Investigation of mass transfer parameters, phytochemical analysis of dried ripen graviola fruit (Annona muricata) and its comparative approach by using statistical tools: ANN and mathematical modelling

Improving the accessibility of bioactive compounds enriched ripen graviola fruit (Annona muricata) by the application of post-harvest processing technology would overcome their climatic barriers and be used as a folk medicine. Therefore, hot air drying technique was applied at various temperatures (40 & DEG;C, 50 & DEG;C and 60 & DEG;C) to evaluate the nutritional efficiency of the medicinal fruit. Drying characteristics of the ripen graviola fruit were determined, and predictive capability of artificial neural network and eight semiempirical models was evaluated. The Weibull model gave satisfactory results over the other models. Levenberg-Marquardt's algorithm along with LOGSIGMIOD transfer function, predicted the moisture content and moisture ratio with better accuracy. Interestingly, the R-2 value of ANN was 0.9999, which was significantly more than that of the semiempirical model. Moisture diffusivity and mass transfer coefficient increased to 4.73 x 10(-6)m(2)/s and 2.386 x 10(-6) m/s, respectively, as the temperature rose. Activation energy proved the conservative requirement of energy and was obtained as 24.659 kJ/mol. Radical scavenging activity (IC 50), polyphenol and flavonoid content were found to be maximum at 60 & DEG;C, and the values were 933.975 & mu;g/ml, 7.088 mg GAE/g, 18.42 mg QE/g, respectively. Fruits dried at 60 & DEG;C showed lower moisture content (8% d.b), lower drying time, higher drying rate, better physico-chemical properties and sustainable colour value. Therefore, drying at 60 & DEG;C was recommended for commercialization in various nutraceutical applications and biotechnology aspects.