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ASSESSMENT AND IMPROVEMENT OF PROCESS VARIABLE REPRODUCIBILITY IN COMPOSTING REACTORS
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: Transactions of the ASAE. Vol. 44(4): 1022–1030 . (doi: 10.13031/2013.6223) @2001
Authors: P. D. Schloss, L. P. Walker
Keywords: Composting, Power analysis, Sensitivity analysis, Experimental design, Mixing, Inoculum
The high variability found in experimental measurements of composting state variables is the major factor that limits detection of statistically significant relationships between experimental treatments. The use of statistical techniques, such as analysis of variance (ANOVA) and power analysis, have proven to be powerful methods for assessing the effects of experimental variability on the ability to detect statistically significant differences between treatments. In two previous studies, nested ANOVAs and power analyses were used to test the effects of mixing and microbial inoculation on the biological activity in composting reactors as measured by temperature. The primary conclusion from these studies was that within–treatment variability limits the ability to detect statistically significant differences. In addition, it was shown that by controlling initial microbial populations in composting reactors, it is possible to increase process reproducibility. In this article, the results of the two previous studies are synthesized with the aid of sensitivity analyses using empirical mathematical models to describe the effects of temperature and moisture content on process behavior. Finally, a simulated power analysis was performed using the data from an inoculum study to address the effects of variability on experimental design. Combined with power analysis, the sensitivity analysis further demonstrates the great need for improved process reproducibility in the field of composting at both the research and application levels.(Download PDF) (Export to EndNotes)