Extraction, characterization and quantification of Quinone dye compounds from macadamia and coconut shell- Waste

Abstract

Natural dye compounds are found in most plants and are a potential substitute for synthetic dyes which are less eco-friendly and contribute highly to environmental pollution. Over the years (2016 – 2020) there has been high volumes of coconut and macadamia nutshell waste (an average of about 16.4Kt and 29.5Kt respectively) produced in Kenya, which is a potential source of natural dyes, such as the quinone-based type. However, studies on quinone dyes are still scanty and yet they have good fastness properties even without use of mordants. The main objective of this study was to extract, characterize, and quantify quinone colorants from macadamia and coconut shells. Specific objectives were to; map coconut and macadamia nut waste in Kenya, extract quinone compounds and optimize extraction process, and characterize and quantify quinone compounds. The methodology used involved size reduction of shells into small particles (<1mm) using a grinder, reflux extraction at 80 using ethanol solvent and a liquor ratio of 1:10. A two-factor, five-level Central Composite Design was used for the optimization of time and solvent ratio. Ultraviolet-visible spectroscopy and Fourier- transform infrared spectroscopy were used for characterization, while 1,3- Dimethylbarbituric acid (DMB) and Magnesium acetate (MgAc) were the derivatizing agents used for quantification. The data gathered from literature revealed that the average annual shell waste generated in Kenya from 2016 to 2020 was 15.9 Kt for coconut and 33.4 Kt for macadamia. The regression models for MNS optimization gave yield of 6.69 % with R 2 = 0.8801, p <0.05, optimal time of 180 minutes and solvent ratio of 75 %; while Total phenolic content (TPC) was 245.21 mg/L with R 2 = 0.8550, p <0.05, optimal time of 180 minutes and solvent ratio of 75 %. R 2 and p values show that both yield and TPC increases with time and solvent ratio. CNS optimization gave yield of 3.77 % with R 2 = 0.3515, p <0.05, and optimal time of 180 minutes, showing less significance of time on yield. TPC for CNS was 394.09 mg/L with R 2 = 0.8190, p <0.05, optimal solvent ratio of 75%. This shows that TPC increases with increase in solvent ratio. Quinones and anthraquinones were detected in both extracts. Significant concentrations of benzoquinone (25.0 µg/ml from CNS, 34.0 µg/ml from MNS) were detected using DMB derivatization with Limit of Detection (LOD) of 0.78 µg/ml and Limit of Quantification (LOQ) of 2.4 µg/ml, while anthraquinone concentrations were 18.09 µg/mL from CNS and 15.23 µg/ml from MNS, with a higher LOQ of 18.70 µg/ml. In conclusion, it was established from the results of the study that there are large quantities of MNS and CNS wastes in Kenya with potential for value addition and that CNS and MNS contain more benzoquinones than anthraquinones. Further work should study the effects of other solvents on extraction, since solvent ratio indicated a more significant effect on TPC than time. Also, the feasibility of more advanced extraction techniques which require low heat should be considered to compare operating costs with that of reflux extraction.