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Review
. 2020 Oct 20:11:581997.
doi: 10.3389/fmicb.2020.581997. eCollection 2020.

Valorization of Vegetable Food Waste and By-Products Through Fermentation Processes

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Review

Valorization of Vegetable Food Waste and By-Products Through Fermentation Processes

Carlos Sabater et al. Front Microbiol. .

Abstract

There is a general interest in finding new ways of valorizing fruit and vegetable processing by-products. With this aim, applications of industrial fermentation to improve nutritional value, or to produce biologically active compounds, have been developed. In this sense, the fermentation of a wide variety of by-products including rice, barley, soya, citrus, and milling by-products has been reported. This minireview gives an overview of recent fermentation-based valorization strategies developed in the last 2 years. To aid the designing of new bioprocesses of industrial interest, this minireview also provides a detailed comparison of the fermentation conditions needed to produce specific bioactive compounds through a simple artificial neural network model. Different applications reported have been focused on increasing the nutritional value of vegetable by-products, while several lactic acid bacteria and Penicillium species have been used to produce high purity lactic acid. Bacteria and fungi like Bacillus subtilis, Rhizopus oligosporus, or Fusarium flocciferum may be used to efficiently produce protein extracts with high biological value and a wide variety of functional carbohydrates and glycosidases have been produced employing Aspergillus, Yarrowia, and Trichoderma species. Fermentative patterns summarized may guide the production of functional ingredients for novel food formulation and the development of low-cost bioprocesses leading to a transition toward a bioeconomy model.

Keywords: bioeconomy; by-product Valorization; food waste; lactic acid bacteria; microbial fermentation.

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Figures

FIGURE 1
FIGURE 1
Production of some chemical and/or bioactive compounds from plant-waste by the metabolic activity of lactic acid bacteria (LAB) (A) and distribution of fermentation data from studies found in the bibliography by artificial neural network-based principal component analysis (PCA). Differences according to substrate used (B), microorganisms inoculated (C) and valorization objective (D) and are shown.

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