Waste cotton fibers are an ideal raw material for extracting nanocellulose crystals (CNCs), benefitting from their high cellulose content. In this study, the waste cotton fibers from the calendering finishing process were used to extract CNCs by sulfuric acid, TEMPO oxidation, and phosphoric acid methods, aiming to create a new way to reutilize the waste cotton fiber and also to verify the practicability that the phosphoric acid method can replace sulfuric acid and TEMPO oxidation methods. The CNCs obtained from the three methods are all in cellulose I state with an average length of 200-500nm and diameter of 15-20nm, indicating that the waste cotton fiber can extract CNCs. However, the CNCs from the phosphoric acid method showed the highest thermostability but the lowest crystallinity, while the ones from the sulfuric acid and TEMPO oxidation methods had higher crystallinity but lower thermal stability. Overall, the three methods are all acceptable for preparing CNCs, but the phosphoric acid method has more significant potential due to its low cost, environmental friendliness, and safety. Graphical abstract
Yan Jun,Huang Xiao-Ping,Wu Ye-Yu,Du Fang-Kai,Tan Xue-Cai,Wang Qi,Zhu Wei-Wei
Abstract Near-infrared (NIR) diffuse reflectance spectroscopy has become an attractive technique for quality assurance of fruits, drugs, vegetables, and foods. In this work, the information on chemical composition of Siraitia grosvenorii was acquired by NIR, and then a calibration model for the prediction of total sugar content (TSC) was developed using chemometric techniques. One hundred and fifty samples were used as calibration set to develop model, while 40 unknown samples were used for prediction, using phenol-concentrated sulphuric acid assay as reference value. Several spectra preprocessing methods and wavelength selection techniques combined with partial least squares regression were compared, and then standard normal variate coupled with Savitzky–Golay derivative was selected for spectra processing and competitive adaptive reweighted sampling method was applied to extract the informative wavelengths related to the prediction of TSC. The performance of the obtained model has been evaluated by external validation, the square of correlation coefficient (R 2 ) are 0.9097 for a separate blind set consists of 40 unknown samples. Additionally, the result of paired t test ( p = 0.3608) illustrated that there is no significant differences between NIR and wet chemistry analysis. These results demonstrated that NIR spectroscopy has the potential to be a time saving and cost-effective method for the determination of the TSC in S. grosvenorii . Graphic abstract
危险品化学品经营许可证（带存储）