Production of Protein Hydrolysate from Quinoa (Chenopodium quinoa Willd.): Economic and Experimental Evaluation of Two Pretreatments Using Supercritical Fluids' Extraction and Conventional Solvent Extraction.

Supercritical fluids' extraction (SFE) and conventional solvent extraction (CSE) for defatting of quinoa flour as pretreatments to produce the quinoa protein hydrolysate (QPH) were studied. The objective was to extract the oil and separate the phenolic compounds (PC) and the defatted quinoa flour for subsequent quinoa protein extraction and enzymatic hydrolysis. The oil extraction yield (OEY), total flavonoid content (TFC), and QPH yield were compared. SuperPro Designer 9.0® software was used to estimate the cost of manufacturing (COM), productivity, and net present value (NPV) on laboratory and industrial scales. SFE allows higher OEY and separation of PC. The SFE oil showed a higher OEY (99.70%), higher antioxidant activity (34.28 mg GAE/100 g), higher QPH yield (197.12%), lower COM (US$ 90.10/kg), and higher NPV (US$ 205,006,000) as compared to CSE (with 77.59%, 160.52%, US$ 109.29/kg, and US$ 28,159,000, respectively). The sensitivity analysis showed that the sale of by-products improves the economic results: at the industrial scale, no significant differences were found, and both processes are economically feasible. However, results indicate that SFE allows the recovery of an oil and QPH of better nutritional quality and a high level of purity-free organic solvents for further health and nutraceutical uses.

Modeling LED street lighting.

LED luminaires may deliver precise illumination patterns to control light pollution, comfort, visibility, and light utilization efficiency. Here, we provide simple equations to determine how the light distributes in the streets. In particular, we model the illuminance spatial distribution as a function of Cartesian coordinates on a floor, road, or street. The equations show explicit dependence on the luminary position (pole height and arm length), luminary angle (fixture tilt), and the angular intensity profile (radiation pattern) of the LED luminary. To achieve this, we propose two mathematical representations to model the sophisticated intensity profiles of LED luminaries. Furthermore, we model the light utilization efficiency, illumination uniformity, and veiling luminance of glare due to one or several LED streetlamps.