Temperature profiles: variance between piles and where to measure

Temperature profiles: variance between piles and where to measure

Our goal for these analysis was to provide useful guidelines that could be used by a producer for monitoring the temperature of an actively heating stacked poultry litter pile. The raw data from the 6 piles is quite complex. Each pile was divided into a number of sections or "slices" along the longitudinal axis. Each slice contained 2 to 3 probes at various heights. Each probe was recording data every 10 minutes. Figure 1A shows the daily averaged temperature by section for two piles and demonstrates some of the variation within a pile. Figure 1A and 1B also show the difference between a very hot pile (Pile 6) versus the coolest pile (Pile 2).

We constructed a statistical model (Model 1, Table 2) to predict the temperature of stacked poultry litter based on the elapsed time after the pile is stacked, the height of the pile from the ground and the depth into the side of the pile that the temperature is measured. This model is designed to answer the question of what effect "pile" (as a categorical variable) has on the temperature profile demonstrated by the stacked litter. Secondly, this model addresses the question of how the coordinates chosen to measure the temperature (height by depth) affect the temperature profile that will be observed in stacked litter piles. The details of the model are given in Appendix 1. A.

Four of 5 piles had very similar temperature profiles for 4 of 5 piles, but one pile (Pile 2) was on average 7.5 C cooler at any point in time. As previously noted, Pile 2 was grossly different than the other piles tested and had lower mean Aw and DM values. We address the reasons why Pile 2 acted differently than the other piles in our later analysis. We concluded that the heating behavior of piles was fairly homogeneous over time despite coming from different farms. This homogeneity is an important feature for determining general guidelines that can be used by producers and regulatory agencies.

Notable, the piles were hot on arrival, when off-loaded from the trucks as is reflected by Day 0 temperature readings. Possibly, this is due to the increased oxygenation and microbial metabolism that occurs as a result of scraping and loading the litter.

Overall, the piles continued to accumulate heat for about 10 days, then slowly cooled. The temperature profiles for our stacked litter piles are shown in Figure 2 for a fixed depth (36") and height (12"). Temperatures peaked between 2 and 10 days after stacking and decline over the next 10 days.

Figures 2 and 3 show the effect of changing the depth and height at which the temperature measurement is performed on the temperature profile that would be observed for a stacked poultry litter pile. Figure 2 shows that the surface heats more rapidly than the deeper portions of the pile. The maximum temperature generated by the microbial activity within the pile appears to occur 5 to 7 days after stacking in deeper (5' depths) portions of the pile. This means that minimal "safe" temperatures, those necessary to kill microbial pathogens are depth dependent. Therefore regulations stipulating how a stacked poultry litter pile should be monitored for safety would need to reflect this.

Similarly, we demonstrate in Figure 3 that the height from the base of the pile is positively correlated with temperature at any point in time. Temperatures measured near ground level would be expected to be approximately 5 degrees lower than temperatures measured at 3 feet from the base of the pile at any point in time (with depth constant at 3 feet).

From our data we can conclude that stacked poultry litter piles are dynamic systems, with temperature changing over time and changing at variable rates at different points within the pile. Therefore good management practices aimed at determining that minimal heating has occurred (i.e., that required to eliminate pathogens) must incorporate guidelines for taking temperature measurements that are specific for the time after stacking, and the height and depth at which the readings are taken. For example, if temperatures are measured at very deep locations in a pile that has been recently stacked, the readings may be misleadingly low because the maximum temperatures in deep sections of the pile are reached up to 10 days after stacking.