Forest soil bacteria able to produce homo and copolymers of polyhydroxyalkanoates from several pure and waste carbon sources.

Two bacterial strains able to produce polyhydroxyalkanoates (PHAs) from a wide variety of pure carbon sources (dextrose, xylose, sucrose, lactose and glycerol) were isolated from forest soils and identified as Achromobacter mucicolens and Stenotrophomonas rhizophila. Achromobacter mucicolens also produced poly(3-hydroxybutyrate) (PHB) from different wastes (cheese whey, molasses, agave bagasse hydrolysate, nejayote and mango waste pulp). Stenotrophomonas rhizophila, produced the copolymer poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHB-co-HV) from glycerol (7·7 mol% of HV), and from sucrose with addition of propionic or valeric acid (4·5 and 25 mol% of HV, respectively). The copolymers presented a lower melting point (145, 156 and 127°C) and crystallinity (23, 26 and 16%) than PHB. The maximum biopolymer accumulation (PHB) for each strain growing in pure carbon source was as follows: 31·3 g per 100 g dry cell weight (DCW) for A. mucicolens from xylose; and 13·7 g per 100 g DCW for S. rhizophila from sucrose. Regarding the waste carbon sources, the highest PHB accumulation was obtained from agave bagasse hydrolysate (20·4 g per 100 g DCW) by A. mucicolens. The molecular weights of the biopolymers obtained ranged from 200 to 741 kDa. SIGNIFICANCE AND IMPACT OF THE STUDY: The economic cost of the carbon source for the culture of polyhydroxyalkanoates (PHAs)-producing microorganisms is one of the main process limitations. Therefore, it is vital to find versatile microorganisms able to grow and to accumulate homo and copolymers of PHAs from low-cost substrates. In this research, we report two bacterial strains that produce poly(3-hydroxybutyrate), poly(3-hydroxybutyrate-co-3-hydroxyvalerate) or both from at least five pure and five waste carbon sources. These results, by such bacterial strains have not been reported, especially the production of copolymer from glycerol without addition of precursors by Stenotrophomonas rhizophila and the production of PHB from xylose and agave bagasse hydrolysate by Achromobacter mucicolens.

Bacterial immobilization by adhesion onto agave-fiber/polymer foamed composites.

Adhesion of Pseudomonas putida F1 onto agave-fiber/recycled-polyethylene foamed composites was studied under different controlled conditions. The adhesion process was analyzed in batch experiments controlling factors such as pH, contact time, temperature, initial biomass concentration and ionic strength; and was verified by scanning electron microscopy (SEM). The number of adhered bacteria after the experimental time was determined by difference between concentration of suspended cells in NaCl solution contained in two different Erlenmeyer flasks, one of the flasks with composite pellets and the other one without them. The concentration of cells in each flask was obtained using the serial dilution technique. Experimental data analysis showed that adsorption follows first-order kinetics. And it was further corroborated to be an irreversible process. For the first time, an equation is proposed here to predict the correlation between adhered bacteria and aqueous pH. In addition to the obvious reuse of waste material, these results suggested that agave-fiber/polymer foamed composites could be used as support for bacterial immobilization to be applied, among others in environmental processes such as bioremediation and biofiltration of gases with almost limitless possibilities.

Kinetic parameters estimation in an anaerobic digestion process using successive quadratic programming.

In this work, an optimization method is implemented in an anaerobic digestion model to estimate its kinetic parameters and yield coefficients. This method combines the use of advanced state estimation schemes and powerful nonlinear programming techniques to yield fast and accurate estimates of the aforementioned parameters. In this method, we first implement an asymptotic observer to provide estimates of the non-measured variables (such as biomass concentration) and good guesses for the initial conditions of the parameter estimation algorithm. These results are then used by the successive quadratic programming (SQP) technique to calculate the kinetic parameters and yield coefficients of the anaerobic digestion process. The model, provided with the estimated parameters, is tested with experimental data from a pilot-scale fixed bed reactor treating raw industrial wine distillery wastewater. It is shown that SQP reaches a fast and accurate estimation of the kinetic parameters despite highly noise corrupted experimental data and time varying inputs variables. A statistical analysis is also performed to validate the combined estimation method. Finally, a comparison between the proposed method and the traditional Marquardt technique shows that both yield similar results; however, the calculation time of the traditional technique is considerable higher than that of the proposed method.