Inicio  /  Applied Sciences  /  Vol: 11 Par: 7 (2021)  /  Artículo
ARTÍCULO
TITULO

A Two-Stage Process for Conversion of Brewer?s Spent Grain into Volatile Fatty Acids through Acidogenic Fermentation

Eliana C. Guarda    
Ana Catarina Oliveira    
Sílvia Antunes    
Filomena Freitas    
Paula M. L. Castro    
Anouk F. Duque and Maria A. M. Reis    

Resumen

This work is focused on the valorization of brewer?s spent grains (BSG) into volatile fatty acids (VFA) through acidogenic fermentation. VFAs are building blocks for several applications, such as bioplastics? production. Using acid hydrolysis as pre-treatment, several batch assays were performed and the impact of organic load (OL) and pH on VFA production from BSG hydrolysate was assessed. Regardless of the condition, the produced acids were mainly butyric and acetic acids followed by propionic acid. The OL had a direct impact on the total organic acid concentration with higher concentrations at the highest OL (40 gCOD L-1). pH affected the concentration of individual organic acid, with the highest fermentation products (FP) diversity attained at pH 5.0 and OL of 40 gCOD L-1. To assess the potential application of organic acids for biopolymers (such as polyhydroxyalkanoates) production, the content in hydroxybutyrate (HB) and hydroxyvalerate (HV) monomers was estimated from the respective precursors produced at each pH and OL. The content in HV precursors increased with pH, with a maximum at pH 6.0 (ca. 16% C-mol basis). The acidogenic fermentation of BSG hydrolysate was also assessed in continuous operation, using an expanded granular sludge bed reactor (EGSB). It was shown that the BSG hydrolysate was successfully converted to VFAs without pH control, achieving higher productivities than in the batch operation mode.

 Artículos similares

       
 
Catur Supriyanto, Abu Salam, Junta Zeniarja and Adi Wijaya    
This research paper presents a deep-learning approach to early detection of skin cancer using image augmentation techniques. We introduce a two-stage image augmentation process utilizing geometric augmentation and a generative adversarial network (GAN) t... ver más
Revista: Computation

 
Jiahui Qian, Wenjun Xia, Zhangyan Zhao and Faju Qiu    
Due to uncontrollable influences of the manufacturing process and different construction environments, there are significant challenges to extracting accurate positioning points for the lifting holes in prefabricated beams. In this study, we propose a tw... ver más
Revista: Applied Sciences

 
Lihong Zhang, Chaolong Liu and Nan Jia    
Multimodal emotion classification (MEC) has been extensively studied in human?computer interaction, healthcare, and other domains. Previous MEC research has utilized identical multimodal annotations (IMAs) to train unimodal models, hindering the learning... ver más
Revista: Applied Sciences

 
Esmaeil Zahedi, Mohamad Saraee, Fatemeh Sadat Masoumi and Mohsen Yazdinejad    
Unsupervised anomalous sound detection, especially self-supervised methods, plays a crucial role in differentiating unknown abnormal sounds of machines from normal sounds. Self-supervised learning can be divided into two main categories: Generative and C... ver más
Revista: Algorithms

 
Gauri Vaidya, Meghana Kshirsagar and Conor Ryan    
Neural networks have revolutionised the way we approach problem solving across multiple domains; however, their effective design and efficient use of computational resources is still a challenging task. One of the most important factors influencing this ... ver más
Revista: Algorithms