Ultraviolet spectrophotometric determination of nitrate: detecting nitrification rates and inhibition

Colorimetric Detection of Metals Using CdS-NPs Synthesized by an Organic Extract of Aspergillus niger

The use of cadmium sulfide nanoparticles (CdS-NPs) synthesized by fungi presents highly stable chemical and optical characteristics; this makes them a promising alternative for development of colorimetric methods for metal detection. Moreover, application of CdS-NPs is challenging due to the biological material used to carry out synthesis and coating is highly diverse; therefore, it is necessary to evaluate if such components are present in the biological material. Thus, the objective of this work was to detect metallic ions in synthetic water samples using CdS-NPs synthesized by the extract of Aspergillus niger. The conditions to produce fungal extracts were determined through a factorial design 2³; additionally, biomolecules involved in metallic ions detection, synthesis, and coating of CdS-NPs were quantified; the studied biomolecules are NADH, sulfhydryl groups, proteins, and ferric reducing antioxidants (FRAP). CdS-NPs synthesized in this study were characterized by spectrophotometry, zeta potential, and high-resolution transmission electron microscopy (HRTEM). Finally, detection capacity of metallic ions in synthetic water samples was evaluated. It was proved that the methanolic extract of Aspergillus niger obtained under established conditions has the necessary components for both synthesis and coating of CdS-NPs, as well as detection of metallic ions because it was possible to synthesize CdS-NPs with a hexagonal crystalline structure with a length of 2.56 ± 0.50 nm which were able to detect Pb²⁺, Cr⁶⁺, and Fe³⁺ at pH 4 and Co²⁺ at pH 8.

In-situ monitoring of nitrate in industrial wastewater using Fourier transform infrared attenuated total reflectance spectroscopy (FTIR-ATR) coupled with chemometrics methods

Quantitative prediction of nitrate contents in different industrial wastewater was carried out using Fourier transform infrared attenuated total reflectance (FTIR-ATR) spectroscopy. The algorithm of Gaussian deconvolution was applied in the spectral range of 1500-1200 cm^-1 to eliminate the background interferences on target information of nitrate, and partial least squares regression (PLSR) model and support vector machine (SVR) model were developed for the prediction of nitrate. The results showed that the PLSR model (Rv ² = 0.921, RMSEv = 0.351 mg/L, RPDv = 3.56) and SVR model (Rv ² = 0.856, RMSEv = 0.473 mg/L, RPDv = 3.15) reached excellent prediction accuracy and robustness for electroplating wastewater, and for metallurgical wastewater the SVR model (Rv ² = 0.916, RMSEv = 1.38 mg/L, RPDv = 3.26) showed a better prediction performance. The PLSR and SVR models exhibited poor prediction accuracy of nitrate for pesticide wastewater and dyeing wastewater due to the strongly interference by carbonate. The spectra pretreatment by deconvolution dramatically improved the prediction models. Therefore, combined with deconvolution spectra pretreatment and chemometrics methods, FTIR-ATR could achieve a fast and effective in-situ monitoring of nitrate in industrial wastewater.

Diversity and spatiotemporal dynamics of fungal communities in the rhizosphere soil of Lycium barbarum L.: a new insight into the mechanism of geoherb formation

Lycium barbarum L. is a well-known traditional geoherb in Ningxia, China. The fruits of L. barbarum contain several dietary constituents, and thus, they exert many beneficial effects on human health. However, a few studies have been conducted on the geoherb L. barbarum and its rhizosphere soil fungal community. In this study, we determined the physicochemical properties and fungal community structure of rhizosphere soil of L. barbarum from three regions of China, namely Ningxia (NX), Qinghai (QH), and Xinjiang (XJ), during three development stages of L. barbarum. Soil pH varied between 7.56 and 8.60 across the three regions, indicating that alkaline soil is conducive to the growth of L. barbarum. The majority of soil properties in NX, an authentic geoherb-producing area, were substantially inferior to those in XJ and QH during all three developmental stages. Total sugar, polysaccharide (LBP), and flavonoid contents were the highest in wolfberry fruits from NX. High-throughput sequencing showed that the abundance of the soil fungal population in NX was higher than that in QH and XJ during the flowering and fruiting stage and summer dormant stage. Moreover, the soil fungal diversity increased with the development of wolfberry. Ascomycota and Mortierellomycota were the predominant phyla in the rhizosphere fungal communities in all samples. Redundancy analysis showed a significant correlation of the soil-available phosphorus and LBP of wolfberry fruits with the fungal community composition. The characteristics of rhizosphere fungal communities determined in the present study provide insights into the mechanism of geoherb formation in NX wolfberry.