Study on Flammulina Velutipes Ready‐to‐Eat Snacks Prepared by Microwave Vacuum Osmotic Dehydration Combined with Hot‐Air Drying

Abstract

Flammulina velutipes ready‐to‐eat snacks are not commonly known. Response surface methodology was employed to optimize the process parameters in making ready‐to‐eat snacks. The optimum dehydration condition was found at a sucrose concentration of 30%, a vacuum pressure of −40 ± 1.5 kPa, an osmotic time of 165 s and a microwave intensity of 65 W/g. These parameters resulted in water loss, solid gain and sensory evaluation values of 39.15%, 6.96% and 7.87, respectively. The water diffusion rate and solid gain diffusion rate were 1.55 × 10−9 and 1.29 × 10−9 m2/s, respectively, when employing the optimum microwave vacuum osmotic dehydration (MVOD) parameters. When F. velutipes mushrooms were dried for 180 min by hot‐air drying, the water content of the ready‐to‐eat snack was 9.8 ± 0.5% and the water diffusion rate was 1.14 × 10−11 m2/s. Both the MVOD and the hot‐air drying stages were consistent with the Page model. Practical Applications Osmotic dehydration technology combined with other drying technologies, such as hot air, can improve the use value and economic benefits of fruits and vegetables. The two correlations developed by modifying second‐order polynomial equations were adequate to predict the responses for the Flammulina velutipes samples. The water and solid effective diffusion rates were calculated at different microwave vacuum osmotic dehydration times and different hot‐air drying times for F. velutipes mushrooms. The Page model could be used to illustrate the water loss and solid gain for these two drying stages. The F. velutipes mushroom snacks made using these conditions had good color, high gloss and a moderately soft texture, with a sweet and sour flavor. The developed mathematical models can be considered precise for the prediction and optimization of process parameters in experimental and industrial applications.

Evaluation and modelling of osmotic pre‐treatment of peach using alternative agents in a multiple‐component solution

“…A second‐degree polynomial model was chosen for the description of the response variables Y (WL, SG, a w , colour/Δ E , texture/hardness) as a function of the factor variables X i (glycerol concentration in osmotic solution, C glycerol = 40, 50, 60% w/w; OD temperature, T = 25, 35, 45 °C; OD time, t = 5–240 min): …”

“…From the experimental results, model coefficients were calculated by nonlinear regression using SYSTAT 12 (Systat Software, UK). The variables present in linear terms represent the coordinates of the maximum value predicted, those in quadratic terms represent the surface curvature, and the bi‐factorial cross‐products represent the directions of the axes of the geometric figure obtained by sectioning the surface area . In general, a positive value of the equation coefficient represents an effect which promotes the response, while a negative value indicates an inverse relationship between the factor and response.…”

“…The variables present in linear terms represent the coordinates of the maximum value predicted, those in quadratic terms represent the surface curvature, and the bi-factorial cross-products represent the directions of the axes of the geometric figure obtained by sectioning the surface area. [30][31][32] In general, a positive value of the equation coefficient represents an effect which promotes the response, while a negative value indicates an inverse relationship between the factor and response. The quality of these models and their predictive power are closely dependent on the coefficients of variance.…”