Cryptococcus laurentii: a wild yeast for xylanase production from agricultural by-products.

The development of technologies that allow the production of enzymes at a competitive cost is of great importance for several biotechnological applications, and the use of agro-industrial by-products is an excellent alternative to minimize costs and reduce environmental impacts. This study aimed to produce endo-xylanases using agro-industrial substrates rich in hemicellulose as sources of xylan in culture media. For this purpose, the yeast Cryptococcus laurentti and five lignocellulosic materials (defatted rice bran, rice husk, corn cob, oat husks, and soybean tegument), with and without pretreatment, were used as a source of xylan for enzyme production. To insert the by-products in the culture medium, they were dried and treated (if applicable) with 4% (w.v-1) NaOH and then added in a concentration of 2% (w.v-1). The cultures were agitated for 96 h, and the aliquots were removed to determine the enzymatic activities. Among the by-products studied, the maximum activity (8.7 U. mL-1 at pH 7.3) was obtained where rice bran was used. In contrast, corn cob was the by-product that resulted in lower enzyme production (1.6 U.mL-1). Thus, the defatted rice bran deserves special attention in front of the other by-products used since it provides the necessary substrate for producing endo-xylanases by yeast.

A rapid method for the assessment of the vitality of microorganisms using flow cytometry.

Cultivability, viability, and vitality make it possible to characterize the behavior of a cellular population. Vitality was assessed using the kinetic parameters of specific metabolisms depending on whether the strains were used, for example, for the acidification of lactic acid bacteria or for CO2 production in fermenting yeasts. However, these methods are time-consuming. We developed a cytometric descriptor based on the energy-dependent extrusion of carboxyfluorescein from cells, subsequent to carboxyfluorescein diacetate staining, and compared it to the measurements of metabolic activities of various bacteria and yeasts. For all of the microorganisms tested, the cytometric descriptor ΔFI15 was well correlated with the results of the metabolic measurements and, moreover, has the advantage of being easier and faster to use than metabolic methods. It can be very useful for evaluating the vitality of the starters before inoculation in industrial processes.

Compilation of data on model cheeses composition, rheological and sensory properties, from six research projects exported from the BaGaTel database.

This paper presents data on model cheeses extracted from the BaGaTel database. The data are issued from 6 different research projects in which data on composition, rheological and sensory properties were collected. The manufacturing of the 68 different samples is described. For each model cheese, data are available on final composition (lipid, protein, water, sodium), rheological properties (uniaxial compression), sensory profile analysis (texture, taste, aroma) and for some cheeses chewing activity and in vivo sodium release were also measured. The material and methods used are detailed. Scatter plots of representation of the values for each variable and each project are plotted. Pearson correlations between variables are given for specific subsets of data. The dataset is hosted in an open access data repository. This dataset will allow a comparison of sensory properties of cheeses varying in lipid, protein water and salt content and can be used for the reformulation of cheeses made with a low salt and fat content to follow food-related health recommendations, whilst fulfilling good sensory qualities.

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity.

Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the multiscale dynamics of those systems using computing science. A robust predictive mathematical tool is implemented for this sector and applied to the wine industry being easily able to be generalized to other applications. Grape berry maturation relies on complex and coupled physicochemical and biochemical reactions which are climate dependent. Moreover one experiment represents one year and the climate variability could not be covered exclusively by the experiments. Consequently, harvest mostly relies on expert predictions. A big challenge for the wine industry is nevertheless to be able to anticipate the reactions for sustainability purposes. We propose to implement a decision support system so called FGRAPEDBN able to (1) capitalize the heterogeneous fragmented knowledge available including data and expertise and (2) predict the sugar (resp. the acidity) concentrations with a relevant RMSE of 7 g/l (resp. 0.44 g/l and 0.11 g/kg). FGRAPEDBN is based on a coupling between a probabilistic graphical approach and a fuzzy expert system.