2016
DOI: 10.1590/1413-70542016406016716
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Drift curves from spray applications on commom bean crop

Abstract: In order to avoid the occurrence of drift in pesticide applications, it is fundamental to know the behavior of sprayed droplets. This study aimed to determine drift curves in pesticide applications on common bean crop under brazilian weather conditions, using different nozzle types and compared them with the "German" and "Dutch" drift prediction models. The experiment was conducted in Uberlândia, Minas Gerais/Brazil, in completely randomized design with ten replications and 4 x 20 split-plot arrangement in spa… Show more

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Cited by 6 publications
(6 citation statements)
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“…As expected, the average ground depositions with both seeders generally decreased with increasing distance from the sowing area (Table 4). Highest depositions generally were measured in the first few metres of the downwind area, as reported in various studies, 8,31–34 but dust drift percentages were much lower than spray drift values from horizontal boom sprayers 35–37 . This decrease in a.i.…”
Section: Resultssupporting
confidence: 62%
See 1 more Smart Citation
“…As expected, the average ground depositions with both seeders generally decreased with increasing distance from the sowing area (Table 4). Highest depositions generally were measured in the first few metres of the downwind area, as reported in various studies, 8,31–34 but dust drift percentages were much lower than spray drift values from horizontal boom sprayers 35–37 . This decrease in a.i.…”
Section: Resultssupporting
confidence: 62%
“…Highest depositions generally were measured in the first few metres of the downwind area, as reported in various studies, 8,[31][32][33][34] but dust drift percentages were much lower than spray drift values from horizontal boom sprayers. [35][36][37] This decrease in a.i. deposited on the ground with increasing distance from the seeder generally is attributed to the coarse particles tending to deposit on the ground close to the drill.…”
Section: Sedimenting Driftmentioning
confidence: 87%
“…From the regression analysis, it can be observed that the power model showed good adjustment to the data. These models allow knowing the covered distances by the droplets after their generation, being very useful for the study of the environmental impact on applications and for the determination of the safety strips (Bueno et al, 2016).…”
Section: Resultsmentioning
confidence: 99%
“…H o w e v e r, s t u d i e s i n v o l v i n g t h e environmental risk, mainly due to drift, are still sparse, although there are already some models of drift forecasting that have recently been developed for the cultivation of coffee (Alves andCunha 2014), beans (Bueno et al 2016a) and soybeans (Bueno et al 2016b).…”
Section: Introductionmentioning
confidence: 99%