•Hardwood prediction models were built using ATR-FTIR and FT-NIR.•ATR-FTIR modeling analysis could be used for screening purposes.•FT-NIR–PLS models can be used for quantitative analysis of specific samples.•PCR performed better for interpretation while PLS performed better for prediction.This study used Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and Fourier transform near-infrared (FT-NIR) spectroscopy with principal component regression (PCR) and partial least squares regression (PLS) to build hardwood prediction models. Wet chemistry analysis coupled with high performance liquid chromatography (HPLC) was employed to obtain the chemical composition of these samples. Spectra loadings were studied to identify key wavenumber in the prediction of chemical composition. NIR–PLS and FTIR–PLS performed the best for extractives, lignin and xylose, whose residual predictive deviation (RPD) values were all over 3 and indicates the potential for either instrument to provide superior prediction models with NIR performing slightly better. During testing, it was found that more accurate determination of holocellulose content was possible when HPLC was used. Independent chemometric models, for FT-NIR and ATR-FTIR, identified similar functional groups responsible for the prediction of chemical composition and suggested that coupling the two techniques could strengthen interpretation and prediction.

Controllable degradation of natural biomaterials for tissue engineering is a big issue that has to be solved. In this paper, sodium alginate was aldehyde-modified and the product (oxidized sodium alginate) was degraded in vitro. Then, oxidized sodium alginate was cross-linked with calcium chloride and its degradation performance was studied. Results showed that the degradation rates of porous materials increased while pH values of degradation liquid decreased, which was proportional to the degree of oxidation. Lotus fibers were carboxyl-modified with TEMPO/NaClO/NaBr system and then lotus nanofibers were obtained. It is found that the degradation rates of the oxidized sodium alginate porous materials which were added lotus nanofibers were slow. Thus, the blending porous materials are expected to be used in medical fields.

The main objective of this research was to construct accurate near-infrared reflectance (NIR) models of wood chemistry. Wet chemistry procedures and high-performance liquid chromatography methods were employed to analyze the chemical composition of southern pine. The NIR spectra were collected from 21 wood samples, which were milled down to different particle size classes. NIR calibration and prediction models were established using two modeling methods with different pretreatments. Furthermore, the spectrum range used in the NIR models was refined to achieve higher prediction accuracy. Results showed that NIR model precision could be improved considerably by decreasing the particle size to a very fine powder coupled with a targeted spectrum range. Superior prediction models for lignin and holocellulose content were constructed, while models for extractives and cellulose contents were also strong.

The antifungal properties and cytotoxicity of alginate fibers were investigated to widen their application in tissue engineering. Calcium, zinc, and copper alginate fibers were separately prepared by replacing Na+ with Ca2+, Zn2+, or Cu2+. The antifungal properties of the three alginate fibers were studied after coming into contact with Candida albicans. Then, the fungal inhibitory rates were measured using the plate-count method following shake-flask test. Moreover, an inhibition-zone test and observation by scanning electron microscopy were carried out. The inhibitory rate of the calcium, copper, and zinc alginate fibers were, respectively, 49.1, 68.6, and 92.2 %. The results from inhibition-zone test and shake-flask test show that zinc alginate fibers have the most significant antifungal action and that copper alginate fibers have obvious inhibitory action, but the calcium alginate fibers have weak inhibitory effects. The scanning electron micrographs similarly illustrate that the fungal surfaces show most scraggly after the interaction between C. albicans and zinc alginate fibers. Moreover, the relative growth rates of zinc or calcium alginate fibers in human embryonic kidney cells and human fibroblast cells were more than 100 %. No significant results were obtained (P > 0.05). The calcium alginate fibers in human fibroblast cells were not much different from the negative control group (P > 0.05). However, zinc alginate fibers had a significant change (P < 0.05). Therefore, the excellent antifungal property of zinc alginate fibers demonstrates potential application in skin tissue engineering comparing with calcium or copper alginate fibers.

Sixty-one and forty-four compounds were identified from the volatile oils of the bast and fibers of Apocynum venetum by means of gas chromatography-mass spectrometry (GC-MS), respectively. The fatty acids, esters, ketones, aldehydes, alkanes, phenols, and miscellaneous compounds were found as the major components in both samples. Furthermore, both of volatile oils exhibited antibacterial properties against Staphylococcus aureus, Staphyloccus epidermidis, and Escherichia coli, whereas they showed weak inhibitory effects on Bacillus lentus and Candida albicans. These results confirmed the claim that A. venetum fibers have antibacterial properties and provide theoretical foundation to make better use of A. venetum fibers.

Rapid and accurate determination of chemical compositions of ramie is crucial to its application. In this paper, calibration models were established using near-infrared (NIR) spectroscopy to predict the main chemical compositions of ramie. A wet chemical analysis method which was improved on the basis of Chinese national standard for getting calibration data was used in this paper. NIR data of 59 ramie samples were collected using Fourier transform near-infrared spectrometer. The calibration models of chemical compositions of ramie were derived by partial least square (PLS) regression. Prediction of chemical composition of independent ramie samples showed that these models were rapid and accurate in the chemical composition analysis, giving residual predictive deviation (RPD) value higher than 2.5. Such NIR calibration models can be utilized by ramie fiber manufacturers and breeding workers, in order to better manage the degumming process and evaluate the quality of ramie varieties.

Apocynum venetum (AV) fibers were extracted by the combination of low (28 kHz) and high frequency (53 kHz) ultrasonic treatment after aqueous alkali maceration. The surface impurities and cementing components between fibers in the range of 10–50 µm were removed by low frequency ultrasound. The surface impurities in the range of 2–8 µm, as well as the residuals in the surface depression and inner cavum of fibers were further eliminated by high frequency ultrasonic irradiation. The treatment did not change crystal structure of cellulose I of AV fibers and could lead to a higher degree of crystallinity. Meanwhile, the examination of mechanical properties showed that the AV fibers could be used for textile industry. It is demonstrated that the combination of low and high frequency ultrasound after alkali treatment is simpler, more controllable and more environment-friendly and is a promising degumming method for textile industry.

Nelumbo nucifera (Nn.) fiber is the isolated secondary wall of the Nn. leafstalk Tracheary elements which has a unique shape. As the shape of the fiber may strongly affect the industrial uses especially for textile usage, the morphology and structure of Nn. fiber at different growth stages were investigated by several techniques in the present work. The Nn. fiber has spriral morphology with cellulose I structure. The diameter of mature fiber is about 4 μm and the cross-section shows elliptical or slightly oval shape without lumen. These findings aim to deeply understand the structure of Nn. fiber which is expected to be helpful to bring Nn. fiber into industrial use.