Particleboards were prepared with thinning wood of Cunninghamia lanceolata (Chinese fir) and wood shavings of waste Uncaria sinensis branches by using melamine-urea-formaldehyde resin as the adhesive. Influences of particle mass ratio of C. lanceolata to Uncaria, adhesive loading, and target density on internal bonding strength (IB), modulus of rupture (MOR), modulus of elasticity (MOE), thickness swelling rate of water absorption (TS), and water absorption (WA) of the composite particleboard were investigated. Results showed that: (1) IB, MOR, MOE, 2h-TS, and 2h-WA of pure C. lanceolata particleboard met service requirements of type-P2 furniture particleboard of GB/T 4897-2015. (2) With the increase of Uncaria particles, IB of composite particleboard decreased gradually, while MOR, MOE, TS, and WA first increased and then decreased. The best comprehensive performances were achieved when the mass ratio of C. lanceolata to Uncaria was 75:25, manifested by 1.5 MPa of IB, 21.3 MPa of MOR, 2140 MPa of MOE, 2.4% of 2h-TS and 12.3% of 2h-WA. These performances basically meet the service requirements on type-P3 of the standard. (3) It can make C. lanceolata fir/Uncaria particleboard meet requirements on type-P4 heavy-load particleboard of the standard by increasing target density and adhesive loading appropriately. (4) The C. lanceolata/Uncaria composite particleboard showed higher thermostability and fire resistance.

The laccase activity changes of the Auricularia cornea var. Li strain were studied over a continuous 9-day period using different carbon sources, nitrogen sources, and lignocellulose as liquid fermentation inducers. The results showed that the addition of carbon sources, nitrogen sources, and alkaline lignin all stimulated Auricularia cornea var. Li to secrete laccase and promoted the accumulation of mycelial biomass. Both carbon and nitrogen deficiencies could stimulate Auricularia cornea var. Li to produce more laccase, but they were detrimental to the accumulation of mycelial biomass. Maltose and peptone should be prioritized as materials for cultivating high-laccase-producing Auricularia cornea var. Li strains through liquid fermentation. Lignocellulosic biomass could significantly enhance laccase activity in Auricularia cornea var. Li. During the cultivation of Auricularia cornea var. Li., wheat bran and cottonseed hulls that produced high levels of laccase should be recommended. This study partially revealed the laccase production characteristics of Auricularia cornea var. Li and identified culture substances that were beneficial for laccase secretion during different growth stages of the mushroom. The results provide a foundation for improving the yield and quality of Auricularia cornea var. Li.

Camellia oleifera is a multipurpose plant resource that contains flavonoids. To explore the differences in the characteristics and metabolic pathways of flavonoids in Camellia oleifera flowers from different plantations, this study compared the differences in the water content, total ash content, ethanol soluble extract, and total flavonoid content of samples from six plantations. Widely targeted flavonoid metabolomics techniques were used to analyze the metabolic characteristics of the different plantations. There were significant differences in total flavonoid content among the different plantations (P < 0.05), with Tianzhu County having the highest total flavonoid content (average value of 13.60 mg/g) and Liping County having the lowest total flavonoid content (average value of 2.39 mg/g). UPLC-MS/MS revealed a total of 13 categories and 758 flavonoid metabolites, among which flavonols, flavonoids, and tannins were the main flavonoid compounds. A total of 266 differentially abundant metabolites were screened via the OPLS-DA model, and KEGG enrichment analysis revealed that the enrichment pathways of differentially abundant metabolites between different plantations were related mainly to the biosynthesis of secondary metabolites, flavonoid biosynthesis, metabolic pathways, etc. This study provides a theoretical reference for the subsequent development and utilization of Camellia oleifera resources, especially in the utilization of Camellia oleifera flower resources.

In recent years, the process of optimizing the design of natural fiber reinforcement in natural fiber composites (NFCs) with distinct properties has been redefined through the application of machine learning (ML). This work elucidates the functions of the types and applications of the ML algorithms and evolutionary computing techniques, with a particular focus on their applicability within the domain of NFCs. Moreover, the solution methodologies and associated databases were employed throughout various stages of the product development journey, from the raw material selection through the final end-use application for the NFCs. The strengths and limitations of the ML in the NFCs industry, together with relevant challenges, such as interpretability of ML models, in materials science was detailed. Finally, future directions and emerging trends in the ML are discussed.