and number of favorable hours for agricultural field spraying in the state of Mato Grosso do Sul, Brazil. The meteorological restrictions imposed during unfavorable hours were as follows: ambient temperature above 32 ºC, relative humidity below 50 %, wind speed above 15 km h-1, and volumetric soil humidity above 39 % (equivalent to 90 % of the available water capacity). Mathematical models were then developed considering a period of ten years, which used historical data from the ground monitoring stations of the National Institute of Meteorology within the region. The subsequent algorithm was programmed and installed in a web server to simulate the time required for agricultural field spraying. During the cropping period in the region, there were climatic restrictions on performing agricultural spraying, with relative humidity being the variable with the most significant impact. However, soil moisture conditions restricted the available time for agricultural spraying more than the wind speed, relative air humidity, or ambient temperature.

https://doi.org/10.5433/1679-0359.2023v44n2p469
pdf

References

Allen, R. G., Pereira, L. S., Smith, M., Raes, D., & Wright, J. L. (2005). FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions. Journal of Irrigation and Drainage Engineering, 131(1), 2-13. doi: 10.1061/(ASCE)0733-9437(2005)131:1(2)

Baio, F. H. R., Antuniassi, U. R., Castilho, B. R., Teodoro, P. E., & Silva, E. E. D. (2019). Factors affecting aerial spray drift in the Brazilian Cerrado. Plos One, 14(2), e0212289. doi: 10.1371/journal.pone.0212289

Cunha, J. P. A. R., Pereira, J. N. P., Barbosa, L. A., & Silva, C. R. D. (2016). Pesticide application windows in the region of Uberlândia, Brazil. Bioscience Journal, 32(2), 403-411. doi: 10.14393/BJ-v32n2a2016-31920

Deon, R. C., Zilli, D., Brandelero, G., & Machado, R. G. (2018). Compaction and water infiltration capacity of a cambisol by the traffic of machines and cattle trampling. Ciência Agrícola, 16(1), 77-84. doi: 10.28998/rca.v16i1.4088

Empresa Brasileira de Pesquisa Agropecuária (2018). Sistema brasileiro de classificação de solos (5a ed.). EMBRAPA Solos.

Esteban, D. A. A., Souza, Z. M., Tormena, C. A., Lovera, L. H., Lima, E. S., Oliveira, I. N., & Ribeiro, N. P. (2019). Soil compaction, root system and productivity of sugarcane under different row spacing and controlled traffic at harvest. Soil and Tillage Research, 187(3), 60-71. doi: 10.1016/j.still.2018.11.015

Gava, R., Scarpin, I. M., Baio, F. H. R., Wassolowski, C. R., & Neves, D. C. (2018). Time available for spraying and mechanized sowing in the northeast of the state of Mato Grosso Do Sul and south of Goiás. Engenharia Agrícola, 38(3), 443-450. doi: 10.1590/1809-4430-eng.agric.v38n3p443-450/2018

Kambrekar, D. N. (2020). Minimizing pesticide risk to bees in cross pollinated crops. Biotica Research Today, 2(4), 69-72. https://biospub.com/index.php/biorestoday/article/view/55

Kay, R., Edwards, W., & Duffy, P. A. (Eds.) (2019). Farm management (9nd ed.). McGraw-Hill Education.

Lima, R. P., Keller, T., Giarola, N. B. F., Tormena, C. A., Silva, A. R., & Rolim, M. M. (2020). Measurements and simulations of compaction effects on the least limiting water range of a no-till Oxisol. Journal of Soil Research, 58(1), 62-72. doi: 10.1071/SR19074

Mello, M. F., Schlosser, J. F., & Cervo, H. Z. (2019). A tomada de decisão baseada em atributos que influenciam a compra de máquinas agrícolas. Revista Científica, 9(15), 149-168. doi: 10.18815/sh.2019v9n15.410

Radons, S. Z., Heldwein, A. B., Silva, J. R., Silva, A. V., & Schepke, E. (2022). Weather conditions favorable for agricultural spraying in Rio Grande do Sul State. Revista Brasileira de Engenharia Agrícola e Ambiental, 26(1), 36-43. doi: 10.1590/1807-1929/agriambi.v26n1p36-43

Santinato, F., Ruas, R. A. A., Tavares, T. O., Silva, R. P., & Godoy, M. A. (2017). Influence of spray volumes, nozzle types and adjuvants on the control of phoma coffee rust. Coffee Science, 12(4), 444-450. http://hdl.handle.net/123456789/9240

Shi, X., Li, M., Hunter, O., Guetti, B., Andrew, A., Stommel, E., Bradley, W., & Karagas, M. (2019). Estimation of environmental exposure: interpolation, Kernel density estimation, or snapshotting. Ann GIS. 25(1), 1-8. doi: 10.1080/19475683.2018.1555188

Silva, S. O., & Ricardo, A. S. (2022). Computational tool for calculating parameters approached in solid and soil mechanics disciplines. Revista Eletrônica de Engenharia Civil, 18(1), 1-17. doi: 10.5216/reec.V18i168478

Tian, Z. W., Xue, X. Y., Cui, L. F., Chen, C., & Peng, B. (2020). Droplet deposition characteristics of plant protection UAV spraying at night. International Journal of Agricultural Aviation, 3(4), 18-23. doi: 10.33440/j.ijpaa.20200304.103

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2023 Semina: Ciências Agrárias

Downloads

Download data is not yet available.