The aim of this study was to investigate the effects of light quality on the morphological traits, leaf anatomical characteristics, antioxidant enzyme (superoxide dismutase, catalase, and peroxidase) activities, photosynthetic pigments content, and bioactive compounds (phenols, flavonoids, and polysaccharides) content in Anoectochilus roxburghii. Plants of A. roxburghii were grown under light filtered through four differently colored films for 8 months. The four treatments were red film (RF), blue film (BF), yellow film (YF), and colorless plastic film (control, CK). Compared with the A. roxburghii plants in CK, those in the BF treatment showed significantly greater stem diameter, fresh weight, leaf area, stomatal frequency, chlorophyll content (Chl a, Chl b, Chl a+b), antioxidant enzyme activities, and active compound (polysaccharides, flavones) content. The plants in the RF treatment showed the greatest plant height and phenolics contents. These results show that growing A. roxburghii plants under blue film is a useful technique to improve quality. This technique is conducive to achieving large-scale sustainable production of high-quality plant materials.
This study used MAE and RSM to extract phenolic compounds from Anoectochilus roxburghii, and the optimum conditions defined by the model to give an optimum yield of 1.31%. The antioxidant activity in vitro showed when the concentration of phenolic compounds was reached 1 mg mL-1, the clearance rates were 82.58% for DPPH and 97.62% for ABTS+. In vivo antioxidant experiments used D-galactose to build oxidative damage in healthy Kunming mice. The result showed that the extractions of A. roxburghii can improve the antioxidant ability and the medium and low dose groups had better ability to scavenge free radicals. The UPLC-Q-TOF-MS/MS was developed to identify 21 kinds of phenolic compounds by molecular mass, ms/ms fragmentation, as well as retention time. The result showed that the phenolic compounds of A. roxburghii had significant potential as a natural antioxidant to promote health and to reduce the risk of disease.
The cyclic void growth model (CVGM) is a micro-mechanical fracture model that has been used to assess ultra-low cycle fatigue (ULCF) of steel structures in recent years. However, owing to the stress triaxiality range and contingency of experimental results, low goodness of fit is sometimes obtained when calibrating the model damage degradation parameter, resulting in poor prediction. In order to improve the prediction accuracy of the CVGM model, a model parameter calibration method is proposed. In the research presented in this paper, tests were conducted on circular notched specimens that provided different magnitudes of stress triaxiality. The comparative analysis was carried out between experimental results and predicted results. The results indicate that the number of cycles and the equivalent plastic strain to ULCF fracture initiation by the CVGM model calibrated by the proposed method agree well with the experimental results. The proposed parameter calibration method greatly improves prediction accuracy compared to the previous method.
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