Evaluation of physicochemical models for rapidly estimating cattle manure nutrient content

With the increasing concern over the potential pollution from farm wastes, there is a need for rapid and robust methods that can evaluate livestock manure nutrient content. Physicochemical models which related cattle manure nutrient content (ammonium nitrogen, AN; total potassium, TK; total nitrogen, TN; total phosphorus, TP) to its physicochemical properties (specific gravity, dry matter, electrical conductivity, pH) have been reported by previous researchers. This study reviewed previous physicochemical models and compiled the observed data drawn from a wide selection of sources to validate various physicochemical models. Several statistical parameters, including the coefficient of determination R2, the modelling efficiency statistic, the mean squared error of prediction, the mean bias, and the linear bias, were calculated to evaluate model performance on the data sets. The results showed that the relationship (AN = 0.136EC − 0.523) developed by , provided satisfactory predictions for AN with R2 = 0.75. The equation (TP = 0.01DM + 0.057) developed by gave reasonable prediction for TP with R2 = 0.77. The corrected TK model (TK = 0.184EC + 0.042) greatly reduced systemic errors and hence improved TK prediction with R2 = 0.87. Compared with prediction models for other nutrient contents, TN physicochemical models provided far from satisfactory predictions but equations used by was the best (R2 = 0.62).