000K utf8 1100 $c2023 1500 eng 2050 urn:nbn:de:gbv:8:3-2025-00383-8 2051 10.3390/su151411049 3000 Manzoor, Maria 3010 Arshad, Muhammad 3010 Gul, Iram 3010 Gulshan, Sumaira 3010 Kamboh, Usman Rauf 3010 Siddiqui, Alighazi 3010 Tomforde, Sven 4000 Optimizing Sustainable Phytoextraction of Lead from Contaminated Soil Using Response Surface Methodology (RSM) and Artificial Neural Network (ANN)$hMDPI AG [Manzoor, Maria] 4030 $nMDPI AG 4209 Lead (Pb) is well known for the containment of soil surfaces. In the last few decades, phytoremediation has been the most ideal technology to extract Pb from soil, involving numerous chemical reactions and cost analysis. The aim of this study is to model and to optimize Pb extraction from the contaminated soil via Pelargonium hortorum by comparing two modeling approaches: response surface methodology (RSM) and artificial neural networks (ANNs) with the genetic algorithm (GA). To determine the significance of the proposed solution, in vitro essays were performed to check the Pb tolerance of bacterial strains (NCCP 1844, 1848, 1857, and 1862), followed by the co-application of bacteria and citric acid on a Pb hyperaccumulator (Pelargonium hortorum L.) on Murashige and Skoog (MS) agar medium. Afterwards, a pot culture experiment was performed to optimize Pb extraction competency from Pb-spiked (0 mg kg−1, 500 mg kg−1, 1000 mg kg−1, and 1500 mg kg−1) soil by Pelargonium hortorum L., to which citric acid (5 and 10 mmol L−1) and Microbacterium paraoxydance (1 and 1.5 OD) were applied. Plants were harvested at 30, 60, and 90 day intervals, and they were analyzed for dry biomass and Pb uptake characteristics. The maximum Pb extraction efficiency of 86.0% was achieved with 500 mg kg−1 soil Pb for 60 days. Furthermore, RSM, based on the Box–Behnken design (BBD) and the ANN-based Levenberg–Marquardt Algorithm (LMA), were applied to model Pb extraction from the soil. The significance of the predicted values from RSM and LMA were close to 36.0% and 86.05%, respectively, compared to the laboratory values. [...]. Therefore, experimental results showed that ANN is an accurate technique to optimize an integrated phytoremediation system for sustainable Pb removal, besides being environmentally friendly and potentially cost-effective. 4950 https://doi.org/10.3390/su151411049$xR$3Volltext$534 4950 https://nbn-resolving.org/urn:nbn:de:gbv:8:3-2025-00383-8$xR$3Volltext$534 4961 https://macau.uni-kiel.de/receive/macau_mods_00005915 5051 500 5550 ANN 5550 bacteria 5550 citric acid 5550 RSM 5550 soil contamination