Production of medium-chain fatty acid caproate from Chinese liquor distillers' grain using pit mud as the fermentation microbes

Chinese liquor distillers' grain (CLDG) is an abundant industrial organic waste showing high potential as feedstock for biofuel conversion. In this study, CLDG was used as substrate by microbial community in pit mud to produce medium-chain fatty acids (especially caproate). Simulated and real fermentation were used to evaluate the effect of ethanol and lactic acid being the electronic donors (EDs) during the anaerobic chain elongation (CE). The caproate concentration was achieved at 449 mg COD/g VS, with the corresponding high carbon selectivity at 37.1%. Microbial analysis revealed that the domestication of pit mud increased the abundance of Caproiciproducens (converting lactic acid into caproate) and Lactobacillus (producing lactic acid), leading to enhanced caproate production. The lactic acid conversion facilitated in full utilization of ethanol through CE consumption. The coexistence of EDs benefited the CE system and that this green energy production can be a promising high-performance biofuel donor for sustainable industrial production development.

Supercritical Carbon Dioxide + Ethanol Extraction to Improve Organoleptic Attributes of Pea Flour with Applications of Sensory Evaluation, HS-SPME-GC, and GC-Olfactory

Supercritical carbon dioxide + ethanol (SC-CO2+EtOH) extraction, was employed as a deflavoring method to improve the sensory properties of pea flours. Furthermore, the impacts of particle size along with extraction on volatile profile and sensory attributes of pea flours were investigated using multiple approaches. These included headspace solid-phase microextraction-gas chromatography (HS-SPME-GC), GC-olfactometry (GC-O), and quantitative descriptive analysis (QDA) using a trained sensory panel. Total volatile contents of non-deflavored and deflavored whole pea flour and its fractions were in the range of 7.1 ± 0.3 to 18.1 ± 1.0 µg/g and 0.4 ± 0.1 to 2.7 ± 0.4 µg/g, respectively. The GC-O system showed that the total volatile intensity was in the range of 14.5 to 22.0 and 0 to 3.5, for non-deflavored and deflavored pea flours, respectively. Volatile analyses indicated that 1-hexanol, 1-octanol, 1-nonanol, nonanal, and 2-alkyl methoxypyrazines were major off-aroma compounds. Most off-aroma compounds were not detected in deflavored pea flours. QDA revealed less pea intensity and bitterness of deflavored pea flours. The larger particle size of flours resulted in less off-aroma compounds based on the GC data but more bitterness based on QDA. The SC-CO2+EtOH extraction at optimum conditions and particle size modifications can be a potential technology to improve the organoleptic properties of pulse ingredients.

Generalized Likelihood Uncertainty Estimation (GLUE) methodology for optimization of extraction in natural products

Optimization process is an important aspect in the natural product extractions. Herein, an alternative approach is proposed for the optimization in extraction, namely, the Generalized Likelihood Uncertainty Estimation (GLUE). The approach combines the Latin hypercube sampling, the feasible range of independent variables, the Monte Carlo simulation, and the threshold criteria of response variables. The GLUE method is tested in three different techniques including the ultrasound, the microwave, and the supercritical CO₂ assisted extractions utilizing the data from previously published reports. The study found that this method can: provide more information on the combined effects of the independent variables on the response variables in the dotty plots; deal with unlimited number of independent and response variables; consider combined multiple threshold criteria, which is subjective depending on the target of the investigation for response variables; and provide a range of values with their distribution for the optimization.