Evaluation of different hydrocolloids and drying temperatures in the drying kinetics, modeling, color, and texture profile of murta (Ugni molinae Turcz) berry leather

Abstract

The aim of this study is to describe the drying kinetics of a murta (Ugni molinae Turcz) berry purée to obtain a fruit leather through mathematical model and determine the effect of different hydrocolloids on the mass diffusion coefficient, activation energy, surface color, and texture profile at different drying temperatures. Three hydrocolloids were used: 1% gelatin, 0.2% carrageenan, and 4% starch at three process temperatures: 50, 60, and 70 C and a formulation without hydrocolloid as control. The hydrocolloids and process temperature influenced the drying time. The mass diffusion coefficient varied depending on the process temperature and hydrocolloids with values between 1.2665 × 10 −10 m 2 s −1 and 4.5341 × 10 −10 m 2 s −1 . The Midilli & Kucuk model had a better fit to experimental values. A MANOVA indicated that hydrocolloids and process temperature had a significant effect on color and texture of fruit leather. The process temperature and concentration of hydrocolloids are important factors for drying process design. Practical ApplicationsFruit leather is a low humidity product and stable at room temperature. It can be made with surpluses, discards, or mixtures of fruits, being a new alternative of preservation and healthy consumption. The murta berry is a stationary fruit with antioxidant properties hardly been explored at an industrial level and fruit leathers can be a novel production alternative. Hydrocolloids have gelling and stabilizing characteristics. For this reason, they are used to improve the formation of fruit leathers, although it is necessary to know their effects on physical characteristics as color and texture of the final product. These features are important for consumers' purchasing decision. The convective drying process parameters for fruit leather production as: moisture content, diffusion coefficient, and activation energy can be determined by mathematical modeling. The knowledge of these parameters is important for drying process designs.

Heat and mass transport analysis of the drying of freshwater fishes by a forced convective air‐dryer

“…Verma model is another kind of exponential model with two terms. Midilli model has a log-log relationship combined with a linear part, which satisfies the drying kinetics as reported in many studies (Gómez-Pérez, Navarrete, Moraga, Rodríguez, & Vega-Gálvez, 2020). It can be observed from (Claumann et al, 2018).…”

Processing of minerals and anthocyanins‐rich mixed‐fruit leather from banana ( Musa acuminata ) and sohiong ( Prunus nepalensis )

“…The hardness of the optimized leather was 522.447 N, and it gradually decreased with increase in MD content up to 259.758 N which may be due to the ability of MD to absorb water within its branched structure. Similar result was reported by García-García et al (2019) and Gómez-Pérez et al (2020) for leather containing higher molecular weight sugar. Addition of 1.5% maltodextrin increased gumminess, springiness, chewiness, and cohesiveness, but with further addition there was decrease in the values, probably due to dilution effect.…”

“…Similarly, for 5 cm thick leather, Modified Page model with highest R 2 value (0.9881) and lowest RMSE (0.03495) (Figure 2b) was found to be the best among all the models. Although the thickness of the leather was different, the prediction of the model remained the same, that is, the same model can be used for the best prediction of a particular product irrespective of thickness, which was also observed by Gojiya and Vyas (2015).…”

“…The texture profile of mixed fruit leather was measured according to Gómez-Pérez et al (2020) with some modification using a Texture Analyzer (TAHD, Stable Micro systems, UK). Textural properties were expressed in terms of hardness, springiness, cohesiveness, gumminess, and chewiness.…”

“…In order to do the prediction of drying kinetics of mixed fruits leather, it is very essential to accurately model its drying behavior. Various mathematical models have already been used to describe the drying characteristics of agricultural products (Avhad & Marchetti, 2016;Dhanushkodi et al, 2017;Gómez-Pérez et al, 2020).…”