Search

• First experimental verification for synthesizing crystalline cellulose nanoribbon from inexpensive starch in one pot by two phosphorylases. • Degree of polymerization of insoluble synthetic CCNR was affected by the primer concentration based on the fixed concentration of maltodextrin. • CCNR can be used as a Pickering emulsions stabilizer and showed excellent emulsifiability. Nanocellulose has many promising applications such as a green ingredient for Pickering emulsion. Traditional strategies to produce nanocellulose, which are acid or enzymatic hydrolysis and mechanical methods on natural complicated cellulose, are hard to control and can result in significant pollutants during the processes. Herein, we demonstrated a facile and sustainable method for the biocatalytic production of insoluble synthetic crystalline cellulose nanoribbon (CCNR) from cheap maltodextrin by coupling α-glucan phosphorylase (αGP) and cellodextrin phosphorylase (CDP) using cellobiose as a primer. And by optimizing the combination of different αGP and CDP, it turned out that the optimal enzyme combination is αGP from Thermotoga maritime and CDP from Clostridium thermocellum , in which CDP was attached to a family 9 cellulose-binding module. The product yield and degree of polymerization (DP) of insoluble synthetic CCNR was affected by the primer concentration at a fixed concentration of maltodextrin. After optimization of reaction conditions, the highest product yield of insoluble synthetic CCNR was 44.92 % and the highest DP of the insoluble synthetic CCNR was 24 from 50 g 1−1 maltodextrin. This insoluble synthetic CCNR can be used as a Pickering emulsions stabilizer, showing excellent emulsifiability. This study provides a promising alternative for cost-efficient production of insoluble synthetic CCNR which was used as a green emulsion stabilizer. [ABSTRACT FROM AUTHOR]

Hydrophilic PVDF membrane was fabricated in single step via cellulose molecular coating prepared by homogeneous solution of cellulose oligomer synthesized by enzyme catalysis (EC)/Trifluoroacetic acid (TFA). Both smooth and rough coatings can be prepared by regulating the aggregative structure of cellulose molecular coatings. The chemical structures of the cellulose and its coating were confirmed by 1H Nuclear Magnetic Resonance Spectroscopy (1H NMR) and Fourier Transform Infrared Spectroscopy (FTIR). The aggregation structure of the cellulose coating was characterized by wide-angle X-ray diffraction (WAXD). X-ray Photoelectron Spectroscopy (XPS) studies unveiled the strong binding of cellulose molecular to PVDF membranes at the interface. Scanning Electron Microscopy (SEM) morphologies show that the cellulose molecules were uniformly coated on the surface and cross section of the membranes. Water contact angle measurement suggested that cellulose molecular coating possessed high hydrophilicity and wetting rate, giving the PVDF membranes high water flux and excellent anti-fouling performances. The coated membranes also show excellent adsorption and desorption performances for crystal violet (CV). The superior performances of incompletely crystallized cellulose coating over amorphous cellulose coating were attributed to the increased specific surface area resulting from the surface roughness. The construction of cellulose molecular coating with controlled aggregation structure provides a novel efficient technology in the field of purification of wastewater, opening up a new approach to the microstructural manipulation of the hydrophilic coating. A novel strategy to prepare the cellulose molecular coating with versatile functions. [Display omitted] • Hydrophilic PVDF membrane was fabricated in one step via cellulose molecular coating. • The surface roughness of coating can be regulated based on the aggregation state. • Cellulose coating showed high water flux and excellent anti-fouling performances. [ABSTRACT FROM AUTHOR]

• SCCO obtained by bioprocessing was used as a Pickering emulsion stabilizer. • The Pickering emulsions were stable in pH ranges of 2–12 and ionic strength from 0 to 2 M. • The Pickering emulsions showed good tolerance to temperature changes from 2 to 60 °C. • The Pickering emulsions remain stable for no less than 6 months. Nanocellulose are promising Pickering emulsion stabilizers for being sustainable and non-toxic. In this work, semicrystalline cellulose oligomers (SCCO), which were synthesized from maltodextrin using cellobiose as primer by in vitro enzymatic biosystem, were exploited as stabilizers for oil-in-water Pickering emulsions. At first, the morphology, structure, thermal and rheological properties of SCCO suspensions were characterized, showing that SCCO had a sheet morphology and typical cellulose-Ⅱ structure with 56 % crystallinity. Then the kinetic stabilities of emulsions containing various amounts of SCCO were evaluated against external stress such as pH, ionic strength, and temperature. Noting that SCCO-Pickering emulsions exhibited excellent stabilities against changes in centrifugation, pH, ionic strengths, and temperatures, and it was also kinetically stable for up to 6 months. Both SCCO suspensions and their emulsions exhibited gel-like structures and shear-thinning behaviors. These results demonstrated great potential of SCCO to be applied as nanocellulosic emulsifiers in food, cosmetic and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

In this article, a vegetation classification hypothesis based on plant biochemical composition is presented. The basic idea of this hypothesis is that the vegetation species/crops have their own biochemical composition characteristics, which are separable from each other for those co-existing species at a specific region. Therefore, vegetation species can be classified based on the biochemical composition characteristics, which can be retrieved from hyperspectral remote-sensing data. In order to test this hypothesis, an experiment was conducted in north-western China. Field data on the biochemical compositions and spectral responses of different plants and an Earth-observing 1 (EO-1) Hyperion image were simultaneously collected. After analysing the relationship between biochemical composition and spectral data collected from Hyperion, the vegetation biochemical compositions were estimated using sample biochemical data and bands of Hyperion data. The vegetation classification was completed using the biochemical content classifier (BCC) and maximum-likelihood classifier (MLC) with all Hyperion bands (MLC_A) and selected bands (MLC_S), which were used for estimating considered biochemical contents (cellulose and carotenoid). The overall classification accuracy of the BCC (95.2%) was as good as MLC_S (95.2%) and better than MLC_A (91.1%), as was the kappa value (BCC 92.849%, MLC_S 92.845%, MLC_A 86.637%), suggesting that the BCC was a feasible classification method. The biochemical-based classification method has higher vegetation classification accuracy and execution speed, reduces data dimension and redundancy and needs only a few spectral bands to retrieve biochemical contents instead of using all of the spectral bands. It is an effective method to classify vegetation based on plant biochemical composition characteristics. [ABSTRACT FROM AUTHOR]