[1] Mesoscale meteorological modeling is an important tool to help understand the energy budget of the oasis, while some of its initial field data are rough limited to describe the atmosphere and land conditions over a small oasis. Local factors including land surface parameters and their interaction with the atmosphere play a dominant role in the local circulation. Therefore, in this study, land surface parameters such as land-use types, vegetation cover fraction, and surface layer soil moisture are derived by satellite remote sensing data from EOS Moderate Resolution Imaging Spectroradiometer (EOS/MODIS), and soil moisture at 10 cm and 200 cm depth are obtained by combining surface layer soil moisture with experiential statistics. Then the parameters are used to specify the respective options in the MM5 model. Comparison with the observations shows that the modeling including satellite values leads to improved meteorological simulations in the Jinta oasis, both for the oasis effect and the local wind circulation, especially for description of the inhomogeneous characteristics over the oasis. Replacing values in the initial field with data obtained from remote sensing removes the number of unknowns in the model and increases the accuracy of the energy budget. This work is a very valuable addition to current numerical research on local circumfluence over the oasis areas.
Using global terrestrial ecosystem observation and proxy data for net primary productivity (NPP), leaf area index (LAI), and climate data, we compared simulated NPP, LAI, and major climatic factors and explored the relationship between their variations in historical scenarios of ten Coupled Model Intercomparison Project (CMIP5) models. The results showed that global spatial patterns of the simulated terrestrial ecosystem and climate are consistent with proxy data, but the values have some differences for each model. Based on statistical analysis, the simulated climatic factors were found to be better than terrestrial ecosystem NPP and LAI, and the multi-model ensemble (MME) results were better than every single model. For the terrestrial ecosystem, air temperature (Ta) was found to be the major affecting factor, followed by precipitation, meaning the terrestrial ecosystem NPP and LAI are more related to Ta than precipitation. Meanwhile, surface downwelling shortwave radiation (Rsds) was found to inhibit the terrestrial ecosystem in almost all regions of the world. Between 1976 and 2005, precipitation had a slight increasing trend, Ta an obvious increasing trend, and Rsds a slight decreasing trend. The changes of precipitation, air temperature, and Rsds were favorable for the terrestrial ecosystem and for plant growth. Therefore, LAI and NPP showed an obvious increasing temporal trend, and the terrestrial ecosystem showed a positive response to climate change. All the model results showed NPP had an increasing temporal trend in the past 150 years, which also indicated that the terrestrial ecosystem has shown a positive
Using global terrestrial ecosystem net primary productivity (NPP) data, we validated the simulated multi-model ensemble (MME) NPP, analyzed the spatial distribution of global NPP and explored the relationship between NPP and climate variations in historical scenarios of 10 CMIP5 models. The results show that the global spatial pattern of simulated terrestrial ecosystem NPP, is consistent with IGBP NPP, but the values have some differences and there is a huge uncertainty. Considering global climate change, near surface temperature is the major factor affecting the terrestrial ecosystem, followed by the precipitation. This means terrestrial ecosystem NPP is more closely related to near surface temperature than precipitation. Between 1976 and 2005, NPP shows an obvious increasing temporal trend, indicating the terrestrial ecosystem has had a positive response to climate change. MME NPP has increased 3.647PgC during historical period, which shows an increasing temporal trend of 3.9 gCm −2 •100 yr −2 in the past 150 years, also indicating that the terrestrial ecosystem has shown a positive response to climate change in past 150 years.
Purpose
Gardenia blue is one of the natural food additives used in East Asia for many years. Its biosynthesis relies on a key rate-limiting cellulase: β-glucosidase (BGL), which mainly exists in Aspergillus niger (A. niger) cells. The purpose of this study was to obtain active β-glucosidase by cell engineering method and applied to gardenia blue synthesis, which would help to promote the application and reduce the cost of β-glucosidase and gardenia blue.
Methods
A. niger was identified based on 18S rRNA gene sequencing. β-Glucosidase gene was cloned and expressed based on PCR and prokaryotic expression. The enzyme activity of β-glucosidase was measured based on p-nitrophenyl-β-D-glucopyranoside method.
Results
An A. niger isolate (AS3.4523) was identified from soil. The β-glucosidase gene of AS3.4523 was cloned and sequenced, which encoded a new type of β-glucosidase mutant containing two specific amino acid substitutions (Asp154Gly and Ser163Pro). Prokaryotic expression of wild-type β-glucosidase in Escherichia coli BL21 showed low cellulase activity (0.29 ± 0.13 U/mL). However, after removing its signal peptide, the β-glucosidase of A. niger AS3.4523 exhibited extremely higher activity (25.88 ± 0.45 U/mL) compared with wild type β-glucosidase (12.59 ± 1.07 U/mL) or other A. niger strains M85 (3.61 ± 0.24 U/mL) and CICC2041 (4.36 ± 0.76 U/mL). Furthermore, recombinant β-glucosidase was applied to geniposide hydrolysis, and gardenia blue pigment was successfully synthesized with the reaction of genipin and Lys.
Conclusions
This work has discovered a new type of highly active β-glucosidase and provided a theoretical basis for large-scale producing β-glucosidase, which lays a brand-new foundation for gardenia blue preparation with high efficiency and low cost.
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