Acidogenic Fermentation of Brewers' Spent Grain Monitored through Two-Dimensional Fluorescence Spectroscopy

被引:6
作者
Guarda, Eliana C. [1 ,2 ]
Costa, Eunice [3 ]
Gil, Catia [1 ,2 ]
Amorim, Catarina L. [3 ]
Galinha, Claudia F. [4 ]
Duque, Anouk F. [1 ,2 ]
Castro, Paula M. L. [3 ]
Reis, Maria A. M. [1 ,2 ]
机构
[1] Univ NOVA Lisboa, Inst Hlth & Bioecon, NOVA Sch Sci & Technol, Associate Lab i4HB, P-2829516 Caparica, Portugal
[2] Univ NOVA Lisboa, NOVA Sch Sci & Technol, Dept Chem, UCIBIO Appl Mol Biosci unit, P-2829516 Caparica, Portugal
[3] Univ Catolica Portuguesa, Ctr Biotecnol & Quim Fina, Lab Associado, Escola Super Biotecnol, P-4169005 Porto, Portugal
[4] Univ NOVA Lisboa, NOVA Sch Sci & Technol, Chemistr Dept y, LAQV REQUIMTE, P-2829516 Caparica, Portugal
关键词
ANAEROBIC FERMENTATION; WASTE; PERFORMANCE; FOOD; PH; CULTURES; PRODUCT; IMPACT; ACID; TOOL;
D O I
10.1021/acssuschemeng.3c00316
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Biological systems are commonly controlled and monitored through offline and time-consuming tools, which often impairs an effective and real-time response to counteract system disturbances. The feasibility of using two-dimensional (2D) fluorescence spectroscopy as a non-invasive, non-destructive, and real-time procedure to monitor the acidogenic fermentation of brewer's spent grain (BSG) in a granular sludge reactor was evaluated. For that, the effect of pH fluctuations on the system response was used as a model to ascertain the 2D fluorescence spectroscopy applicability to monitor the process performance, namely, to predict the fermentation products (FP) and the soluble protein (SProt) concentrations in the effluent stream through protein (SProt) through mathematical analysis. The pH fluctuations over the course of the reactor's operation altered the granules' microbiome composition, leading to different effluent FP profiles. Fluorescence excitation-emission matrices (EEMs) were used with projection to latent structures (PLS) modeling to predict the FP and SProt concentrations in the effluent with average errors below 0.75 and 0.43 g L-1, respectively. Both models were able to capture the tendency of the data even when the accuracy of prediction was not so high. The combined approach of using 2D fluorescence spectroscopy and mathematical analysis seemed promising for real-time monitoring of the fermentation of complex substrates.
引用
收藏
页码:7398 / 7406
页数:9
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