Estimating the Heavy Metal Contents in Entisols from a Mining Area Based on Improved Spectral Indices and Catboost.

In the study of the inversion of soil multi-species heavy metal element concentrations using hyperspectral techniques, the selection of feature bands is very important. However, interactions among soil elements can lead to redundancy and instability of spectral features. In this study, heavy metal elements (Pb, Zn, Mn, and As) in entisols around a mining area in Harbin, Heilongjiang Province, China, were studied. To optimise the combination of spectral indices and their weights, radar plots of characteristic-band Pearson coefficients (RCBP) were used to screen three-band spectral index combinations of Pb, Zn, Mn, and As elements, while the Catboost algorithm was used to invert the concentrations of each element. The correlations of Fe with the four heavy metals were analysed from both concentration and characteristic band perspectives, while the effect of spectral inversion was further evaluated via spatial analysis. It was found that the regression model for the inversion of the Zn elemental concentration based on the optimised spectral index combinations had the best fit, with R2 = 0.8786 for the test set, followed by Mn (R2 = 0.8576), As (R2 = 0.7916), and Pb (R2 = 0.6022). As far as the characteristic bands are concerned, the best correlations of Fe with the Pb, Zn, Mn and As elements were 0.837, 0.711, 0.542 and 0.303, respectively. The spatial distribution and correlation of the spectral inversion concentrations of the As and Mn elements with the measured concentrations were consistent, and there were some differences in the results for Zn and Pb. Therefore, hyperspectral techniques and analysis of Fe elements have potential applications in the inversion of entisols heavy metal concentrations and can improve the quality monitoring efficiency of these soils.

High-yield production of ß-arbutin by identifying and eliminating byproducts formation.

ß-Arbutin is a plant-derived glycoside and widely used in cosmetic and pharmaceutical industries because of its safe and effective skin-lightening property as well as anti-oxidant, anti-microbial, and anti-inflammatory activities. In recent years, microbial fermentation has become a highly promising method for the production of ß-arbutin. However, this method suffers from low titer and low yield, which has become the bottleneck for its widely industrial application. In this study, we used ß-arbutin to demonstrate methods for improving yields for industrial-scale production in Escherichia coli. First, the supply of precursors phosphoenolpyruvate and uridine diphosphate glucose was improved, leading to a 4.6-fold increase in ß-arbutin production in shaking flasks. The engineered strain produced 36.12 g/L ß-arbutin with a yield of 0.11 g/g glucose in a 3-L bioreactor. Next, based on the substrate and product's structural similarity, an endogenous O-acetyltransferase was identified as responsible for 6-O-acetylarbutin formation for the first time. Eliminating the formation of byproducts, including 6-O-acetylarbutin, tyrosine, and acetate, resulted in an engineered strain producing 43.79 g/L ß-arbutin with a yield of 0.22 g/g glucose in fed-batch fermentation. Thus, the yield increased twofold by eliminating byproducts formation. To the best of our knowledge, this is the highest titer and yield of ß-arbutin ever reported, paving the way for the industrial production of ß-arbutin. This study demonstrated a systematic strategy to alleviate undesirable byproduct accumulation and improve the titer and yield of target products. KEY POINTS: • A systematic strategy to improve titer and yield was showed • Genes responsible for 6-O-acetylarbutin formation were firstly identified • 43.79 g/L ß-arbutin was produced in bioreactor, which is the highest titer so far.

Establishing a growth-coupled mechanism for high-yield production of ß-arbutin from glycerol in Escherichia coli.

Biodiesel production has increased significantly in recent years, leading to an increase in the production of crude glycerol. In this study, a novel growth-coupled erythrose 4-phosphate (E4P) formation strategy that can be used to produce high levels of ß-arbutin using engineered Escherichia coli and glycerol as the carbon source was developed. In the strategy, E4P formation was coupled with cell growth, and a growth-driving force made the E4P formation efficient. By applying this strategy, efficient microbial synthesis of ß-arbutin was achieved, with 7.91 g/L ß-arbutin produced in shaking flask, and 28.1 g/L produced in a fed batch fermentation with a yield of 0.20 g/g glycerol and a productivity of 0.39 g/L/h. This is the highest ß-arbutin production through microbial fermentation ever reported to date. This study may have significant implications in the large-scale production of ß-arbutin as well as other aromatic compounds of importance.

Quantitative Analysis of Iron and Silicon Concentrations in Iron Ore Concentrate Using Portable X-ray Fluorescence (XRF).

As a technique capable of rapid, nondestructive, and multi-elemental analysis, portable X-ray fluorescence (pXRF) has applications to mineral exploration, environmental evaluation, and archaeological analysis. However, few applications have been conducted in the smelting industry especially when analyzing the metal concentration in ore concentrate samples. This research analyzed the effectiveness of using pXRF in determining the metal concentration in Fe concentrate. For this proof of concept study, Fe ore samples dominated by Fe and Si were collected from the Northeastern University Mineral Processing Laboratory (Shenyang, China) and directly analyzed using pXRF, laboratory-based XRF, and titration methods. The compactness (density) of the ore concentrate was found to have very little effect on pXRF readings. The pXRF readings for Fe and Si were comparative to laboratory-based XRF results. Based on the strong correlations between the pXRF and XRF results (Fe: R2 > 0.99, Si: R2 > 0.96), linear calibrations were adopted to improve the accuracy of pXRF readings. Linear regression equations derived from the relations between XRF results and pXRF results of 21 Fe ore concentrate samples were used to calibrate the pXRF, and then validation was performed on five additional samples. Results from this preliminary study suggest that ordinary least squares (OLS) regression improves the accuracy dramatically, especially for Fe with relative errors (REs) decreasing to 0.03%-3.27% from 4.26%-8.32%. Consequently, pXRF shows strong promise for rapid, quantitative analysis of Fe concentration in Fe ore concentrate. Based on the results obtained in this study, a larger, more comprehensive study is warranted to confirm the results obtained.

Rapid in situ determination of heavy metal concentrations in polluted water via portable XRF: Using Cu and Pb as example.

In this research, the effectiveness of using portable X-ray fluorescence (pXRF), with the help of waterproof film, to determine the concentration of the heavy metals Cu and Pb in polluted water was assessed through indoor and field studies. The effects of the thickness of the film and the distance between the instrument and sample were also evaluated. The penetration depth of X-rays in water was found to be between 2 mm and 4 mm, and a water sample of at least 4 mm in depth was thus suggested. The minimum detectable concentration for Cu was ca. 21 ppm and ca. 28 ppm for Pb. Based on the indoor study, the pXRF results were found to be comparable with the certified concentrations of prepared solutions (R2 > 0.99 for both Cu and Pb). The field pXRF readings also showed a good linear correlation with the corresponding laboratory results (R2 > 0.95 for Cu). The calibration formula derived from indoor analysis was used to correct the field pXRF results and effectively improved the accuracy. Consequently, pXRF has the potential to be applied to the analysis of polluted waters with relatively high concentrations (e.g., >20-30 ppm Cu), which would benefit the in situ monitoring of water pollution caused by heavy metals.