Comparison of Prokaryotic Communities Associated with Different TOC Concentrations in Dianchi Lake

Li, Chengpeng; Li, Yaping; Huo, Qing-Qing; Xiao, Wei; Duan, Changqun; Wang, Yongxia; Cui, Xiao‐Long

doi:10.3390/w12092557

“…When all 48 samples were considered, TOC was positively correlated with ttd. TOC was identi ed as an important factor in determining microbial growth, including the assimilable organic carbon (AOC) (Li et al 2020) and dissolved organic carbon (DOC) (Vila-Costa et al 2020), which are easy to be absorbed and utilized by microorganisms. It was established that AOC and DOC were both positively correlated with the persistence of EcO157 in sterile freshwater (Vital et al 2008).…”

Section: Seasonal Variation In Water Properties and Bacterial Communitymentioning

confidence: 99%

Persistence of E. coli O157:H7 in urban recreational waters from Spring and Autumn: a comparison analysis

Xie

¹

,

Zhu

²

,

Lyu

³

et al. 2022

Environ Sci Pollut Res

3

0

View full text Add to dashboard Cite

Persistence of E. coli O157: H7 (EcO157) in 48 water samples (24 Spring samples and 24 Autumn samples) from 3 urban recreational waters in Changchun City was investigated, and multivariate statistical analysis was performed to correlate survival data with water physicochemical properties and bacterial communities. Our data showed that EcO157 survived longer in Spring samples than in Autumn samples regardless of the lakes. Results revealed that recreational water physicochemical properties and bacterial community in Spring samples were different from those in Autumn samples. Mantel and Partial Mantel tests, as well as co-occurrence network analysis illustrated that EC salinity, TOC and bacterial community were correlated with survival time (ttd) (p < 0.05). Variation partition analysis (VPA) indicated that bacterial community, EC, TOC and TN explained about 64.81% of overall ttd variation in Spring samples, and bacterial community, EC, pH and TP accounted for about 56.59% of overall ttd variation in Autumn samples. Structural equation model (SEM) illustrated that EC indirectly positively affected ttd through bacterial community. The correlation between bacterial community and ttd was negative in Spring samples and positive in Autumn samples. TN appeared a direct positive effect on ttd in Spring samples. TP displayed a direct negative effect on ttd in Autumn samples. Our results concluded that there was seasonal variation in environmental factors that directly or indirectly affected the survival of EcO157 in urban recreational waters.

show abstract

Persistence of E. Coli O157:H7 in Urban Recreational Waters From Spring and Autumn: A Comparison Analysis

Xie¹,

Zhu²,

Lyu³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

Persistence of E. coli O157: H7 (EcO157) in 48 water samples (24 Spring samples and 24 Autumn samples) from 3 urban recreational waters in Changchun City was investigated, and multivariate statistical analysis was performed to correlate survival data with water physicochemical properties and bacterial communities. Our data showed that EcO157 survived longer in Spring samples than in Autumn samples regardless of the lakes. Results revealed that recreational water physicochemical properties and bacterial community in Spring samples were different from those in Autumn samples. Mantel and Partial Mantel tests, as well as co-occurrence network analysis illustrated that EC salinity, TOC and bacterial community were correlated with survival time (ttd) (p < 0.05). Variation partition analysis (VPA) indicated that bacterial community, EC, TOC and TN explained about 64.81% of overall ttd variation in Spring samples, and bacterial community, EC, pH and TP accounted for about 56.59% of overall ttd variation in Autumn samples. Structural equation model (SEM) illustrated that EC indirectly positively affected ttd through bacterial community. The correlation between bacterial community and ttd was negative in Spring samples and positive in Autumn samples. TN appeared a direct positive effect on ttd in Spring samples. TP displayed a direct negative effect on ttd in Autumn samples. Our results concluded that there was seasonal variation in environmental factors that directly or indirectly affected the survival of EcO157 in urban recreational waters.

show abstract

An ensemble deep neural network approach for predicting TOC concentration in lakes along the middle-lower reaches of Yangtze River

Guo

¹

,

Song

²

,

Tang

³

et al. 2022

IFS

1

0

View full text Add to dashboard Cite

In recent years, lakes pollution has become increasingly serious, so water quality monitoring is becoming increasingly important. The concentration of total organic carbon (TOC) in lakes is an important indicator for monitoring the emission of organic pollutants. Therefore, it is of great significance to determine the TOC concentration in lakes. In this paper, the water quality dataset of the middle and lower reaches of the Yangtze River is obtained, and then the temperature, transparency, pH value, dissolved oxygen, conductivity, chlorophyll and ammonia nitrogen content are taken as the impact factors, and the stacking of different epochs’ deep neural networks (SDE-DNN) model is constructed to predict the TOC concentration in water. Five deep neural networks and linear regression are integrated into a strong prediction model by the stacking ensemble method. The experimental results show the prediction performance, the Nash-Sutcliffe efficiency coefficient (NSE) is 0.5312, the mean absolute error (MAE) is 0.2108 mg/L, the symmetric mean absolute percentage error (SMAPE) is 43.92%, and the root mean squared error (RMSE) is 0.3064 mg/L. The model has good prediction performance for the TOC concentration in water. Compared with the common machine learning models, traditional ensemble learning models and existing TOC prediction methods, the prediction error of this model is lower, and it is more suitable for predicting the TOC concentration. The model can use a wireless sensor network to obtain water quality data, thus predicting the TOC concentration of lakes in real time, reducing the cost of manual testing, and improving the detection efficiency.

show abstract

Comparison of Prokaryotic Communities Associated with Different TOC Concentrations in Dianchi Lake

Cited by 3 publications

References 37 publications

Persistence of E. coli O157:H7 in urban recreational waters from Spring and Autumn: a comparison analysis

Persistence of E. coli O157:H7 in urban recreational waters from Spring and Autumn: a comparison analysis

Persistence of E. Coli O157:H7 in Urban Recreational Waters From Spring and Autumn: A Comparison Analysis

An ensemble deep neural network approach for predicting TOC concentration in lakes along the middle-lower reaches of Yangtze River

Contact Info

Product

Resources

About