Drying temperature-dependent profile of bioactive compounds and prediction of antioxidant capacity of cashew apple pomace using coupled Gaussian Process Regression and Support Vector Regression (GPR-SVR) model

Bobby Shekarau Luka; Taitiya Kenneth Yuguda; Meriem Adnouni; Riyang Zakka; Ibrahim Bako Abdulhamid; Bumbyerga Garboa Gargea

doi:10.1016/j.heliyon.2022.e10461

Drying temperature-dependent profile of bioactive compounds and prediction of antioxidant capacity of cashew apple pomace using coupled Gaussian Process Regression and Support Vector Regression (GPR-SVR) model

Heliyon. 2022 Sep 6;8(9):e10461. doi: 10.1016/j.heliyon.2022.e10461. eCollection 2022 Sep.

Authors

Bobby Shekarau Luka^{1

2}, Taitiya Kenneth Yuguda³, Meriem Adnouni⁴, Riyang Zakka², Ibrahim Bako Abdulhamid⁵, Bumbyerga Garboa Gargea²

Affiliations

¹ Department of Agricultural Engineering, Federal University Wukari, Taraba State, Nigeria.
² Department of Food Science and Technology, Federal University Wukari, Taraba State, Nigeria.
³ College of Environment, Hohai University, Nanjing 210098, China.
⁴ Institution of Refrigeration and Cryogenics, Zhejiang University, Hangzhou, 310027, China.
⁵ Department of Computer Engineering, Federal University Wukari, Taraba State, Nigeria.

Abstract

Crude extracts from cashew apple pomace (CAP) dried at different temperatures were used in High-Pressure Liquid Chromatography to quantify total alkaloids content (TAC), total flavanoids content (TFC), total saponin content (TSC) and total phenolics content (TPC). Diphenyl-1-picrylhydrazyl (DPPH) was used to determine the antioxidant capacity (AOC) of CAP. Fourier-Transformed Infrared Spectroscopy-Attenuated Total Reflectance (FTIR-ATR) was used to identify the functional groups present in the pomace. TAC, TFC, TSC and TPC were used as inputs to model AOC using Gaussian Process Regression (GPR), and Support Vector Regression (SVR) and a coupled model was developed using the residuals of GPR and SVR. It was found that increasing drying temperature decreased TAC, TFC, TPC and AOC but TSC increased. Both GPR and SVR predicted AOC with high accuracy. Drying CAP at lower temperature preserved more bioactive compounds hence high AOC; FTIR-ATR showed that CAP has good hydration capacity and contains majorly inorganic phosphates, aliphatic hydrocarbons and primary alcohols. Model coupling enhanced AOC prediction.

Keywords: Bioactive compounds quantification; Cashew apple pomace; Coupled GPR–SVR; Drying; Gaussian Process Regression modeling; Predicting antioxidant capacity; Support Vector Regression modeling.