Abstract
Cottonseed is one of the important by-products of the cotton crop. Researchers claim that cottonseed with less than 0.45% of gossypol is quite good for human consumption and animal feeding because it is a rich source of protein, edible oil, and energy. Total and free gossypols are the influencing parameters that reduce the edible nature of the cottonseed. In the present work, multiple quadratic regression models have been prepared to predict the reduction in the free and total gossypol percent. This response surface method (RSM)-based approach was applied to investigate the combined effect between input parameters such as acetone level, time of extraction, liquid-to-solid ratio (LSR), and the number of extraction cycles, whereas output responses are free and total gossypol reduction percentage. Analysis of Variance (ANOVA) has been performed to determine the highly significant parameter. The optimum combination of input parameters was determined using the RSM-based desirability approach, and confirmatory experiments were performed to validate the combination. Results revealed that the number of extraction cycles and liquid-to-solid ratio significantly affects the reduction of free and total gossypol levels. The values of r-square were found above 0.9, which indicates that the developed models are suitable and reliable for predicting free and total gossypol reduction percentage.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
11 articles.
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