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44th TWC, Tob. Work. Conf., 2010, abstr. 18

Tobacco response to simulated drift of glufosinate, dicamba, and 2,4-D

JOHNSON J.A.; FISHER L.R.; PRIEST J.A.
North Carolina State Universiiy, Raleigh, NC, USA

In addition to crops already tolerant to glyphosate and glufosinate, prospective advances in agricultural technology have resulted in cultivars that will be tolerant to topical applications of dicamba and 2,4-D. However, these herbicides can cause injuries in non-target; sensitive crops if spray or vapor drift were to occur. Research was conducted to simulate drift rates of glufosinate, dicamba and 2,4-D to evaluate injury and effects on tobacco yield and quality. Experiments were conducted at two locations during the 2009 growing season. Tobacco cultivar NC 71 was grown under recommended cultural practices until early to mid June when treatments were applied. Dicamba and 2,4-D rates were ½, 1/8, 1/32, 1/128, and 1/512 the recommended rate of .25 lbs and .48 lbs a.i. per acre, respectively. Glufosinate rates were ½, ¼, 1/8, 1/16, and 1/32 the recommended rate of 0.54 lbs a.i. per acre. Treatments were arranged in a randomized complete block design with four replications. Plots were two rows by 40 feet with treatments applied to the right hand row of each plot. Visual injury was recorded 7 and 14 days after treatment on a scale of 0 (no injury) to 100 (plant death). Photographs were also taken 7 and 14 days after treatment to document injury. Yield and quality data were collected along with cured leaf samples for chemical residue analyses. All treatments resulted in visual injury which increased with rate. The ½ rate of dicamba reduced yield at both locations and the 1/8 rate reduced yield at one location. Crop value was reduced with the ½ rate of dicamba at one location. The ½ rate of 2, 4-D and glufosinate both resulted in significant yield loss at one location each. Cured leaf residue data are not available. Trials will be repeated in 2010 and in season residue samples will be collected to correlate injury and predict recovery.