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Nutrient Variability Following Dairy Manure Storage Agitation

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Applied Engineering in Agriculture. 34(6): 908-917. (doi: 10.13031/aea.12796) @2018
Authors:   Horacio A Aguirre-Villegas, Mahmoud A Sharara, Rebecca A Larson
Keywords:   Dairy manure, Manure agitation, Nutrients, Nutrient variability, Sample size.

Abstract. The nutrient profile in stored manure can be highly variable due to the solids building up at the bottom of the storage over time as unagitated manure is removed. This variability can lead to under- or over-application of nutrients potentially reducing crop yields or increasing nutrient losses, respectively. Agitation of stored manure is a common practice to re-suspend solids providing a more uniform nutrient consistency for application. This study explores the solids and nutrient variability in stored dairy manure after agitation and the relationship between the number of samples and the quality of the nutrient content estimate. A total of 16 dairy facilities across Wisconsin were sampled in the study. Samples were taken during agitation and analyzed for total solids (TS), total Kjeldahl nitrogen (TKN), total ammonia nitrogen (TAN), total phosphorus (TP), total potassium (TK), and microminerals. Overall, TKN, TAN, and TP contents were more uniform than TS. The mean concentrations (wet basis) from the 16 farms range from 2.45% to 15.28% for TS, 0.17% to 0.53% for TKN, 0.01% to 0.33 for TAN, 0.02 to 0.06 for TP, and 0.11% to 0.31% for TK. This range is mostly attributed to the between-farms variability in manure nutrient content. In addition, 54% of the total variation in the TS content was attributable to within-farm sample variability. These results show that TS was variable on farms whereas TKN, TAN, and TP were variable between farms. A random resampling analysis showed that three samples generate a mean between 20% to 30% of the true experimental mean for TKN and TAN whereas nine samples are required to be in this range for TP. Results show that the improvement achieved by adding more samples than 11 is less than 10%.

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