Evidence map›Paper›PMID 42688443›Full record

ArticleFrontiers in bioengineering and biotechnology2026

Sustainable and integrated cascade valorization of the biomass generated by the invasive plant

Paulina Falletti, María F Barrera Vázquez, Elia S Mendoza Ocampo, Paulina L Páez, Raquel E Martini, Patricia Lema, Laura R Comini

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Article in Frontiers in bioengineering and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Paulina FallettiFacultad de Ciencias Exactas Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina.
María F Barrera VázquezFacultad de Ciencias Exactas Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina.
Elia S Mendoza OcampoUnidad de Investigaciones y Desarrollo en Tecnología Farmacéutica (UNITEFA - CONICET), Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Córdoba, Argentina.
Paulina L PáezUnidad de Investigaciones y Desarrollo en Tecnología Farmacéutica (UNITEFA - CONICET), Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Córdoba, Argentina.
Raquel E MartiniFacultad de Ciencias Exactas Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina.
Patricia LemaInstituto de Ingeniería Química, Facultad de Ingeniería, Universidad de la República (UDELAR), Montevideo, Uruguay.
Laura R CominiConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Córdoba, Argentina.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study addresses the integrated valorization of residual biomass from Flaveria bidentis, an invasive species native to the Americas through the recovery of phenolic compounds (phenolic acids and flavonoids, mainly glycosylated and sulfated - the latter being rare in nature -) and their subsequent use in the green synthesis of silver nanoparticles. The optimization of ultrasound-assisted aqueous extraction of phenolic compounds from F. bidentis biomass and the direct use of the resulting extracts as reducing and stabilizing agents for the green synthesis of silver nanoparticles remain largely unexplored. Methods: The phenolic compounds were extracted by ultrasound-assisted extraction (UAE) using water as extraction solvent. Extraction time, temperature, and solvent/sample ratio were optimized within the investigated experimental domain using response surface methodology based on a three-variable Doehlert experimental design (R2 ≥ 0.96). The optimized aqueous extracts were then used directly, without purification, as reducing and stabilizing agents in the green synthesis of silver nanoparticles. These nanoparticles were characterized in terms of size and morphology, and their antibacterial activity against Gram- positive and Gram-negative bacteria was subsequently evaluated using the diffusion assay. Results and Discussion: Optimal conditions for phenols extraction were established from leaves (68 min, 59 °C, 20 mL/ g) and from flowers (65 min, 75 °C, 20 mL/g). Under these conditions, the results revealed a key finding: the high yield of phenolic compounds from F. bidentis, particularly from the leaves (250.86 mg/g), using water as the sole solvent. Spherical biogenic silver nanoparticles (∼30-31 nm; PDI: 0.26-0.46; ζ-potential: -15.0 to -12.1 mV) were successfully synthesized and exhibited significant antimicrobial activity. The results demonstrate the feasibility of integrating phenolic extraction and nanoparticle synthesis into a single process, in which the aqueous extracts obtained under optimized conditions can be directly employed to produce functional nanomaterials without intermediate purification steps. Thus, the proposed cascade valorization strategy enabled the sustainable transformation of

Indexed as

antimicrobial activityantioxidant compoundsbiogenic silver nanoparticlesgreen ultrasound-assisted extractionoptimization

Identifiers

PMID42688443
PMCPMC13534056

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