Solid-state fermentation of Apocynum venetum L. by Aspergillus niger: Effect on phenolic compounds, antioxidant activities and metabolic syndrome-associated enzymes

This study aimed to evaluate the effect of solid-state fermentation (SSF) with Aspergillus niger on the total phenolic content (TPC), the total flavonoid content (TFC), individual phenolic contents, and antioxidant and inhibitory activities against metabolic syndrome-associated enzymes in an ethanol extract from Apocynum venetum L. (AVL). TPC, TFC, and the contents of quercetin and kaempferol during SSF were 1.52-, 1.33-, 3.64-, and 2.22-fold higher than those of native AVL in the ethyl acetate (EA) subfraction of the ethanol extract. The ABTS·+, DPPH· scavenging, and inhibitory activities against α-glucosidase and pancreatic lipase were found to be highest in the EA subfraction. Fermentation significantly increased the ABTS radical cation, DPPH radical scavenging, and pancreatic lipase inhibitory activities by 1.33, 1.39, and 1.28 times, respectively. TPC showed a significantly positive correlation with antioxidant activities or inhibition against metabolic syndrome-associated enzymes. This study provides a theoretical basis for producing tea products with enhanced antioxidant, antidiabetic, and antihyperlipidemic activities

Exploring the Potential of Unmanned Aerial Vehicle (UAV) Remote Sensing for Mapping Plucking Area of Tea Plantations

Mapping plucking areas of tea plantations is essential for tea plantation management and production estimation. However, on-ground survey methods are time-consuming and labor-intensive, and satellite-based remotely sensed data are not fine enough for plucking area mapping that is 0.5–1.5 m in width. Unmanned aerial vehicles (UAV) remote sensing can provide an alternative. This paper explores the potential of using UAV-derived remotely sensed data for identifying plucking areas of tea plantations. In particular, four classification models were built based on different UAV data (optical imagery, digital aerial photogrammetry, and lidar data). The results indicated that the integration of optical imagery and lidar data produced the highest overall accuracy using the random forest algorithm (94.39%), while the digital aerial photogrammetry data could be an alternative to lidar point clouds with only a ~3% accuracy loss. The plucking area of tea plantations in the Huashan Tea Garden was accurately measured for the first time with a total area of 6.41 ha, which accounts for 57.47% of the tea garden land. The most important features required for tea plantation mapping were the canopy height, variances of heights, blue band, and red band. Furthermore, a cost–benefit analysis was conducted. The novelty of this study is that it is the first specific exploration of UAV remote sensing in mapping plucking areas of tea plantations, demonstrating it to be an accurate and cost-effective method, and hence represents an advance in remote sensing of tea plantations

Additional file 1 of Improving saccharification of ramie stalks by synergistic effect of in-house cellulolytic enzymes consortium

Additional file 1: Figure S1. Effect of different carbon sources on enzyme production by cultivating T. reesei. Figure S2. Effect of different carbon sources on enzyme production by cultivating T. harzianum. Figure S3. Effect of different carbon sources on enzyme production by cultivating A. niger. Figure S4. Effect of different nitrogen sources on enzyme production by cultivating T. reesei. Figure S5. Effect of different nitrogen sources on enzyme production by cultivating T. harzianum. Figure S6. Effect of different nitrogen sources on enzyme production by cultivating A. niger