Wine industry generates large volumes of wastewaters resulting from numerous cleaning operations that occur during the different stages of winemaking. Disposal of these effluents in the environment causes huge problems due to their high organic and inorganic load and seasonal variability. The bioconversion of winery wastewaters in valuable product, such as xanthan, is an important alternative to overcome environmental problems. In this research, the possibility of xanthan production using Xanthomonas campestris on blended wastewaters from different stages of white and rose wine production with initial sugar content of 50 g/L was investigated. In addition to the media parameters (content of sugars, total and assimilable nitrogen, phosphorus, total dissolved salts and apparent viscosity), raw xanthan yield and degree of sugar conversion into product were determined in order to examine the success of xanthan biosynthesis. In applied experimental conditions, xanthan yield of 20.92 and 30.64 g/L and sugar conversion into product of 40.23 and 60.73% were achieved on wastewaters from white and rose wine production, respectively. The results of these experiments suggest that winery wastewaters, after additional optimization of the process in terms of the substrate composition and the cultivation conditions, may be a suitable raw material for industrial xanthan production.
Artificial neural networks (ANNs) have been used to dynamically model cross-flow microfiltration of Streptomyces hygroscopicus fermentation broths. The aim is to predict permeate flux as a function of temperature, feed flow, transmembrane pressure and processing time. Dynamic modeling of microfiltration performance of complex systems (such as broths) is very important for design of new processes and better understanding of the present. The results of ANN model analysis suggest that the coefficients of the determination have high values. The application of the Bayesian regularization gave better results to the performance of the neural network compared to the Levenberg-Marquet algorithm. The optimal number of neurons in the hidden layer is eight. Analysis of the absolute relative error showed excellent permeate flux estimates for 100 % of the data points, with an error less than 5 % for the data obtained during microfiltration in the presence of a turbulence promoter. Whilst in the case of microfiltration without turbulence promoter 90 % of predictions have an error less than 10 %. The results of applying the concept of neural networks in the dynamic modeling of microfiltration of Streptomyces hygroscopicus fermentative broths with and without a turbulence promoter clearly show the validity of proposed method for simulation and prediction of microfiltration experimental results.
This study is concerned with the effect of different initial glycerol
concentrations in the medium on xanthan production by Xanthomonas campestris
ATCC 13951. Xanthan biosynthesis was carried out in batch mode under aerobic
conditions at a temperature of 30oC and agitation rate of 150 rpm for 7 days.
The process efficiency was estimated based on the values of raw xanthan
yield, average molecular weight of the polymer and residual content of
glycerol, total nitrogen and phosphorus. Based on these results, the initial
concentration of glycerol as a carbon source in the production medium was
suggested. In the applied experimental conditions, high raw xanthan yield
(12.15 g/l) of good quality (Mw = 2.86?105 g/mol) and the lowest amount of
residual nutrients (glycerol 2.75 g/l, nitrogen 0.46 g/l and phosphorus 0.67
g/l) was achieved in the medium with the initial glycerol content of 20 g/l.
The obtained results are the basis for optimization of xanthan production on
glycerol containing media in order to increase the product yield and quality.
The success of xanthan biosynthesis depends on several factors, most importantly the genetic potential of the production microorganism and cultivation media composition. Cultivation media composition affects the yield and quality of the desired product as well as production costs. This is why many studies focus on finding cheap alternative raw materials, especially carbon sources, to replace commercially used glucose and sucrose. In addition to the Xanthomonas campestris ATCC 13951 which is the primary industrial production microorganism, other Xanthomonas strains can produce xanthan as well. Under the same conditions, different strains produce different amounts of the biopolymer of varying quality. The aim of this paper is to compare producibility of phytopathogenic X. campestris strains, isolated from the environment with the reference X. campestris ATCC 13951 strain and to estimate the possibility of xanthan production using alternative glycerol-based media than the synthetic glucose-based media. Submerged cultivation on the medium based on glucose or glycerol (2.0 %w/v) was performed using the reference strain and eight isolated X. campestris strains. In order to assess the success of biosynthesis, xanthan yield and rheological properties were determined. Strains isolated from the environment produced yields between 2.98 g/L and 12.17 g/L on the glucose-based medium and 1.68 g/L and 6.31 g/L on the glycerol-based medium. Additionally, X. campestris ATCC 13951 provided the highest yield when using glucose (13.24 g/L), as well as glycerol-based medium (7.44 g/L). The obtained results indicate that in the applied experimental conditions and using all tested strains, glycerol is viable as a carbon source for the production of xanthan.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.