Artificial Intelligence-Powered Optimization and Milk Permeate Upcycling for Innovative Sesame Milk with Enhanced Probiotic Viability and Sensory Appeal.

Consumer demand for plant-based alternatives drives innovation in nondairy beverages. This study explores the development of a novel sesame milk with enhanced functionality using an artificial neural network (ANN) and milk permeate integration. An ANN model effectively optimized water-based sesame milk (WSM) extraction, maximizing total solids (T.S.) recovery. The ANN model's predicted T.S. yield (99.65%) closely matched the actual value (95.18%), demonstrating its potential for optimizing high-yield production. Furthermore, milk permeate was incorporated (5:1 ratio) to create permeate-based sesame milk (PSM), which supported the growth of lactic acid bacteria, suggesting its potential as a growth medium for future probiotic applications. PSM also displayed superior nutritional value and sensory characteristics compared to WSM. These findings highlight the promise of ANN-powered optimization and milk permeate integration for creating innovative sesame milk alternatives with enhanced probiotic viability and sensory appeal. Future research should focus on ANN optimization of alternative-based-plant milk, including permeate-based sesame milk production, the health benefits of LAB fermentation, and consumer preferences for flavors and textures. Optimizing fermentation and LAB selection remain key for commercial success.

Optimization of pullulan production by Aureobasidium pullulans using semi-solid-state fermentation and artificial neural networks: Characterization and antibacterial activity of pullulan impregnated with Ag-TiO2 nanocomposite.

This study presents a novel and efficient approach for pullulan production using artificial neural networks (ANNs) to optimize semi-solid-state fermentation (S-SSF) on faba bean biomass (FBB). This method achieved a record-breaking pullulan yield of 36.81 mg/g within 10.82 days, significantly exceeding previous results. Furthermore, the study goes beyond yield optimization by characterizing the purified pullulan, revealing its unique properties including thermal stability, amorphous structure, and antioxidant activity. Energy-dispersive X-ray spectroscopy and scanning electron microscopy confirmed its chemical composition and distinct morphology. This research introduces a groundbreaking combination of ANNs and comprehensive characterization, paving the way for sustainable and cost-effective pullulan production on FBB under S-SSF conditions. Additionally, the study demonstrates the successful integration of pullulan with Ag@TiO2 nanoparticles during synthesis using Fusarium oxysporum. This novel approach significantly enhances the stability and efficacy of the nanoparticles by modifying their surface properties, leading to remarkably improved antibacterial activity against various human pathogens. These findings showcase the low-cost production medium, and extensive potential of pullulan not only for its intrinsic properties but also for its ability to significantly improve the performance of nanomaterials. This breakthrough opens doors to diverse applications in various fields.

Multifaceted chemical and bioactive features of Ag@TiO2 and Ag@SeO2 core/shell nanoparticles biosynthesized using Beta vulgaris L. extract.

Due to increasing concerns about environmental impact and toxicity, developing green and sustainable methods for nanoparticle synthesis is attracting significant interest. This work reports the successful green synthesis of silver (Ag), silver-titanium dioxide (Ag@TiO2), and silver-selenium dioxide (Ag@SeO2) nanoparticles (NPs) using Beta vulgaris L. extract. Characterization by XRD, SEM, TEM, and EDX confirmed the successful formation of uniformly distributed spherical NPs with controlled size (25 ± 4.9 nm) and desired elemental composition. All synthesized NPs and the B. vulgaris extract exhibited potent free radical scavenging activity, indicating significant antioxidant potential. However, Ag@SeO2 displayed lower hemocompatibility compared to other NPs, while Ag@SeO2 and the extract demonstrated reduced inflammation in a carrageenan-induced paw edema animal model. Interestingly, Ag@TiO2 and Ag@SeO2 exhibited strong antifungal activity against Rhizoctonia solani and Sclerotia sclerotium, as evidenced by TEM and FTIR analyses. Generally, the findings suggest that B. vulgaris-derived NPs possess diverse biological activities with potential applications in various fields such as medicine and agriculture. Ag@TiO2 and Ag@SeO2, in particular, warrant further investigation for their potential as novel bioactive agents.

Turmeric extract-mediated biogenic synthesis of Ag@SeO2 magnetic nanoparticles: characterization, optimization, antibacterial and antioxidant activities.

This study bio-synthesized Ag@SeO2 bmNPs successfully, using turmeric ethanol extract, and characterized them using various techniques. The FT-IR analysis reveals the involvement of these plant-derived compounds, especially phenolics, in the reduction process by acting as electron donors and stabilizing/capping agents. Zeta potential analysis showed a slight negative surface charge for the stability of Ag@SeO2 NPs, where TEM revealed spherical nanoparticles with an average size of 20 nm. The XRD confirmed crystallinity and a core-shell structure, and EDX identified elements consistent with Ag@SeO2 and a 3 : 1 Ag/Se atomic ratio. Further, SEM supported the spherical shape and uniform size. These findings highlight the successful biosynthesis of Ag@SeO2 bmNPs with promising properties for diverse applications. Moreover, the Box-Behnken design (BBD) and artificial neural network (ANN) model were engaged to optimize Ag@SeO2 bmNP biosynthesis. BBD identified significant influences of pH, bioconversion temperature, time, and turmeric concentration on bmNP yield, with adjusted R2 and predictive R2 being 0.9075 and 0.8829, respectively. However, its limitations were revealed by a significant lack of fit. ANN modeling with a 3-5-7-1 topology showed superior predictive accuracy and identified optimal conditions for maximizing yield (pH 9.83, 51.7 °C, 1.0 h, 3.71 mg mL-1 turmeric). Validation experiments confirmed the model's reliability. Turmeric extract exhibited significantly higher amounts of phenolics, and flavonoids compared to the bmNPs, suggesting its potential for strong antioxidant activity. Both turmeric extract and bmNPs displayed antioxidant activity in ABTS and DPPH assays, with turmeric extract being the most potent due to its curcuminoid content. The potential activity of Ag@SeO2 bmNPs against S. aureus, K. pneumonia, E. coli, and B. cereus was investigated, with inhibition zones ranging from 22 to 32 mm. The MIC values of tested NPs towards pathogenic bacteria ranged from 165.625 and 331.25 µg mL-1.

Lytic and Molecular Evidence of the Widespread Coriander Leaf Spot Disease Caused by Alternaria dauci.

Coriandrum sativum L. is a globally significant economic herb with medicinal and aromatic properties. While coriander leaf blight disease was previously confined to India and the USA, this study presents new evidence of its outbreak in Africa and the Middle East caused by Alternaria dauci. Infected leaves display irregular chlorotic to dark brown necrotic lesions along their edges, resulting in leaf discoloration, collapse, and eventual death. The disease also impacts inflorescences and seeds, significantly reducing seed quality. Koch's postulates confirmed the pathogenicity of the fungus through the re-isolation of A. dauci from artificially infected leaves, and its morphology aligns with typical A. dauci features. Notably, this study identified strong lytic activity (cellulase: 23.76 U, xylanase: 12.83 U, pectinase: 51.84 U, amylase: 9.12 U, and proteinase: 5.73 U), suggesting a correlation with pathogenicity. Molecular characterization using ITS (ON171224) and the specific Alt-a-1 gene (OR236142) supports the fungal morphology. This research provides the first comprehensive documentation of the pathological, lytic, and molecular evidence of A. dauci leaf blight disease on coriander. Future investigations should prioritize the development of resistant coriander varieties and sustainable disease management strategies, including the use of advanced molecular techniques for swift and accurate disease diagnosis to protect coriander from the devastating impact of A. dauci.

Application of artificial neural networks for enhancing Aspergillus flavipes lipase synthesis for green biodiesel production.

Biodiesel is a sustainable, and renewable alternative to fossil fuels that can be produced from various biological sources with the aid of lipases. This study developed a simple and novel fungal system for lipase biosynthesis to be used for catalyzing the oily residuals into biodiesel, employing the artificial neural network (ANN), and semi-solid-state fermentation (SSSF). Nigella sativa was selected among agro-industrial oily residuals as a substrate for lipase biosynthesis by Aspergillus flavipes MH47297. The effect of cultural humidity (X1), the surfactant; Brij 35 (X2), and inoculum density (X3) on lipase biosynthesis were researched based on the matrix of Box-Behnken design (BBD). The ANN together with a new fungal candidate and SSSF were then applied for the first time to model the biosynthesis process of lipase. The optimum predicted cultural conditions varied according to the model. The optimum predicted conditions were estimated separately by BBD (X1 = 5.8 ml water/g, X2 = 46.6 µl/g, and X3 = 62156610 spore/g) and ANN (X1 = 5.4 ml water/g, X2 = 54.2 µl/g, and X3 = 100000000 spore/g) models. Based on the modeling process, the response of lipase was calculated to be 214.95 (BBD) and 217.72 U (ANN), which revealed high consistency with the experimental lipase yield (209.13 ± 3.27 U for BBD, and 218 ± 2.01 U for ANN). Despite both models showing high accuracy, ANN was more accurate and surpassed the BBD model. Gas chromatography analysis showed that lipase successfully converted corn oil to biodiesel (29.5 mg/l).

A Comparative Study of Cr(VI) Sorption by Aureobasidium pullulans AKW Biomass and Its Extracellular Melanin: Complementary Modeling with Equilibrium Isotherms, Kinetic Studies, and Decision Tree Modeling.

Melanin as a natural polymer is found in all living organisms, and plays an important role in protecting the body from harmful UV rays from the sun. The efficiency of fungal biomass (Aureobasidium pullulans) and its extracellular melanin as Cr(VI) biosorbents was comparatively considered. The efficiency of Cr(VI) biosorption by the two sorbents used was augmented up to 240 min. The maximum sorption capacities were 485.747 (fungus biomass) and 595.974 (melanin) mg/g. The practical data were merely fitted to both Langmuir and Freundlich isotherms. The kinetics of the biosorption process obeyed the pseudo-first-order. Melanin was superior in Cr(VI) sorption than fungal biomass. Furthermore, four independent variables (contact time, initial concentration of Cr(VI), biosorbent dosage, and pH,) were modeled by the two decision trees (DTs). Conversely, to equilibrium isotherms and kinetic studies, DT of fungal biomass had lower errors compared to DT of melanin. Lately, the DTs improved the efficacy of the Cr(VI) removal process, thus introducing complementary and alternative solutions to equilibrium isotherms and kinetic studies. The Cr(VI) biosorption onto the biosorbents was confirmed and elucidated through FTIR, SEM, and EDX investigations. Conclusively, this is the first report study attaining the biosorption of Cr(VI) by biomass of A. pullulans and its extracellular melanin among equilibrium isotherms, kinetic study, and algorithmic decision tree modeling.

A comparative study using response surface methodology and artificial neural network towards optimized production of melanin by Aureobasidium pullulans AKW.

The effect of three independent variables (i.e., tyrosine, sucrose, and incubation time) on melanin production by Aureobasidium pullulans AKW was unraveled by two distinctive approaches: response surface methodology (i.e. Box Behnken design (BBD)) and artificial neural network (ANN) in this study for the first time ever using a simple medium. Regarding BBD, sucrose and incubation intervals did impose a significant influence on the output (melanin levels), however, tyrosine did not. The validation process exhibited a high consistency of BBD and ANN paradigms with the experimental melanin production. Concerning ANN, the predicted values of melanin were highly comparable to the experimental values, with minor errors competing with BBD. Highly comparable experimental values of melanin were achieved upon using BBD (9.295 ± 0.556 g/L) and ANN (10.192 ± 0.782 g/L). ANN accurately predicted melanin production and showed more improvement in melanin production by about 9.7% higher than BBD. The purified melanin structure was verified by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction pattern (XRD), and thermogravimetric analysis (TGA). The results verified the hierarchical architecture of the particles as small compasses by SEM analysis, inter-layer spacing in the XRD analysis, maximal atomic % for carbon, and oxygen atoms in the EDX analysis, and the great thermal stability in the TGA analysis of the purified melanin. Interestingly, the current novel endophytic strain was tyrosine-independent, and the uniquely applied ANN paradigm was more efficient in modeling the melanin production with appreciate amount on a simple medium in a relatively short time (168 h), suggesting additional optimization studies for further maximization of melanin production.

A Simple Formula of the Endophytic Trichoderma viride, a Case Study for the Management of Rhizoctonia solani on the Common Bean.

The utilization of beneficial endophytic microorganisms presents a promising and innovative strategy for attaining environmental sustainability and fostering development. The majority of microbial bioagents are unsuitable for preparation in a suitable granular formula, and few are prepared in complicated formulas. In this work, Trichoderma viride was simply prepared in a marketable granular formula to manage Rhizoctonia solani and improve common bean growth. The GC-MS analysis showed several antimicrobial compounds in the fungal filtrate. T. viride was able to suppress the phytopathogenic R. solani in the laboratory. The formula had up to 6 months of shelf-life viability. Under greenhouse conditions, the formula improved plant resistance against R. solani. Moreover, the vegetative plant growth and physiological performance (peroxidase, polyphenol, total phenols, phenylalanine ammonia-lyase, and photosynthetic pigments) of the common bean showed obvious promotion. The formula reduced the disease incidence by 82.68% and increased the yield by 69.28%. This work may be considered a step in the right direction for producing simple bioactive products on a large scale. Moreover, the study's findings suggest that this method can be considered a novel approach to enhancing plant growth and protection, in addition to reducing costs, improving handling and application, and maintaining fungal viability for enhancing plant growth and protecting against fungal infections.

Pseudomonas alcaliphila NEWG-2 as biosorbent agent for methylene blue dye: optimization, equilibrium isotherms, and kinetic processes.

In comparison to physicochemical and chemical methods, microbial dye biosorption is regarded as an eco-effective and economically viable alternative and is a widely applied method due to its high efficiency and compatibility with the environment. Therefore, the idea of this study is to clarify to what extent the viable cells and the dry biomass of Pseudomonas alcaliphila NEWG-2 can improve the biosorption of methylene blue (MB) from a synthetic wastewater sample. The array of Taguchi paradigm has been conducted to ascertain five variables affecting the biosorption of MB by broth forms of P. alcaliphila NEWG. The data of MB biosorption were familiar to the predicted ones, indicating the precision of the Taguchi model's prediction. The maximum biosorption of MB (87.14%) was achieved at pH 8, after 60 h, in a medium containing 15 mg/ml MB, 2.5% glucose, and 2% peptone, with sorting the highest signal-to-noise ratio (38.80). FTIR spectra detected various functional groups (primary alcohol, α, ß-unsaturated ester, symmetric NH2 bending, and strong C-O stretching) on the bacterial cell wall that participated in the biosorption of MB. Furthermore, the spectacular MB biosorption ability was validated by equilibrium isotherms and kinetic studies (the dry biomass form), which were derived from the Langmuir model (qmax = 68.827 mg/g). The equilibrium time was achieved in about 60 min, with 70.5% of MB removal. The biosorption kinetic profile might be adequately represented by pseudo-second order and Elovich models. The changes in the bacterial cells before and after the biosorption of MB were characterized using a scanning electron microscope. As realized from the aforementioned data, the bacterium is a talented, effective, eco-friendly, and low-cost bio-sorbent for the decolorization and remedy of an industrial effluent containing MB from an aqueous environment. The current outcomes in the biosorption of MB molecules promote the use of the bacterial strain as viable cells and/or dry biomass in ecosystem restoration, environmental cleanup, and bioremediation studies.

Exclusive Biosynthesis of Pullulan Using Taguchi's Approach and Decision Tree Learning Algorithm by a Novel Endophytic Aureobasidium pullulans Strain.

Pullulan is a biodegradable, renewable, and environmentally friendly hydrogel biopolymer, with potential uses in food, medicine, and cosmetics. New endophytic Aureobasidium pullulans (accession number; OP924554) was used for the biosynthesis of pullulan. Innovatively, the fermentation process was optimized using both Taguchi's approach and the decision tree learning algorithm for the determination of important variables for pullulan biosynthesis. The relative importance of the seven tested variables that were obtained by Taguchi and the decision tree model was accurate and followed each other's, confirming the accuracy of the experimental design. The decision tree model was more economical by reducing the quantity of medium sucrose content by 33% without a negative reduction in the biosynthesis of pullulan. The optimum nutritional conditions (g/L) were sucrose (60 or 40), K2HPO4 (6.0), NaCl (1.5), MgSO4 (0.3), and yeast extract (1.0) at pH 5.5, and short incubation time (48 h), yielding 7.23% pullulan. The spectroscopic characterization (FT-IR and 1H-NMR spectroscopy) confirmed the structure of the obtained pullulan. This is the first report on using Taguchi and the decision tree for pullulan production by a new endophyte. Further research is encouraged for additional studies on using artificial intelligence to maximize fermentation conditions.

Domiciliation of Trichoderma asperellum Suppresses Globiosporangium ultimum and Promotes Pea Growth, Ultrastructure, and Metabolic Features.

The beneficial microorganisms represent a new and hopeful solution for a sustainable environment and development. In this investigation, Trichoderma asperellum ZNW, isolated from seeds, was domiciliated within the pea plant for improving growth, disease management, and enhancement of productivity. Globisporangium ultimum NZW was isolated from deformed pea seeds, representing the first record of the pathogen caused by pea damping-off. Both fungi were molecularly identified. T. asperellum ZNW produced several lytic enzymes and bioactive metabolites as detected by GC-MC. The SEM illustrated the mycoparasitic behavior of T. asperellum ZNW on G. ultimum NZW mycelia. In the pot experiment, T. asperellum domiciliated the root and grew as an endophytic fungus, leading to root vessel lignification. Under soil infection, T. asperellum reduced damping-off, by enhancing peroxidase, polyphenol, total phenols, and photosynthetic pigments content. The vegetative growth, yield, and soil dehydrogenase activity were improved, with an enhancement in the numerical diversity of the microbial rhizosphere. This work may enable more understanding of the plant-fungal interaction, yet, working on domiciliation is recommended as a new approach to plant protection and growth promotion under various ecological setups.

Innovative biosynthesis, artificial intelligence-based optimization, and characterization of chitosan nanoparticles by Streptomyces microflavus and their inhibitory potential against Pectobacterium carotovorum.

Microbial-based strategy in nanotechnology offers economic, eco-friendly, and biosafety advantages over traditional chemical and physical protocols. The current study describes a novel biosynthesis protocol for chitosan nanoparticles (CNPs), employing a pioneer Streptomyces sp. strain NEAE-83, which exhibited a significant potential for CNPs biosynthesis. It was identified as Streptomyces microflavus strain NEAE-83 based on morphological, and physiological properties as well as the 16S rRNA sequence (GenBank accession number: MG384964). CNPs were characterized by SEM, TEM, EDXS, zeta potential, FTIR, XRD, TGA, and DSC. CNPs biosynthesis was maximized using a mathematical model, face-centered central composite design (CCFCD). The highest yield of CNPs (9.41 mg/mL) was obtained in run no. 27, using an initial pH of 5.5, 1% chitosan, 40 °C, and a 12 h incubation period. Innovatively, the artificial neural network (ANN), was used for validating and predicting CNPs biosynthesis based on the trials data of CCFCD. Despite the high precision degree of both models, ANN was supreme in the prediction of CNPs biosynthesis compared to CCFCD. ANN had a higher prediction efficacy and, lower error values (RMSE, MDA, and SSE). CNPs biosynthesized by Streptomyces microflavus strain NEAE-83 showed in-vitro antibacterial activity against Pectobacterium carotovorum, which causes the potato soft rot. These results suggested its potential application for controlling the destructive potato soft rot diseases. This is the first report on the biosynthesis of CNPs using a newly isolated; Streptomyces microflavus strain NEAE-83 as an eco-friendly approach and optimization of the biosynthesis process by artificial intelligence.

Innovative binary sorption of Cobalt(II) and methylene blue by Sargassum latifolium using Taguchi and hybrid artificial neural network paradigms.

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, ß-unsaturated ester, α, ß-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.

Seed Endophytic Achromobacter sp. F23KW as a Promising Growth Promoter and Biocontrol of Rhizoctonia Root Rot of Fenugreek.

Root rot is one of the most significant soil and seed-borne fungal diseases, limiting the cultivation of fenugreek plants. Endophytic bacteria and their natural bioproducts have emerged as growth promoters and disease suppressors in the current era. Despite limited research, seeds are a good funder of endophytic microbiomes, which are transmitted from them to other seedling parts, thereby providing a shield against biotic and abiotic anxiety and promoting the growth at early germination and later stages. The current study evaluated the hypothesis that seed endophytic bacteria and their lytic enzymes, growth promotors, and antifungal molecules can induce growth, and inhibit root rot disease development at the same time. The isolation trial from fenugreek seeds revealed a lytic Achromobacter sp., which produces indole acetic acid, has antifungal compounds (e.g., 2-Butanol, 3,3'-oxybis-), and reduces the growth of Rhizoctonia solani by 43.75%. Under the greenhouse and natural field conditions, bacterial cells and/or supernatant improved the growth, physiology, and yield performance of fenugreek plants, and effectively suppressed the progress of root rot disease; this is the first extensive study that uses a new seed-borne endophytic bacterium as a plant-growth-promoting, and biocontrol tool against the sclerotia-forming; R. solani; the causative of fenugreek root rot.

New Strategy for Inducing Resistance against Bacterial Wilt Disease Using an Avirulent Strain of Ralstonia solanacearum.

Ralstonia solanacearum is one of the globally significant plant pathogens that infect a wide host range of economically important plants. A study was conducted to evaluate the hypothesis that an avirulent strain of R. solanacearum can act as a biocontrol mediator for managing potato bacterial wilt. Virulent R. solanacearum was isolated and identified (GenBank accession number; OP180100). The avirulent strain was obtained from the virulent strain through storage for 3 weeks until the development of deep red colonies. The virulent strain had higher lytic activity than the avirulent strain. Tubers' treatments by the avirulent strain of R. solanacearum, (supernatant, boiled supernatant, and dead cells) significantly reduced plant disease rating and increased the growth, physiological activities, and biomass of potato compared to the untreated, infected control. The major components detected by GC-MS in the supernatant revealed 10.86% palmitic acid (virulent), and 18.03% 1,3-dioxolane, 2,4,5-trimethyl- (avirulent), whereas the major component in the boiled supernatant was 2-hydroxy-gamma-butyrolactone in the virulent (21.17%) and avirulent (27.78%) strains. This is the first research that assessed the influence of boiled supernatant and dead cells of virulent and avirulent R.solanacearum strains in controlling bacterial wilt disease. Additional work is encouraged for further elucidation of such a topic.

Optimization of Heavy Metals Biosorption via Artificial Neural Network: A Case Study of Cobalt (II) Sorption by Pseudomonas alcaliphila NEWG-2.

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.

A Novel Endophytic Trichoderma longibrachiatum WKA55 With Biologically Active Metabolites for Promoting Germination and Reducing Mycotoxinogenic Fungi of Peanut.

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.

Natural Melanin: Current Trends, and Future Approaches, with Especial Reference to Microbial Source.

Melanin is a universal natural dark polymeric pigment, arising in microorganisms, animals, and plants. There is a couple of pieces of literature on melanin, each focusing on a different issue, the goal of the present review is to focus on microbial melanin. It has numerous benefits with very few drawbacks. The current situation and expected trends are discussed. Intriguing, numerous studies have provoked a serious necessity for a comprehensive assessment of microbial melanin pigments. So that, such review would help scholars from diverse backgrounds to realize the importance of melanin pigments isolated from microorganisms, with this aim in mind, information, and hypothesis from this review could be the paradigm for studies on melanin in the next era.

An innovative green synthesis approach of chitosan nanoparticles and their inhibitory activity against phytopathogenic Botrytis cinerea on strawberry leaves.

Green synthesis is a newly emerging field of nanobiotechnology that offers economic and environmental advantages over traditional chemical and physical protocols. Nontoxic, eco-friendly, and biosafe materials are used to implement sustainable processes. The current work proposes a new biological-based strategy for the biosynthesis of chitosan nanoparticles (CNPs) using Pelargonium graveolens leaves extract. The bioconversion process of CNPs was maximized using the response surface methodology. The best combination of the tested parameters that maximized the biosynthesis process was the incubation of plant extract with 1.08% chitosan at 50.38 °C for 57.53 min., yielding 9.82 ± 3 mg CNPs/mL. Investigation of CNPs by SEM, TEM, EDXS, zeta potential, FTIR, XRD, TGA, and DSC proved the bioconversion process's success. Furthermore, the antifungal activity of the biosynthesized CNPs was screened against a severe isolate of the phytopathogenic Botrytis cinerea. CNPs exerted efficient activity against the fungal growth. On strawberry leaves, 25 mg CNPs/mL reduced the symptoms of gray mold severity down to 3%. The higher concentration of CNPs (50 mg/mL) was found to have a reverse effect on the infected area compared with those of lower concentrations (12.5 and 25 mg CNPs/mL). Therefore, additional work is encouraged to reduce the harmful side effects of elevated CNPs concentrations.