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Production of Cellulases by Trichoderma, Aspergillus, and Penicillium: Optimization Strategies, Biomass Valorization, and Industrial Perspectives

Aug 2026 · Biomass · 0 citations · 160 references

TL;DR

Fungal cellulases are key biocatalysts for lignocellulosic biomass valorization and the development of sustainable biorefineries and the complementary characteristics of these fungi genera support their application in integrated biomass conversion and future lignocellulosic biorefineries.

Abstract

Fungal cellulases are key biocatalysts for lignocellulosic biomass valorization and the development of sustainable biorefineries. This review examines recent advances in the production of endoglucanase (EGL), exoglucanase (EXG), and β-glucosidase (BGL) by fungi of the genera Trichoderma, Aspergillus, and Penicillium under solid-state fermentation (SSF) and submerged fermentation (SmF). Emphasis is placed on fermentation strategies, substrate selection, process optimization, and emerging chemometric and artificial intelligence-based approaches. The literature reveals a predominance of SSF systems, especially when agri-food residues such as wheat bran, sugarcane bagasse, rice-derived residues, fruit-processing wastes, and cocoa by-products are employed as low-cost substrates. Among the evaluated genera, Aspergillus was among the most frequently investigated genera and exhibited broad substrate versatility, whereas Trichoderma reesei remains the principal industrial production host for cellulase-rich enzyme preparations used mainly in the saccharification of lignocellulosic biomass for cellulosic ethanol and other biorefinery applications. In contrast, Penicillium stands out as an important source of BGL, complementing cellulase systems derived from other fungi. Temperature, pH, moisture content, and fermentation time were consistently identified as the main factors affecting cellulase biosynthesis, with optimal production generally occurring under mildly acidic conditions and mesophilic temperatures. CCD and BBD were the predominant optimization strategies, while artificial neural network-based models are emerging as promising alternatives. The complementary characteristics of these fungi genera support their application in integrated biomass conversion and future lignocellulosic biorefineries.

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