Moment Analysis of Data on Sieving to Quantify Forage Digesta Particle Size Distributions

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Abstract
Standard techniques for particle size analysis typically assume a lognormal distribution. Assumptions of a lognormal distribution were invalid for mass-size frequency data resulting from wet sieving of rumen digesta particulate material. An alternative approach used statistical moments to describe these data. Moment analysis was appropriate and did not suffer from the assumption of a longnormal distribution. Moments provided more definitive evidence of treatment effects for central tendency and dispersion of rumen digesta particle size distributions than procedures based on a longnormal assumption. Skewness and kurtosis could also be evaluated using moments.