Artificial neural network approach for protection of the color of dried golden and pink oyster mushrooms with pretreatments

Abstract

AbstractIn this study, the possibilities of protecting the color of dried golden and pink mushrooms were investigated, and color parameters of dried mushrooms were modeled by artificial neural network (ANN). For this purpose, first, the golden oyster mushroom (Pleurotus citrinopileatus) and pink oyster mushroom (Pleurotus djamor) were cultivated. Then, pretreatments were applied using citric acid (CA) and potassium metabisulfite (KMS) with different rates (0.5%, 1.0%, and 1.5%) separately, excluding control group mushrooms. All mushrooms were dried for 330 minutes in a laboratory type oven at two different temperatures (40°C and 50°C) until completely dehydrated. Colorimetric values (L*, a*, and b*) were determined using Konica Minolta CM‐2600d spectrophotometer for 30 minute intervals during the drying process. The obtained data were modeled using the ANN technique. The results show that darkening of mushrooms increased as the drying temperature increased. CA and KMS showed better results for dried golden and pink mushrooms, respectively. Thanks to the pretreatment, the mushroom's original color was protected compared with control samples. All mean absolute percentage error values of models were determined, which were lower than 4.0%. It was concluded that ANN can be a good way to predict the color of dried golden and pink mushrooms (pretreated or not) with a high degree of accuracy.