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The optimization of an alkaline pretreatment process for the delignification of sugarcane bagasse (SCB) to enhance the subsequent enzymatic hydrolysis was performed according to the Doehlert uniform shell design. In this experimental design, the effect of two factors—potassium hydroxide (KOH) concentration and autoclaving time at 121 C (1 atm)—on cellulose, hemicellulose, or the total polysaccharide and lignin content in SCB was evaluated. This response surface methodology revealed that KOH concentration is the factor that most influences the chemical characteristics of treated SCB (SCBt), with optimal conditions for the highest delignification being KOH in the range 5–10% (w/v) and an autoclaving time of 35 min, which provides an average of 97% total polysaccharides without inhibitor accumulation (furfural, 5-hydroxymethyl furfural) and #5% lignin. SCBt samples from two pretreatment conditions (KOH 3.25% – 13 min; KOH 10% – 35 min) were selected, based on the greatest delignification (70–74%) and polysaccharide availability (95–97%) after pretreatment, and further hydrolysed for fermentable sugar production. High sugar yields were obtained from both the pretreated samples (866 to 880 mg sugar per g biomass, respectively) in contrast with the 129 mg sugar per g raw biomass obtained from untreated SCB. These results demonstrate the effectiveness of KOH alkali pretreatments, which improves the overall digestibility of raw SCB polysaccharides from about 18% up to 91%. However, harsh alkali treatment (KOH 10%) is the most effective if the highest glucose/xylose ratio in the final sugar-rich hydrolysate is the aim. Hence, the use of sugar-rich hydrolysates obtained from SCBt as the carbon source for industrial purposes may provide a sustainable and economic solution for the production of bio-based added-value products, such as second generation (2G) bioethanol.

With the increasing awareness on the toxicity of several synthetic dyes, demand for pigments from natural sources, such as microbial carotenoids, has gained interest as a promising safe alternative colour additive. In this study, a surface response methodology based on the Doehlert distribution for two factors [% of glucose in a mixture of glucose + fructose (10 g/L total sugars), and sulfate concentration] was used towards the optimal carotenoids production by Gordonia alkanivorans strain 1B in the presence of light (400 lx). Time influence on pigment production by this bacterium was also evaluated, as well as the cell viability profile during longer incubation periods at optimal conditions. Indeed, the highest carotenoid production (2596-3100 mu g/g(DCW)) was obtained when strain 1B was cultivated in the optimal conditions: glucose 10 g/L and sulfate >= 22 mg/L, in the presence of light for 19 days at 30 degrees C, 150 rpm. Flow cytometry showed that the highest production was somehow related with the cellular stress. These results highlight the great potential of strain 1B as a new hyperpigment producer to be exploited towards several applications. info:eu-repo/semantics/publishedVersion

Biopesticides based on natural endophytic bacteria to control plant diseases are an ecological alternative to the chemical treatments. Bacillus species produce a wide variety of metabolites with biological activity like iturinic lipopeptides. This work addresses the production of biopesticides based on natural endophytic bacteria, isolated from Quercus suber. Artificial Neural Networks were used to maximize the percentage of inhibition triggered by antifungal activity of bioactive compounds produced by Bacillus amyloliquefaciens. The active compounds, produced in liquid cultures, inhibited the growth of fifteen fungi and exhibited a broader spectrum of antifungal activity against surface contaminant fungi, blue stain fungi and phytopathogenic fungi. A 19-7-6-1 neural network was selected to predict the percentage of inhibition produced by antifungal bioactive compounds. A good match among the observed and predicted values was obtained with the R2 values varying between 0.9965 – 0.9971 and 0.9974 – 0.9989 for training and test sets. The 19-7-6-1 neural network was used to establish the dilution rates that maximize the production of antifungal bioactive compounds, namely 0.25 h-1 for surface contaminant fungi, 0.45 h-1 for blue stain fungi and between 0.30 and 0.40 h-1 for phytopathogenic fungi. Artificial neural networks show great potential in the modelling and optimization of these bioprocesses., Les biopesticides à base de bactéries endophytes naturelles pour lutter contre les maladies des plantes constituent une alternative écologique aux traitements chimiques. Les espèces de Bacillus produisent une grande variété de métabolites biologiquement actifs tels que les lipopeptides ituriniques. Cette étude porte sur la production de biopesticides par des bactéries endophytes naturelles isolées du Quercus suber L. Des réseaux neuronaux artificiels ont été utilisés pour maximiser le pourcentage d’inhibition provoquée par l’activité antifongique des composés bioactifs produits par Bacillus amyloliquefaciens. Les composés actifs, produits en culture liquide, ont inhibé la croissance de 15 champignons et avaient un spectre d’activé antifongique plus large contre les contaminants fongiques de surface, les champignons de bleuissement et les champignons phytopathogènes. Un réseau neuronal 19-7-6-1 a été choisi pour prédire le pourcentage d’inhibition produit par les composés bioactifs antifongiques. Une bonne concordance entre les valeurs observées et prédites a été obtenue; les valeurs de R2 variaient de 0,9965 a` 0,9971 et de 0,9974 a` 0,9989 pour les bases d’apprentissage et de test. Le réseau neuronal 19-7-6-1 a été utilisé pour établir les taux de dilution qui maximisent la production des composés bioactifs antifongiques, nommément 0,25 h−1 pour les contaminants fongiques de surface, 0,45 h−1 pour les champignons de bleuissement et entre 0,30 et 0,40 h−1 pour les champignons phytopathogènes. Les réseaux neuronaux artificiels ont un potentiel élevé pour modéliser et optimiser ces processus biologiques.

Biodesulfurization can be a complementary technology to the hydrodesulfurization, the commonly physical-chemical process used for sulfur removal from crude oil. The desulfurizing bacterium Gordonia alkanivorans strain 1B as a fructophilic microorganism requires fructose as C-source. In this context, the main goal of this work was the optimization of a simultaneous saccharification and fermentation (SSF) approach using the Zygosaccharomyces bailii strain Talf1 crude enzymes with invertase activity and sucrose as a cheaper fructose-rich commercial C-source (50% fructose) towards dibenzothiophene (DBT) desulfurization by strain 1B. The determination of optimal conditions, for both sucrose hydrolysis and DBT desulfurization was carried out through two sequential experimental uniform designs according to the Doehlert distribution for two factors: pH (5.5-7.5) and temperature (28-38 °C), with the enzyme load of 1.16 U/g/L; and enzyme load (0-4 U/g/L) and temperature (28-38 °C), with pH at 7.5. Based on 2-hydroxybiphenyl production, the analysis of the response surfaces obtained pointed out for pH 7.5, 32 °C and 1.8 U/g/L as optimal conditions. Further optimized SSF of sucrose during the DBT desulfurization process permitted to attain a 4-fold enhanced biodesulfurization. This study opens a new focus of research through the exploitation of sustainable low cost sucrose-rich feedstocks towards a more economical viable bioprocess scale-up.