Swine Slurry Characterization and Prediction Equations for Nutrients on South Korean Farms

摘要

Slurry samples, collected from 23 commercial swine farms in South Korea during January to May 2008, were characterized in terms of various physiochemical parameters: pH, specific gravity (SG), electrical conductivity (EC), total solids (TS), volatile solids (VS), fixed solids (FS), total suspended solids (TSS), total dissolved solids (TDS), biochemical oxygen demand (BOD ₅ ), chemical oxygen demand (COD _cr ), macronutrients (N, P, K, Ca, Na, and Mg), micronutrients (Zn, Fe, Al, Mn, Cu, and Co), heavy metals (Ni, Cr, As, Cd, and Pb), and microbes (total heterotrophic bacteria, coliforms, Escherichia coli, and Salmonella). Average TS was found to be 4.5%, similar to that of other countries. A great variation in physiochemical parameters and nutrient contents were observed in the analyzed samples. This could be attributed to the differences in feeds, use of wash water, rainfall, and slurry age at the time of sampling. TS appeared to be a superior indicator of most nutrients and other parameters. Strong positive relationships (P 0.001) were observed between TS and total N (R 2 = 0.74), total P (R 2 = 0.81), total K (R 2 = 0.59), Ca (R 2 = 0.76), Fe (R 2 = 0.64), Mn (R 2 = 0.60), Mg (R 2 = 0.64), Na (R 2 = 0.51), Al (R 2 = 0.62), BOD ₅ (R 2 = 0.64), COD _cr (R 2 = 0.81), VS (R 2 = 0.99), FS (R 2 = 0.83), and TSS (R 2 = 0.71). The regression equations for Cu and TDS against TS were also obtained (P 0.05) at R 2 = 0.38 and 0.40, respectively. The total heterotrophic bacterial count was significantly correlated with TS. E. coli and Salmonella counts were noted at an average of 5.08 log ₁₀ CFU mL -1 and 3.56 log ₁₀ most probable number (MPN) mL -1 , respectively. In addition, equations for predicting nutrient contents in Korean swine farms are presented in term of TS, an easily determinable parameter. The present study and the data obtained could be used as a guideline for estimating nutrient contribution from swine slurry in agricultural fields, ultimately facilitating the implementation of Good Management Practices in South Korean swine farms