Eco-Efficiency Model for Evaluating Feedlot Rations in the Great Plains, United States

J Environ Qual. 2016 Jul;45(4):1234-42. doi: 10.2134/jeq2015.09.0464.

Abstract

Environmental impacts attributable to beef feedlot production provide an opportunity for economically linked efficiency optimization. Eco-efficiency models are used to optimize production and processes by connecting and quantifying environmental and economic impacts. An adaptable, objective eco-efficiency model was developed to assess the impacts of dietary rations on beef feedlot environmental and fiscal cost. The hybridized model used California Net Energy System modeling, life cycle assessment, principal component analyses (PCA), and economic analyses. The model approach was based on 38 potential feedlot rations and four transportation scenarios for the US Great Plains for each ration to determine the appropriate weight of each impact. All 152 scenarios were then assessed through a nested PCA to determine the relative contributing weight of each impact and environmental category to the overall system. The PCA output was evaluated using an eco-efficiency model. Results suggest that water, ecosystem, and human health emissions were the primary impact category drivers for feedlot eco-efficiency scoring. Enteric CH emissions were the greatest individual contributor to environmental performance (5.7% of the overall assessment), whereas terrestrial ecotoxicity had the lowest overall contribution (0.2% of the overall assessment). A well-balanced ration with mid-range dietary and processing energy requirements yielded the most eco- and environmentally efficient system. Using these results, it is possible to design a beef feed ration that is more economical and environmentally friendly. This methodology can be used to evaluate eco-efficiency and to reduce researcher bias of other complex systems.

MeSH terms

  • Animal Feed*
  • Animal Husbandry*
  • Animals
  • California
  • Cattle
  • Environment
  • Red Meat
  • United States
  • Water

Substances

  • Water