Evaluation of Nitrogen Bioavailability Predictors for Poultry Wastes

C. Wesley Wood*, Maribeth C. Duqueza, Brenda H. Wood
Agronomy and Soils Department, 202 Funchess Hall, Auburn University, AL 36849-5412, USA

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© 2010 Wood et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Agronomy and Soils Department, 202 Funchess Hall, Auburn University, AL 36849-5412, USA; Tel: 334-844-3997; Fax: 334-844-3945; E-mail:


Long-term land application of manure, litter, and dead-bird compost generated during poultry (Gallus, gallus) production may oversupply nitrogen (N) and result in nitrate (NO3-N) contamination of groundwater. A barrier to judicious use of poultry waste as a fertilizer is the absence of management tools for prediction of waste-derived N released during the plant growing season. This study was conducted to establish an N extraction method for poultry wastes as a predictor of soil N release owing to land application of poultry waste. We correlated N released from 87 different poultry wastes in a 60-day incubation with seven bioavailability predictors. Bioavailability predictors included autoclave-calcium chloride (CaCl2) extraction, bicarbonate extraction, Walkley-Black (acid dichromate) digestion, acid permanganate digestion, pepsin digestion, protein extraction, and barium hydroxide extractable glucose. Results indicate that acid permanganate digestion (r=0.77) has the highest potential for predicting N mineralized from poultry wastes followed by sodium bicarbonate extraction (r=0.51). However, the relationships are not strong enough to indicate that these methods would be useful in a practical, predictive sense.

Keywords: Nitrogen, poultry litter, extractants and bioavailability predictors.