The definitive screening design (DSD) and artificial neural network (ANN) were conducted for modeling the biosorption of Co(II) by Pseudomonas alcaliphila NEWG-2. Factors such as peptone, incubation time, pH, glycerol, glucose, K2HPO4, and initial cobalt had a significant effect on the biosorption process. MgSO4 was the only insignificant factor. The DSD model was invalid and could not forecast the prediction of Co(II) removal, owing to the significant lack-of-fit (P < 0.0001). Decisively, the prediction ability of ANN was accurate with a prominent response for training (R2 = 0.9779) and validation (R2 = 0.9773) and lower errors. Applying the optimal levels of the tested variables obtained by the ANN model led to 96.32 ± 2.1% of cobalt bioremoval. During the biosorption process, Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy, and scanning electron microscopy confirmed the sorption of Co(II) ions by P. alcaliphila. FTIR indicated the appearance of a new stretching vibration band formed with Co(II) ions at wavenumbers of 562, 530, and 531 cm–1. The symmetric amino (NH2) binding was also formed due to Co(II) sorption. Interestingly, throughout the revision of publications so far, no attempt has been conducted to optimize the biosorption of Co(II) by P. alcaliphila via DSD or ANN paradigm.

The current study reported a new keratinolytic bacterium, which was characterized as Bacillus paramycoides and identified by 16S rRNA, and the sequence was then deposited in the GenBank (MW876249). The bacterium was able to degrade the insoluble chicken feather keratin (CFK) into amino acids (AA) through the keratinase system. The statistical optimization of the biodegradation process into AA was performed based on the Plackett–Burman design and rotatable central composite design (RCCD) on a simple solid-state fermentation medium. The optimum conditions were temperature, 37°C, 0.547 mg KH2PO4, 1.438 mg NH4Cl, and 11.61 days of incubation. Innovatively, the degradation of the CFK process was modeled using the artificial neural network (ANN), which was better than RCCD in modeling the biodegradation process. Differentiation of the AA by high-performance liquid chromatography (HPLC) revealed the presence of 14 AA including essential and non-essential ones; proline and aspartic acids were the most dominant. The toxicity test of AA on the HepG2 cell line did not show any negative effect either on the cell line or on the morphological alteration. B. paramycoides ZW-5 is a new eco-friendly tool for CFK degradation that could be optimized by ANN. However, additional nutritional trials are encouraged on animal models.

Plant residuals comprise the natural habitat of the plant pathogen; therefore, attention is currently focusing on biological-based bioprocessing of biomass residuals into benefit substances. The current study focused on the biodegradation of peanut plant residual (PNR) into citric acid (CA) through a mathematical modeling strategy. Novel endophytic Trichoderma longibrachiatum WKA55 (GenBank accession number: MZ014020.1), having lytic (cellulase, protease, and polygalacturonase) activity, and tricalcium phosphate (TCP) solubilization ability were isolated from peanut seeds and used during the fermentation process. As reported by HPLC, the maximum CA (5505.1 μg/g PNR) was obtained after 9 days in the presence of 15.49 mg TCP, and 15.68 mg glucose. GC–MS analysis showed other bioactive metabolites in the filtrate of the fermented PNR. Practically, the crude product (40%) fully inhibited (100%) the growth and spore germination of three mycotoxinogenic fungi. On peanuts, it improved the seed germination (91%), seedling features, and vigor index (70.45%) with a reduction of abnormal seedlings (9.33%). The current study presents the fundamentals for large-scale production in the industry for the sustainable development of PNR biomass as a natural source of bioactive metabolites, and safe consumption of lignocellulosic-proteinaceous biomass, as well. T. longibrachiatum WKA55 was also introduced as a novel CA producer specified on PNR. Application of the resulting metabolite is encouraged on a large scale.

The present investigation has been designed by Taguchi and hybrid artificial neural network (ANN) paradigms to improve and optimize the binary sorption of Cobalt(II) and methylene blue (MB) from an aqueous solution, depending on modifying physicochemical conditions to generate an appropriate constitution for a highly efficient biosorption by the alga; Sargassum latifolium. Concerning Taguchi's design, the predicted values of the two responses were comparable to actual ones. The biosorption of Cobalt(II) ions was more efficient than MB, the supreme biosorption of Cobalt(II) was verified in run L21 (93.28%), with the highest S/N ratio being 39.40. The highest biosorption of MB was reached in run L22 (74.04%), with a S/N ratio of 37.39. The R2 and adjusted R2 were in reasonable values, indicating the validity of the model. The hybrid ANN model has exclusively emerged herein to optimize the biosorption of both Cobalt(II) and MB simultaneously, therefore, the ANN model was better than the Taguchi design. The predicted values of Cobalt(II) and MB biosorption were more obedience to the ANN model. The SEM analysis of the surface of S. latifolium showed mosaic form with massive particles, as crosslinking of biomolecules of the algal surface in the presence of Cobalt(II) and MB. Viewing FTIR analysis showed active groups e.g., hydroxyl, α, β-unsaturated ester, α, β-unsaturated ketone, N–O, and aromatic amine. To the best of our knowledge, there are no reports deeming the binary sorption of Cobalt(II) and MB ions by S. latifolium during Taguchi orthogonal arrays and hybrid ANN.

This study aims at the investigation of using magnetic water (MW) to manage brown rot (bacterial wilt) disease of potato. The effect of magnetic field (MF) on the viability of Ralstonia solanacearum (the bacterial causal pathogen of this disease) was investigated by passing the suspension of R. solanacearum through a magnetic liquid modifier tube. The viable count of the bacterial pathogen increased with the increasing of the incubation time (1, 2, 3 and 4 h) as well as with increasing the number of passes through the magnetic tube. In the pots experiment (carried out at Tag El-Ezz Agricultural Research Station, Dakahlia Governorate, Egypt-during the period of 17 February to 12 May 2016), the irrigation with MW led to significant increases in total phenols, polyphenol oxidase, peroxidase, total chlorophylls, chlorophyll a chlorophyll b, and carotenoids. Significant increase in plant height after 50 and 70 days of planting and decrease in disease rating were noticed. The viable count of R. solanacearum in rhizosphere of the plant irrigated with MW was significantly decreased after 70 and 108 days of planting when compared with the plants irrigated with tap water (TW). The irrigation with MW led to significant increase in potato yield (25.64 %) and a significant decrease in the percentage of infected tubers (40.22 %) in comparing with the plants irrigated with TW. These studies encourage more studies for the use of MW to manage brown rot disease of potato as well as other plant diseases.