The broiler (Gallus gallus domesticus) industry in the United States and several other countries routinely includes subtherapeutic levels of antibiotics such as roxarsone, virginiamycin, and bacitracin in the feed to improve bird growth yields. Large fractions of the antibiotics fed to the birds are excreted in manure (litter), which is often applied to soils to improve fertility. Some concerns with this practice are antibiotic-induced alterations in microbially-mediated nutrient cycling, which could influence plant productivity and environmental quality. To investigate this possibility, a series of lab experiments were conducted to determine the effects of increasing levels of the three livestock antibiotics on nitrification, denitrification, and microbial community composition (fatty acid methyl ester profiles) of soils collected along a catena. Roxarsone and virginiamycin significantly influenced microbial community composition and inhibited nitrification in the soils, but only at levels that were several-fold higher than expected in poultry litter-applied soils. Bacitracin did not affect microbial growth, microbial community composition, or nitrification at any concentration tested (up to 500 mg·kg-1). None of the antibiotics influenced denitrification at environmentally-relevant concentrations. Amounts of antibiotics in soil solution were greatly reduced by sorption, which followed Freundlich models in the concentration range of 1 - 500 mg·L-1. Results from this study indicated that addition of roxarsone, virginiamycin, or bacitracin to these soils at environmentally-relevant concentrations would not likely impact microbial community composition, nitrification or denitrification due to intrinsic resistance/insensitivity of microorganisms to these antibiotics and reductions in the bioavailable amounts due to sorption by soil surfaces.
The quality of the resulting pulping continuous digesters is monitored by measuring the Kappa number, which is a reference of residual lignin. The control of the kappa number is carried out mainly in the top of the digester, therefore it is important to get some indication of this analysis beforehand. In this context, the aim of this work was to obtain a prediction model of the kappa number in advance to the laboratory results. This paper proposes a new approach using the Box & Jenkins methodology to develop a dynamic model for predicting the kappa number from a Kamyr continuous digester from an eucalyptus Kraft pulp mill in Brazil. With a database of 1500 observations over a period of 30 days of operation, some ARMA models were studied, leading to the choice of ARMA (1, 2) as the best forecasting model. After fitting the model, we performed validation with a new set of data from 30 days of operation, achieving a model of 2.7% mean absolute percent error.