Real-time monitoring of color variations of apple slices and effects of pre-treatment and drying air temperature

Effect of drying temperature and storage time on the crispiness of homemade apple snacks

BACKGROUND

The apple (Malus domestica Borkh.) plays an important role in the trendy market of dried snacks because of its exceptional flavor and texture. In addition to the health benefits, there is also a general disposition to consume organic and do-it-yourself products.

RESULTS

Three different drying temperatures, 65, 75, and 85 °C, were tested using a commercial ventilated drying oven in 'Royal Gala' and 'Golden Delicious' cultivars. Physical changes, including texture, color, shrinkage ratio, and microstructure, were evaluated for the temperatures and cultivars considered. Based on the results, particularly in terms of shrinkage, hardness, and crispiness, a drying temperature of 75 °C was selected to perform texture profile analyses throughout the drying period. Storability conditions were evaluated to determine the best moment to maintain the physical properties of the dried snacks during storage. Considered the more important property related to consumer preferences, crispiness was followed with puncture tests.

CONCLUSION

The storage of apple chips, dried at the various temperatures, that must be performed in 5-10 min after removing from the drying oven, was assessed over the course of a month. Both the drying process and the subsequent storage proved effective in preserving the desired texture of the apple snacks, regardless of the specific cultivar or drying temperature used. Through this study, with a refined understanding of the changes occurring during the drying process and the optimization of storage conditions, we can confidently offer consumers the best combination of crispy and healthy snacks that meet their expectations. © 2023 Society of Chemical Industry.

Mathematical Description of Changes of Dried Apple Characteristics during Their Rehydration

The mathematical description of changes of dried apples characteristics (mass gain, volume increase, dry matter loss, rehydration indices, and colour) during their rehydration was performed. The effect of conditions of both processes on model parameters were also considered. Apple slices (3 and 10 mm) and cubes (10 mm) were dried in natural convection (drying air velocity 0.01 m/s), forced convection (0.5 and 2 m/s), and fluidisation (6 m/s). Drying air temperatures (Td) were equal to 50, 60, and 70 °C. The rehydration process was carried out in distilled water at the temperatures (Tr) of 20, 45, 70, and 95 °C. Mass gain, volume increase, and dry matter loss were modelled using the following empirical models: Peleg, Pilosof–Boquet–Batholomai, Singh and Kulshrestha, Lewis (Newton), Henderson–Pabis, Page, and modified Page. Colour changes were described through applying the first-order model. Artificial neural networks (feedforward multilayer perceptron) were applied to make the rehydration indices and colour variations (ΔE) dependent on characteristic dimension, Td, drying air velocity, and Tr. The Page and the modified Page models can be considered to be the most appropriate in order to characterise the mass gain (RMSE = 0.0143–0.0619) and the volume increase (RMSE = 0.0142–0.1130), whereas the Peleg, Pilosof–Bouquet–Batholomai, and Singh and Kulshrestha models were found to be the most appropriate to characterise dry matter loss (RMSE = 0.0116–0.0454). The ANNs described rehydration indices and ΔE satisfactorily (RMSE = 0.0567–0.0802). Both considered process conditions influenced (although in different degree) the changes of the considered dried apple characteristics during their rehydration.

Effect of Variety on Rehydration Characteristics of Dried Apples

The effect of dried apple varieties on their rehydration characteristics was investigated. Four varieties of apples, Champion, Cortland, Grey Reinette and Ligol, were taken into consideration. Rehydration properties and color of apples were investigated. In order to examine the influence of apple variety on its rehydration properties, the process of rehydration was modeled. The model parameters obtained for investigated apple varieties were compared. Apple cubes were dried in a tunnel dryer (air temperature 60 °C and air velocity 2 m/s) and next rehydrated in distilled water at temperature: 20, 45 and 70 °C. Mass, dry matter mass, volume and color attributes of apples (raw, dried and rehydrated) were measured. The process of rehydration was modeled using empirical (Peleg and Weibull models) and theoretical (the Fick’s second law) models. Results of the analysis showed that the apple variety affects values of mass and volume increase, dry matter decrease and color of the rehydrated apple. Discussed parameters were also affected by rehydration temperature. Fick’s second law model can be considered as the most appropriate. Apple variety and rehydration temperature influenced the values of the model’s constants. Obtained values enabled attempts of the explanation of the rehydration course. It can be stated that apple var. Champion showed a greater rate of water absorption during the entire process of rehydration than other investigated varieties.

Recent developments of artificial intelligence in drying of fresh food: A review

Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena. This article presents a comprehensive review on intelligent drying technologies and their applications. The paper starts with the introduction of basic theoretical knowledge of ANN, fuzzy logic and expert system. Then, we summarize the AI application of modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physiochemical properties of dried products in artificial biomimetic technology (electronic nose, computer vision) and different conventional drying technologies. Furthermore, opportunities and limitations of AI technique in drying are also outlined to provide more ideas for researchers in this area.

Optimal pretreatment determination of kiwifruit drying via online monitoring

BACKGROUND

Pre-treating is a crucial stage of drying process. The best pretreatment for hot air drying of kiwifruit was investigated using a computer vision system (CVS), for online monitoring of drying attributes including drying time, colour changes and shrinkage, as decision criteria and using clustering method. Slices were dried at 70 °C with hot water blanching (HWB), steam blanching (SB), infrared blanching (IR) and acid ascorbic 1% w/w (AA) as pretreatments each with three durations of 5, 10 and 15 min.

RESULTS

The results showed that the cells in HWB-pretreated samples stretched without any cell wall rupture, while the highest damage was observed in AA-pretreated kiwifruit microstructure. Increasing duration of AA and HWB significantly lengthened the drying time while SB showed opposite results. The drying rate had a profound effect on the progression of the shrinkage. The total colour change of pretreated samples was higher than those with no pretreatment except for AA and HWB. The AA could well prevent colour change during the initial stage of drying. Among all pretreatments, SB and IR had the highest colour changes.

CONCLUSION

HWB with a duration of 5 min is the optimum pretreatment method for kiwifruit drying. © 2016 Society of Chemical Industry.