Influence of Different Pretreatments on Hot air and Microwave-Hot Air Combined Drying of White Sweet Cherry

Şimşek, Meriç; Süfer, Özge

doi:10.24925/turjaf.v9i6.1172-1179.4455

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…The highest value of the D eff was obtained in the MW‐CV dryer. Similar findings were reported by Çetin (2022c), Simsek and Süfer (2021), and Zhu et al (2022).…”

Section: Resultssupporting

confidence: 89%

Machine learning approaches for estimating apricot drying characteristics in various advanced and conventional dryers

Kaveh,

Çetin,

Khalife

et al. 2023

J Food Process Engineering

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Drying plays a crucial role in preserving the quality of agricultural products. Nevertheless, suboptimal conditions in drying systems have an adverse effect on drying characteristics and energy efficiency. Machine learning approaches are innovative and reliable that have been successfully used to solve such challenges and achieve optimization in drying processes. In this study, five machine learning approaches (multilayer perceptron [MLP], gaussian processes [GP], support vector regression [SVR], k‐nearest neighbors [kN], and random forest [RF]) were used to estimate moisture content and moisture ratio of apricot in five various dryers (convective [CV], microwave [MW], infrared [IR], microwave‐convective [MW‐CV], and infrared‐convective [IR‐CV]). Also, the values of specific energy consumption (SEC) and effective moisture diffusivity (Deff) were calculated in these dryers. Accordingly, the best result of the Deff (3.14 × 10−10 m2/s) and the minimum value of the drying time (130 min) and SEC (18.67 MJ/kg) were obtained using MW‐CV hybrid dryer. While the lowest values of Deff (2.09 × 10−11 m2/s) and highest drying time (18.5 h) and SEC (209.34 MJ/kg) were detected in CV dryer at 50°C. The best correlation coefficients (R) for the estimation of moisture content were gained using RF technique for k‐fold cross validation and train‐test split with the values of 0.9908 and 0.9912, respectively. Moreover, moisture ratio results showed that the MLP achieved the highest R value over 0.9985 for both validation methodologies. In the discrimination of the drying methods, the MLP had the greatest accuracy as 82.00% and 86.00% for k‐fold cross validation and train‐test split, respectively. The results showed that the RF and ML models could potentially be used for estimation and discrimination for drying applications.Practical ApplicationsRecently, there has been an increased interest in healthy food choices such as foodstuffs, snacks, and dried products. This trend has captured the attention of both dietitians and conscious consumers. Apricots are a prime example of a valuable dried product that can be dry in various conditions. Machine learning techniques can be used for rapid and non‐destructive determination of drying characteristics and such techniques yield objective and accurate results. Present findings revealed that texture machine learning models could be used as an effective and reliable discrimination tool for dried products.

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“…The highest value of the D eff was obtained in the MW‐CV dryer. Similar findings were reported by Çetin (2022c), Simsek and Süfer (2021), and Zhu et al (2022).…”

Section: Resultssupporting

confidence: 89%

Machine learning approaches for estimating apricot drying characteristics in various advanced and conventional dryers

Kaveh,

Çetin,

Khalife

et al. 2023

J Food Process Engineering

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“…Their results showed that the minimum drying time (180 min) and the maximum D eff value (2.4 × 10 −9 m 2 /s) were obtained with freezing pretreatment, respectively. In another study, Simsek and Süfer ( 2021b ) examined the impacts of various pretreatments on combined hot air and microwave hot air drying of white SC. Their results confirm that the D eff value of white SC ranges from 1.7 × 10 −10 to 5.2 × 10 −10 m 2 /s in hot air drying and from 4.3 × 10 −10 to 1.8 × 10 −9 m 2 /s in microwave hot air drying.…”

Section: Resultsmentioning

confidence: 99%

“…The results of Simsek and Süfer ( 2021a ) confirmed that the freezing pretreatment improved the total phenolic content (4180 ± 0.86 μg GAE/g dry matter) and antioxidant capacity of dried white SC, as compared to control and other pretreatment methods. In another study, Simsek and Süfer ( 2021b ) examined the impacts of various pretreatments on combined hot air and hot air‐microwave drying of white SC. Their results confirmed that the total phenolic content of freezing pretreated and hot air dried at 50°C and hot air dried at 70°C control samples were 1481 and 6181 μg GAE/g, respectively.…”

Section: Resultsmentioning

confidence: 99%

Influence of microwave pretreatment on the total phenolics, antioxidant activity, moisture diffusivity, and rehydration rate of dried sweet cherry

Salehi,

Inanloodoghouz,

Ghazvineh

2023

Food Science & Nutrition

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The target of this work was to investigate the influence of microwave pretreatments (at five levels of 0, 30, 60, 90, and 120 s) on the total phenolics content, antioxidant potential, mass transfer rate, effective moisture diffusivity (Deff), and rehydration rate of sweet cherries (SC). The drying duration of microwave‐treated SC was shorter than the untreated sample. The average drying time of fresh SC microwaved for 0, 30, 60, 90, and 120 s were 220, 205, 190, 175, and 150 min, respectively. The Deff values, total phenolics, and antioxidant capacity of microwave‐treated SC were higher than the untreated sample. In this study, the SC Deff as determined by the second Fick law varied from 8.73 × 10−10 to 1.41 × 10−9 m2/s. The experimental data for the dehydration curves were fitted to different thin‐layer equations, and the Midilli equation using the experimental constants best described the drying rate of SC. As the microwave pretreatment time increased from 0 to 120 s, the total phenolics and antioxidant capacity of dried SC increased from 1491.4 μg Gallic acid equivalents (GAE)/g dry to 2272.1 μg GAE/g dry, and 54.47%–62.59% (p < .05). The microwave pretreatment enhanced the rehydration rate of dried SC. The rehydration percent of dried SC microwaved for 0, 30, 60, 90, and 120 s were 127.27%, 136.63%, 136.91%, 137.07%, and 136.72%, respectively.

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“…According to Siuci ńska et al [25], an ultrasound application during the osmotic pretreatment can result in a decrease in anthocyanin content and accelerate the loss of the antioxidant potential of stored convectively dried sour cherries. Simsek and Süfer [26] reported a reduced time for the microwave-hot air drying of white sweet cherries as a result of using 10% citric acid, 60% sucrose solutions, or a freezing pretreatment. In addition to osmotic dehydration, other pretreatment techniques can be used for sour cherries.…”

Section: Discussionmentioning

confidence: 99%

The Quality Assessment of Sour Cherries Dried Using an Innovative Simultaneous Osmotic–Microwave–Vacuum Approach Based on Image Textures, Color Parameters, and Sensory Attributes

Ropelewska,

Konopacka,

Piecko

2023

Agriculture

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Sour cherries are a perishable raw material, and their preservation is needed to extend their availability to consumers. Improving drying techniques is desirable to ensure the highest quality of products. This study aimed to determine image textures from color channels R, G, B, L, a, b, X, Y, and Z; color parameters L*, a*, and b*; the color difference (ΔE) of raw materials and dried fruit; and the sensory attributes of dried sour cherry products prepared using an innovative approach. Three sour cherry cultivars, ‘Nefris’, ‘Debreceni Botermo’, and ‘Łutówka’, were used in the experiment. Sour cherries were subjected to freezing and pit removal before drying. The simultaneous osmotic–microwave–vacuum drying was carried out in one process lasting an hour and combining osmotic dehydration using a 40 °Bx sucrose solution and microwave–vacuum drying at microwave powers of 100 W for 900 s, 300 W for 900 s, 250 W for 900 s, and 0 W for stabilization for 900 s and a pressure of 30 ± 2 hPa. After drying, the quality assessment of products was performed using non-destructive image analysis and color measurements, as well as sensory analysis, including non-destructively and destructively assessed attributes. The highest changes in textures occurred for the GHMean (histogram’s mean for color channel G) (from 30.69 to 22.64) and LHMean (histogram’s mean for color channel L) (from 66.93 to 59.07) of images of the cultivar ‘Łutówka’, and the smallest changes were found for the cultivar ‘Nefris’. Drying had a statistically significant effect on the color parameters of the ‘Debreceni Botermo’ and ‘Łutówka’ sour cherries. The value of ΔE was the highest (10.44) for ‘Debreceni Botermo’ and the smallest (1.98) for ‘Nefris’. All cultivars of dried sour cherries had very high values of overall quality, reaching 8.9 for ‘Nefris’ and ‘Debreceni Botermo’ and 8.8 for ‘Łutówka’. The ‘Nefris’ sour cherry was characterized by the highest value of flavor of 9.0. All dried samples were attractive in terms of their external appearance. The sensory parameters related to taste, texture, and crunchiness were also satisfactory. Innovative simultaneous osmotic–microwave–vacuum drying allowed for the obtainment of dried sour cherries with a high quality, including acceptable sensory attributes.

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Influence of Different Pretreatments on Hot air and Microwave-Hot Air Combined Drying of White Sweet Cherry

Cited by 5 publications

References 36 publications

Machine learning approaches for estimating apricot drying characteristics in various advanced and conventional dryers

Machine learning approaches for estimating apricot drying characteristics in various advanced and conventional dryers

Influence of microwave pretreatment on the total phenolics, antioxidant activity, moisture diffusivity, and rehydration rate of dried sweet cherry

The Quality Assessment of Sour Cherries Dried Using an Innovative Simultaneous Osmotic–Microwave–Vacuum Approach Based on Image Textures, Color Parameters, and Sensory Attributes

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