Physicochemical and microbial analysis of feces from horses fed diets containing citrus pulp.

This study aimed to evaluate the e ect of diets containing increasing levels of citrus pulp on the physic-chemical and microbiological characteristics of horses feces. Five mares, at an average age of 3.5 years old and body weight of 492 ± 44.5 kg were arranged in a 5 x 5 Latin Square. The experimental diet consisted of 60% coast-cross hay and 40 % of concentrate with increasing levels of citrus pulp (0, 7, 14, 21, and 28 %). To determine the fecal pH, samples were collected directly from the oor, immediately after defecation, in the rst feces the day at 07:00 a.m., and color and fecal consistency were evaluated. For microbiological analysis, an aliquot was reserved in plastic bags, frozen, and sent to the microbiological laboratory for further analysis. Lactic acid bacteria were counted for Lactobacillus spp. and Streptococcus spp. from fecal samples under anaerobic conditions. The diet produced di erences (P<0.05) in feces consistency 98% had normal and rm stools, while 2% had loose ruminant-type feces. We observed no di erence (P<0.05) for color, verifying 100% of greenish feces, normal for equines. There was no e ect (P>0.05) on pH and on the number of Lactobacillus spp. and Streptococcus spp. The inclusion of up to 28% citrus pulp concentrates for horses did not promote change in the physio-chemical characteristics and on the population of lactic acid-producing bacteria in feces.

On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.