Bioprocess development with special yeasts for cassava bagasse enrichment nutritional to use in animal feed

Shinya, Thaís; Elsner, Victor Henrique Pereira; Júnior, David Spressão de Lima; Ranke, Fabiane Fernanda de Barros; Escaramboni, Bruna; Melo, Weilan Gomes da Paixão; Núñez, Eutímio Gustavo Fernández; Neto, Pedro de Oliva

doi:10.1016/j.anifeedsci.2022.115338

Cited by 4 publications

(1 citation statement)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, breeding cows require a special feeding system, the Total Mixed Ration (TMR) system, which provides a proper mixture of concentrated and roughage feed to meet the nutritional needs of the animal for rapid growth (Schingoethe 2017). It is recommended to enrich feed biomass by using it as a substrate for the biosynthesis of single cell protein (SCP) (Shinya et al 2022). The easiest way to enrich biomass is fermentation with waste biomass as a culture medium, providing a homogenous product.…”

Section: Introductionmentioning

confidence: 99%

Sugar beet processing waste as a substrate for yeast protein production for livestock feed

Dygas

Berłowska

2023

BioRes

View full text Add to dashboard Cite

This study investigated the optimal yeast strains for producing single cell protein based on waste sugar beet pulp (SBP) under various biomass loads. All tested strains were capable of growing on the waste biomass. Candida utilis and Saccharomyces cerevisiae Ethanol Red produced the greatest increase in protein on fresh SBP (ΔN 1.84%). Scheffersomyces stipitis (ΔN 2.27%) provided the highest increase on dried SBP. All tested strains showed significant assimilation of nitrogenous compounds. Based on the crude fiber content after fermentation, the largest reduction in fiber occurred with Candida utilis R6 (10.5%) on fresh SBP, and Yarrowia lipolytica (13.1%) on dried SBP. These results demonstrate the potential of SBP as a substrate for the production of single cell protein and highlight the importance of selecting the appropriate strains to optimize the process.

show abstract

Section: Introductionmentioning

confidence: 99%