/AnMtgsAbsts2009.55228 Remote Sensing Methods for Identifying Potential Emissions From Feedlot Surfaces.

Tuesday, November 3, 2009
Convention Center, Exhibit Hall BC, Second Floor

Bryan Woodbury, Roger Eigenberg, Vince Varel and Mindy Spiehs, USDA-ARS, U.S. Meat Animal Res. Center, Clay Center, NE
Abstract:
Remote sensing methods have been developed to measure manure accumulation patterns on feedlot surfaces.   This study was designed to determine if this sensor data could be used to predict differences in volatile fermentation products and the areas in the pens where they are produced following a rainfall event.  Finishing steers were fed either a corn- or wet distillers grains with solubles (WDGS)-based diet. Soil samples were collected from 20 sites by removing all soil in a 20 cm diameter to a depth of 10 cm. Soils were mixed and incubated for three days at room temperature.  Soils collected from pens with animals fed the corn-based-diet had greater average straight-chained volatile fatty acids (VFA) production.  Soils collected from pens with animals fed the WDGS diet had greater branched-chained VFA production.  Linear regression models from the sensor data were used to estimate the percent pen surface area contributing to specified volatile concentration ranges.  It was found 65% of the corn-base diet pen surface produced greater than 40 mmol kg1 straight-chained VFA while the WDGS pens only had 51% of the surface area in the same concentration range.  The opposite trend was found for the branched-chained VFAs in that the corn-based diet had 47 % of the pen surface area produce 6 mmol kg-1 or greater while the WDGS diet had 61%.  Diet appears to affect the types and amounts of VFAs produced following a rainfall event.  The WDGS diet appears to produce higher branched-chained VFAs, which can be considered more offensive.  Understanding accumulation patterns and the ability to predict odorant production can be used to develop precision management practices to mitigate contamination from animal feeding operations.