摘要

Crop injury caused by off-target drift of aerially applied glyphosate is of great concern to farmers and aerial applicators. An experiment was conducted in 2009 to determine the extent of injury due to near-field glyphosate drift from aerial application to glyphosate-sensitive cotton, corn, and soybean. The drift effects on different crops were characterized in afield planted in alternating blocks of these sensitive crops. Spray samplers were placed in the spray swath and downwind to quantify, relative concentrations of the applied chemical. An Air Tractor 402B spray airplane equipped with fifty-four CP-09 nozzles was flown down the center of the field, applying 866 g a.e. ha(-1) glyphosate (Roundup Weathermax) and rubidium chloride tracer at a 2.6 g ha(-1) spray rate. Relative concentrations of the tracer were quantified from downwind spray samplers by atomic absorption spectroscopy. Biological responses of the crops to the glyphosate drift were measured at weekly intervals, along with airborne multispectral imaging. Statistical analysis indicated that spray drift sampling was able to explain downwind crop injury, and physical responses could be estimated for evaluating crop injury caused by the drift of aerially applied glyphosate. Correlations between the relative concentration of the spray tracer and the crop biological responses identified that cotton was less sensitive to glyphosate drift than corn and soybean. Regression models for the injuries of cotton and soybean one and two weeks after field treatment and for the injury of corn one week after treatment with the percent applied glyphosate from the label rate were developed and evaluated with chlorophyll data. The cotton models for visual injury and plant height at one and two weeks after treatment were well validated with chlorophyll data (average of 1 for the ratio of estimated vs. measured chlorophyll, and low root mean squared deviations). However, in validation of the corn model, the ratio of estimated vs. measured chlorophyll deviated from 1. Compared with validation of the corn model, the validation of the soybean models showed less bias, with a value close to 1 for the ratio of estimated vs. measured chlorophyll. These results have established a method of characterizing crop injury caused by aerially applied glyphosate and can provide guideline data for use by farmers and aerial applicators.