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From stale bread and brewers spent grain to a new food source using edible filamentous fungi.

Rebecca Gmoser | Rikard Fristedt | Karin Larsson | Ingrid Undeland | Mohammad J Taherzadeh | Patrik R Lennartsson
Bioengineered | 2020

By-products from the food sector with a high load of organic matter present both a waste-handling problem related to expenses and to the environment, yet also an opportunity. This study aims to increase the value of stale bread and brewers spent grain (BSG) by re-introducing these residues to the food production chain by converting them to new protein-enriched products using the edible filamentous fungi Neurospora intermedia and Rhizopusoryzae. After 6 days of solid state fermentation (at 35°C, with a95% relative humidity and moisture content of 40% in the substrate) on stale bread, a nutrient-rich fungal-fermented product was produced. The total protein content, as analyzed by total amino acids, increased from 16.5% in stale sourdough bread to 21.1% (on dry weight basis) in the final product with an improved relative ratio of essential amino acids. An increase in dietary fiber, minerals (Cu, Fe, Zn) and vitamin E, as well as an addition of vitamin D2 (0.89 µg/g dry weight sample) was obtained compared with untreated stale bread. Furthermore, addition of BSG to the sourdough bread with the aim to improve textural changes after fermentation showed promising outcomes. Cultivation of N. intermedia or R. oryzae on stale sourdough bread mixed with 6.5% or 11.8% BSG, respectively, resulted in fungal-fermented products with similar textural properties to a commercial soybean burger. Bioconversion of stale bread and BSG by fungal solid state fermentation to produce a nutrient-enriched food product was confirmed to be a successful way to minimize food waste and protein shortage.

Pubmed ID: 32449450

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RRID:SCR_014483

A statistical software package that allows the user to import data, create graphs, and perform statistical analysis. It can perform basic statistical tests like descriptive statistics, hypothesis tests, confidence intervals, and normality tests as well as regression and ANOVA and quality assessment.

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