Revalorization of coffee husk: Modeling and optimizing the green sustainable extraction of phenolic compounds

This study aimed to model and optimize a green sustainable extraction method of phenolic compounds from the coffee husk. Response surface methodology (RSM) and artificial neural networks (ANNs) were used to model the impact of extraction variables (temperature, time, acidity, and solid-to-liquid ratio) on the recovery of phenolic compounds. All responses were fitted to the RSM and ANN model, which revealed high estimation capabilities. The main factors affecting phenolic extraction were temperature, followed by solid-to-liquid ratio, and acidity. The optimal extraction conditions were 100◦C, 90 min, 0% citric acid, and 0.02 g coffee husk mL−1 . Under these conditions, experimental values for total phenolic compounds, flavonoids, flavanols, proanthocyanidins, phenolic acids, o-diphenols, and in vitro antioxidant capacity matched with predicted ones, therefore, validating the model. The presence of chlorogenic, protocatechuic, caffeic, and gallic acids and kaemferol-3-O-galactoside was confirmed by UPLC-ESI-MS/MS. The phenolic aqueous extracts from the coffee husk could be used as sustainable food ingredients and nutraceutical productsThis research was funded by the Spanish Ministry of Science and Innovation, SUSCOFFEE (grant number AGL2014–57239-R), COCARDIOLAC (grant number RTI 2018-097504-B-I00) projects, and the Community of Madrid and UAM Agreement (2019–2023). M. Rebollo-Hernanz thanks to the FPU program of the Ministry of Universities for his predoctoral fellowship (grant number FPU15/04238