Optimization of microwave extraction of biocompounds from black pepper using meat quality assessment

Abstract

Black pepper (Piper nigrum) is a plant highly valued for its functional aromatic compounds. To increase bioavailability of its phytochemicals, a novel approach to extraction using microwave heating and optimization was investigated. Fixed (microwave power and particle size) and variable (heating time and solvent volume) extraction criteria were applied to obtain aqueous extracts, followed by the optimization of the quality of extracts by subjecting the extracts to meat quality test using the central composite design. Thereafter, quality indices (pH, 2-thiobarbituric acid reactive substance value, refrigeration loss, colour and cooking loss) of meat subjected to storage were determined and the outcomes were analysed using response surface methodology. A total of six optimised solutions were derived but the best extraction criteria (variable) were 87.28 min and 364.26 mL of heating time and solvent volume respectively with a desirability value of 0.624, while microwave power and particle size were kept constant. Afterwards, selected optimised extraction criteria was applied, and black pepper aqueous extract obtained was compositionally analysed using Gas Chromatography Mass Spectrometry. Remarkably, a total of 71 compounds were extracted, comprising element-based compounds such as silicon, nitrogen, sulphur and iodine. Two silicon and nitrogen-based compounds as well as one sulphur and nitrogen-sulphur based compound were obtained while seven iodine-based compounds were discovered alongside other functional compounds. This approach results in green and efficient extraction process with increased bioavailability of functional compounds. However, further modifications of extraction criteria can be applied to upscale the desirability level (score) for increased extraction efficiency.

IMPLICATIONS OF BUTYLATED HYDROXYTOLUENE AND OPTIMIZED Piper nigrum EXTRACTS APPLICATION ON QUALITY OF STORED PORK

“…Extraction parameters were generated by modifying production constraints from data provided [Adegoke et al (2023); submitted data] by Design Expert Software. Post-upscale of previous data, 97% desirability was achieved after setting the following targets.…”