English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Most of the dyes are toxic and non-biodegradable in textile industry wastewaters. Therefore, removal of textile dye using agriculture waste becomes crucial for the environment. This can be accomplished by the biosorption process which is the passive uptake of pollutants by agricultural waste. In this study, Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to obtain optimum conditions for Methylene Blue (MB) removal using sugarcane bagasse and peanut hulls as low-cost agricultural waste. The experimental design was carried out to study the effect of temperature, pH, biosorbent amount and dye concentration. The maximum MB dye removal considering the effect of total dissolved solids from aqueous solutions of 74.49% and 67.99% by sugarcane bagasse and peanut hulls, respectively. The models specify that they could predict biosorption with high accuracy having  R2 -value above 0.9. Statistical studies for RSM, ANFIS and ANN models were compared. Further, the models were optimized for maximum dye removal was at 1.21 g of biosorbent, pH 5.24, 31.24 mg/L MB concentration, 22.29°C of dye solution using sugarcane bagasse and at 1.37 g of biosorbent, pH 5.77, 36.7 mg/L MB concentration, 26.8°C of dye solution using peanut hulls. Additionally, Fourier Transform Infra-Red (FTIR) spectral analysis was also carried out to confirm the biosorption.

Use of artificial intelligence for optimizing biosorption of textile wastewater using agricultural waste