Boiling Point, Specific Heat and Density Measurements and Modeling of Soybean Molasses and Its Aqueous Solutions

Factors influencing the enzymatic hydrolysis of soy molasses into fermentation feedstock

Soybean processing generates huge amounts of soy molasses that can support biorefinery but require development of waste-to-value conversion technologies. Here, soy molasses processing by Aspergillus niger enzymes was studied to optimize the conversion of oligosaccharides to monomeric sugars as ready fermentation feedstock. The effects of pH and temperature were first investigated using fixed enzyme composition and loading. pH, in the tested 3.0-6.5 range, significantly affected hydrolysis particularly in galactose release. The hydrolysis was fastest at pH 4.8 and 60 °C although the 48-h sugar (glucose, fructose, and galactose) yields were similar at pH 4.8 and 5.7, and 50 and 60 °C. Study was next made at these favorable pH and temperatures using different enzyme compositions and loadings. Glucose and fructose were effectively released, reaching ∼100 % yields in 24-48 h by most of the enzymes and loadings evaluated. Galactose production was less effective and varied significantly with the pH-temperature condition and enzyme loading and composition. Mechanistic evaluation suggested formation and accumulation of galactose disaccharide, whose slow hydrolysis was rate-limiting in the systems with complete glucose and fructose releases but low galactose yields. Model equations were developed to describe the kinetic sugar-release profiles and make technoeconomic analysis, which showed that a process of lower enzyme loading, while requiring longer duration, is more economical within the analyzed range of 5-50 (U α-galactosidase/g molasses). With 5 (U/g) loading, the total cost is about 30 % lower at 60 °C-pH 5.7 than 50 °C-pH 4.8. The α-galactosidase-to-sucrase ratio plays a less significant role in affecting the overall process cost.

Thermal physical properties of the golden pomfret at low temperatures

Food thermal properties are essential for calculating freezing time and analyzing energy cost during food freezing or thawing. However, there are currently few data or models of physical properties for foods below −40 °C (e.g., thermal conductivity of food at lower temperatures are lacked due to limitations of device testing below −40 °C). In this paper, the thermophysical parameters of golden pomfret were tested in the temperature range from −100 °C to room temperature. The freezing point was determined. The specific heat and enthalpy of golden pomfret were measured by using a DSC, and the thermal conductivity was measured by a novel self-designed device cooled by a pulse tube cryocooler that can give low temperatures to −253 °C. Finally, the temperature profile obtained by numerical calculation was consistent with experimental results, which proves that predicted models of thermal physical properties in this work will provide reliable data support for the cryogenic freezing of food.