Characterization of Volatile Flavor Compounds in Supercritical Fluid Separated and Identified in Gurum (Citrulluslanatus Var. colocynthoide) Seed Oil Using HSME and GC–MS

In this study, the volatile compound profiles of gurum seed oil were determined using two methods: supercritical CO₂ extraction (SFE) and the screw press process (SPP). For volatile compounds extraction and identification, headspace solid-phase micro-extraction (HS-SPME) and GC–MS were used, respectively. A total number of 56 volatile compounds were revealed and identified in oil extracted by SFE, while only 40 compounds were detected in extracted oil by SPP. Acids, aldehydes, esters, ketones, furans, and other components were present in the highest ratio in oil extracted by SFE. In contrast, alcohols and alkenes were found in the highest proportion in oil extracted by SPP. In this study, it was observed that SFE showed an increase in the amounts of volatile compounds and favorably impacted the aroma of gurum seed oil. The results reveal that different extraction methods significantly impact the volatile components of gurum seed oil, and this study can help evaluate the quality of the oil extracted from gurum seeds.     

Mathematical model for the novel coronavirus (2019-nCOV) with clinical data using fractional operator

Coronavirus infection (COVID-19) is a considerably dangerous disease with a high demise rate around the world. There is no known vaccination or medicine until our time because the unknown aspects of the virus are more significant than our theoretical and experimental knowledge. One of the most effective strategies for comprehending and controlling the spread of this epidemic is to model it using a powerful mathematical model. However, mathematical modeling with a fractional operator can provide explanations for the disease's possibility and severity. Accordingly, basic information will be provided to identify the kind of measure and intrusion that will be required to control the disease's progress. In this study, we propose using a fractional-order SEIARPQ model with the Caputo sense to model the coronavirus (COVID-19) pandemic, which has never been done before in the literature. The stability analysis, existence, uniqueness theorems, and numerical solutions of such a model are displayed. All results were numerically simulated using MATLAB programming. The current study supports the applicability and influence of fractional operators on real-world problems.