Optimization of adsorption performance of cerium-loaded intercalated bentonite by CCD-RSM and GA-BPNN and its application in simultaneous removal of phosphorus and ammonia nitrogen.

Excessive phosphorus (P) and ammonia nitrogen (NH3-N) in water bodies can lead to eutrophication of the aquatic environment. Therefore, it is important to develop a technology that can efficiently remove P and NH3-N from water. Here, the adsorption performance of cerium-loaded intercalated bentonite (Ce-bentonite) was optimized based on single-factor experiments using central composite design-response surface methodology (CCD-RSM) and genetic algorithm-back propagation neural network (GA-BPNN) models. Based on the determination coefficient (R2), mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE), and root mean square error (RMSE), the GA-BPNN model was found to be more accurate in predicting adsorption conditions than the CCD-RSM model. The validation results showed that the removal efficiency of P and NH3-N by Ce-bentonite under optimal adsorption conditions (adsorbent dosage = 1.0 g, adsorption time = 60 min, pH = 8, initial concentration = 30 mg/L) reached 95.70% and 65.93%. Furthermore, based on the application of these optimal conditions in simultaneous removal of P and NH3-N by Ce-bentonite, pseudo-second order and Freundlich models were able to better analyze adsorption kinetics and isotherms. It is concluded that the optimization of experimental conditions by GA-BPNN has some guidance and provides a new approach to explore adsorption performance after optimizing the conditions.

[Rapid screening and identification of 62 kinds of illegally added traditional Chinese medicine in food by high performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry].

An analytical method based on high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF/MS) was established for the rapid screening and identification of 62 kinds of illegally added traditional Chinese medicine (TCM) in food. According to the notice of the Ministry of Health of the People's Republic of China on further regulating the management of raw materials of health food (Weifa Jianfa (2002) No. 51), the characteristic components of the 62 kinds of TCM were screened, and the corresponding characteristic component lists of different TCM were obtained. Methanolic extracts of the 62 kinds of standard medicinal materials were subjected to HPLC-Q-TOF-MS analysis. The filtrate was separated on a Thermo Accucore aQ column (150 mm×2.1 mm, 2.6 µm) using 0.1%(v/v) formic acid aqueous solution or water and acetonitrile as the mobile phases for gradient elution in the electrospray positive and negative ion scanning mode. All the data were determined on the full scan of primary mass spectrometry and secondary mass spectrometry, with mass acquisition ranges of 100-1000 Da and 50-1000 Da, respectively. A 10 mmol/L sodium formate solution was used as the mass correction solution in both the positive and negative ion modes. Library View software was used to establish the precursor ion accurate quality database and the product ion fragment mass spectrometry database of the corresponding characteristic components of the different kinds of TCM. In the Library View database software, the name of each characteristic component of the 62 kinds of TCM was input (serial number) in order to classify the screened characteristic components. The samples were processed using the same method and analyzed. Peak View software was used to rapidly analyze and screen the target components of the TCM. The high-resolution data collected from the samples to be tested were imported into the Peak View software, followed by the compound list of the established MS database of standard medicinal materials. After setting the identification method parameters and library retrieval parameters, a matching analysis was performed, and the candidate substances for each peak were automatically identified by comparing the mass spectrum, accurate molecular ion mass number, fragment ion mass number, retention time, and other related parameters. The determination conditions of compound detection were as follows: the comprehensive score was more than 70 points. The molecular formula, retention time, mass spectrum as well as the primary isotope mass spectrometry, primary mass spectrometry, and secondary mass spectrometry data were matched with the library compounds. The corresponding list of "TCM-characteristic components" was established, and a high-resolution MS library of 388 characteristic components from the 62 types of TCM was constructed. Each TCM contains 5-10 characteristic components. According to the screening analysis of the actual food samples of the prepared wine, substitute tea, and beverage, one batch of the prepared wine sample matched with seven characteristic components of epimedium, and it was inferred that epimedium was added to the prepared wine samples. This method can allow for the qualitative screening of TCM without standards and has the characteristics of high throughput, accuracy, simplicity, and rapidity. It solves the difficulty in identifying and confirming illegally added TCM in food; provides technical methods and a basis for cracking down on the illegal addition of TCM in food; and facilitates the rapid screening and identification of illegally added TCM in food.