Abstract
A standard method for monitoring temperature in windrow piles of broiler litter to predict microbial population reductions is described. Temperature data collected every 2 min on a 10 cm x 10 cm spatial sampling grid in five identically-constructed litter windrow piles was utilized in this study. A Weibull distribution was fit to mean temperature response (MTR) curves of each pile. Curves were constructed at sample intervals parsed over a range of two to 1000 minutes. No difference in Weibull shape or scale parameters was observed among the analyzed sample intervals. A difference (P<0.05) in mean standard error of Weibull distribution fit parameters was identified between the 200- and 400-min sample intervals. Further analysis between the 200- and 400-minute sample intervals did not reveal a more appropriate value for optimal temporal sampling frequency. Optimal spatial sampling density was characterized using ordinary kriging analysis. Ordinary kriging was used to predict the cross-sectional areas of piles reaching specified time-temperature goals. Eight spatial sampling grid configurations were analyzed. Mean (n=5) predicted cross-sectional area (CSA) reaching 40C for 120 h differed significantly (P<0.05) between the 30 cm x 20 cm and 30 cm x 30 cm grid spacing configurations. Accuracy of predicted pile CSA decreased as spatial sampling density decreased. This data will be beneficial when designing future windrow composting temperature monitoring studies.
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