Volume 78, Issue 6

Camellia oleifera Abel. shell (COS) is an agricultural waste in quantities exceeding a million tons annually. The ultrastructure of the COS cell wall and the distribution of lignocellulose components were investigated. The microscopic results showed that COS contains two types of cells, sclerenchyma cells (SC) and parenchyma cells (PC). SC contained 50.4 % hemicellulose, 17.6 % cellulose and 30.9 % lignin while PC contained 35.2 % hemicellulose, 23.7 % cellulose and 35.0 % lignin. The distribution of lignocellulose components in COS is non-homogeneous. Lignin is alternately distributed with polysaccharides in the PC wall. In SC, hemicellulose is mainly present in the secondary wall S 2 , while lignin was mainly found in the compound middle lamella, and cellulose mainly exists in the secondary wall, S 3 . A comprehensive model of the cell wall ultrastructure and lignocellulose distribution of COS was given. This study provides a fundamental understanding of COS cell walls and can aid in the future graded utilization of COS.

The porosity of cell walls, as indicated by diffusion of rhodamine B dye, in the wood of Douglas fir, radiata pine, New Zealand red beech and Shining gum was compared under dynamic conditions using fluorescence recovery after photobleaching. The comparative diffusion rate was estimated using the half-life of fluorescence recovery under water-saturated conditions performed on transverse sections. All four wood species showed similar diffusion behaviour in tracheid or fibre cell walls with slower diffusion in the middle lamella layer compared to the secondary cell wall. Within the S 2 layer of the secondary wall two regions were observed, an outer region with a slow diffusion rate and an inner region with a higher diffusion rate. Vessel cell walls showed slightly slower diffusion rates. Diffusion of rhodamine B dye appears to occur primarily along the fibre axis and is probably somewhat different to water in its behaviour. This suggests that pores are aligned with cellulose microfibrils. The dye diffusion rate was estimated to be in the range of 50–100 nm 2  s −1 . This has implications for understanding wood drying behaviour and chemical modification of wood by infiltration with small molecules as well as water storage in living trees.

Terahertz waves hold significant potential for applications in wood identification, owing to their good penetration and distinctive fingerprints in wood. This study focuses on wood samples from five different Guibourtia species as the research objects. The terahertz time-domain spectroscopy (THz-TDS) is employed to acquire the spectroscopic signals of the wood samples and to extract their optical parameter data. The THz refractive indices are dimensionally reduced through principal component analysis (PCA), and three machine learning models, namely partial least squares-discriminant analysis (PLS-DA), random forest (RF), and support vector machine (SVM), are employed to classify the wood of five different Guibourtia species. Time delays of the wood samples from five different Guibourtia species are concentrated in the range of 60–62 ps and exhibit different amplitudes in the frequency domain. Refractive indices showed significant variations within the THz band. PCA for dimensionality reduction of terahertz time-domain spectral data significantly improves the recognition rate of machine learning models. Applying PCA to the refractive index data, the RF model achieves a highest recognition rate of 96.9 % and an overall classification accuracy of 98 %. Current results demonstrate that THz-TDS enables rapid, accurate, and non-destructive classification and identification of wood from the Guibourtia species.

Pretreatment serves as an important step in maximizing the efficient utilization of woody biomass feedstock. This study focused on enhancing the component and structural properties of apple wood to optimize the utilization of apple wood resources effectively. This study presents the optimization of, the apple wood pretreatment system, combining bioenzyme and hydrothermal treatments. This study aimed to investigate the effect of different bioenzyme pretreatment conditions on the components and structural properties of apple wood extract and to analyze the feasibility of enzyme solution reuse. Fourier transform infrared spectroscopy analysis revealed an increase in cellulose content in the wood flour following enzyme treatment. Concurrently, changes in characteristic peaks indicated an increased hemicellulose content and a reduction in lignin content after the pretreatment, correlating with fraction analysis results. Scanning electron microscopy illustrated that the dense structure of the fiber surface was disrupted after treatment. Notably, the results indicated that the recovered biocomposite enzymes exhibited excellent activity, suggesting their potential for reuse.