ARS | Publication request: HEAVY METAL LOADING RATES ON SOILS OF WISCONSIN DAIRY FARMS

Submitted to: Sustainable Land Application Conference
Publication Type: Proceedings
Publication Acceptance Date: October 15, 2003
Publication Date: January 4, 2004
Citation: Mccrory, D., Powell, J.M., Jackson-Smith, D., Saam, H., Li, Y. 2004. Heavy metal loading rates on soils of wisconsin dairy farms. In: Sustainable Land Application Conference, January 4-8, 2004, Buena Vista, Florida. p.112.

Technical Abstract: Heavy metal build up in agricultural soils has the potential to reduce soil productivity and poses a risk to human health. The content of heavy metals (Copper, Zinc, Cadmium, Nickel, Arsenic, Chromium and Lead) in dairy manure from 52 randomly selected Wisconsin farms were determined to assess the potential contribution dairy manure may make to heavy accumulation in agricultural soils. Heavy metal loading rates for 2002 were calculated using a simple model constructed from standards for manure (liquid and solid) mass excretions, heavy metal concentrations and farmer-estimated areas of fields that receive manure. Initial results indicated heavy metal loading rates associated with dairy manure are considerably below current USEPA regulations. The model was corrected to include an 'apparent manure collection' (AMC) component, calculated from the relative time lactating cows spent in areas where manure was collected and not collected (e.g. exercise lots). Results indicated 37% of farms collected all manure. The remaining farms collected on average 61% of manure. Relationships between AMC (y) and the number of lactating cows (x) for these farms was y=0.4415x + 40.561 Rsq=0.24, indicating that the smaller the herd the lower the AMC. Assuming exercise areas to be 0.5ha in size, the model indicated that mean Nickel loading rates were approximately 1.23 kg ha-1 and exceed current USEPA regulations. Further work will improve the model by identifying other heavy metal inputs to agricultural soil; actively track manure loading rates, and utilize GPS to determine the size of exercise areas.