Implementing variable-rate herbicide applications based on soil physical properties in grain sorghum

Soil application of herbicides for pre-emergence (PRE) weed control is vital for grain sorghum production. Many soil-applied herbicides can be adsorbed or bound to the soil reducing the amount available for weed control. Extent of adsorption is strongly correlated to soil physical properties of organic matter (SOM) and texture. To overcome adsorption, the rate of herbicide to be applied is dependent on SOM and texture levels. These properties can vary within one field, making it difficult to follow label recommendations and achieve adequate weed control with a uniform rate. Variable rate applications (VRA) can be utilized to maximize herbicide effectiveness by applying the right rate in the right place. In 2016 and 2017, herbicide algorithms were developed for two different tank-mixes to be applied at five locations across Kansas. A Veris MSP3 system was utilized to collect and develop interpolated maps of SOM and of EC values that were correlated with soil texture classes to develop soil texture maps. Three algorithms were evaluated in the field for each tank-mix: based only on SOM (alg-SOM), on SOM and texture (alg-SOMtex), or on a flat rate. Rates for each tank-mix were based on the maximum usage rate (MUR) allowed for each herbicide. VRA based on SOM reduced the amount of herbicide applied while resulting in similar weed control compared to the flat rate. VRA based on SOM and texture greatly reduced the amount of herbicide applied but also resulted in reduced weed control compared to the flat rate at several locations. These findings prove that accurate SOM and texture data at high resolution combined with herbicide algorithms can be utilized by producers for effective VRA of soil-applied herbicides.

Automated summary

Soil application of pre-emergence herbicides is crucial for grain sorghum production, but adsorption and soil texture variations can impact effectiveness. Variable rate applications (VRA) using high-resolution SOM and texture data with herbicide algorithms can enhance weed control outcomes.