Extraction optimization and characterization of durian (Durio zibethinus) rind pectin extracted by subcritical water.

The subcritical water extraction (SWE) of pectin from durian rind was optimized using response surface methodology with Box-Behnken experimental design. The FTIR, SEM, and DSC analysis were used to examine the physicochemical, structural, thermal, and functional characteristics of the subcritical water-extracted pectin (SWEP) under optimum conditions and contrasted with the conventional acid-extracted pectin (CAEP). The optimum yield of pectin (5.

Hyperspectral imaging for detection of macronutrients retained in glutinous rice under different drying conditions.

This study detected the macronutrients retained in glutinous rice (GR) under different drying conditions by innovatively applying visible-near infrared hyperspectral imaging coupled with different spectra preprocessing and effective wavelength selection techniques (EWs). Subsequently, predictive models were developed based on processed spectra for the detection of the macronutrients, which include protein content (PC), moisture content (MC), fat content (FC), and ash content (AC). The result shows the raw spectra-based model had a prediction accuracy ( ) of 0.

Optimization of computational intelligence approach for the prediction of glutinous rice dehydration.

Background: Five computational intelligence approaches, namely Gaussian process regression (GPR), artificial neural network (ANN), decision tree (DT), ensemble of trees (EoT) and support vector machine (SVM), were used to describe the evolution of moisture during the dehydration process of glutinous rice. The hyperparameters of the models were optimized with three strategies: Bayesian optimization, grid search and random search. To understand the parameters that facilitate intelligence model adaptation to the dehydration process, global sensitivity analysis (GSA) was used to compute the impact of the input variables on the model output.