Description of a Sample of Liquid Dairy Manures and Relationships Between Analytical Variables

A sample of 93 liquid dairy manures from Lombardy in northern Italy was analysed to determine manure composition, and regression equations for the prediction of manure composition were developed. The manures had a mean (and standard deviation) dry matter content of 95 (32) g kg-1, with total Kjeldahl nitrogen, ammonium nitrogen, carbon, phosphorus and potassium concentrations of 3.75 (1.00), 1.48 (0.45), 37 (13), 0.65 (0.24), 2.62 (0.77) g kg-1 [raw manure], respectively. It is concluded that the high variability in composition of dairy manures is not compatible with the use of tabulated average values in nutrient management plans, and requires traditional or simplified analyses to reduce fertiliser input in the agro-ecosystems and to preserve crop yield. Linear regressions were used to estimate the organic matter and nutrient content of the manures from the dry matter content and the electrical conductivity. Because electrical conductivity was only measured on manures with dry matter less than 103 g kg-1, regressions based on electrical conductivity were developed on a reduced sub-set of 38 samples. The electrical conductivity is an acceptable predictor for ammonium nitrogen, with a coefficient of determination (R2) of 0.76. Carbon is well predicted based on dry matter with an R2 of 0.98, while phosphorus and total Kjeldahl nitrogen are estimated using both dry matter and electrical conductivity (R2 = 0.69 and 0.91, respectively). Unreliable predictions are obtained for potassium. It is concluded that the electrical conductivity and the dry matter content are the basic data required for low-cost estimates of manure nutrient concentrations and are useful to improve the effectiveness of nutrient management plans.