Mathematical modeling of nutritional, color, texture, and microbial activity changes in fruit and vegetables during drying: A critical review

Tuly, S.S.; Mahiuddin,; Karim, Azharul

doi:10.1080/10408398.2021.1969533

Cited by 23 publications

(6 citation statements)

References 182 publications

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“…Table 2 shows the activation energy at all thicknesses examined. The E a ranged between 19.02 and 29.83 kJ/mol under various experimental conditions, which is within the acceptable range of activation energy for the majority of goods (12.7–110 kJ/mol) (Tuly et al., 2023). At every level of infrared radiation magnitude, activation energy values rose as airflow velocity surged between 0.5 and 1.5 m/s.…”

Section: Resultsmentioning

confidence: 61%

A study into how thickness, infrared intensity, and airflow affect drying kinetics, modeling, activation energy, and quality attributes of apple slices using infrared dryer

El‐Mesery,

Hu,

Ashiagbor

et al. 2024

Journal of Food Science

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Drying is a widely recognized process that reduces the need for storage and shipping weight, keeps free water out of the product, and prolongs its shelf life. An infrared dryer was designed to dry apples under different drying conditions. Apple slices of 6‐, 4‐, and 2‐mm thicknesses were dried at intensities 0.130, 0.225, and 0.341 W/cm2 and airflow 1.0, 0.5, and 1.5 m/s. The dehydrating period was prolonged with higher airflow and shortened with higher infrared intensity (IR). The shortest dehydrating period was verified by 190 min at 0.341 W/cm2, 0.5 m/s under 2 mm thickness. Increasing the sample thickness from 2 to 4 mm and then to 6 mm resulted in an 84% and 192% increase in drying time, respectively. Dehydrated apples had water activity values ranging from 0.30 to 0.40. The shrinkage ratio increased with an increase in infrared radiation intensity. However, it decreased with an increase in air velocity, while the rehydration ratio decreased with an increase in radiation intensity and increased with an increase in air velocity. Regarding total color change, apple slice thickness was a major factor. The effective diffusivities varied between 2.6 and 9.0 𝗑10−10 m2/s under different drying conditions. The dehydrating curves of apples were best described by the model developed by Midilli et al.

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Section: Resultsmentioning

confidence: 61%

A study into how thickness, infrared intensity, and airflow affect drying kinetics, modeling, activation energy, and quality attributes of apple slices using infrared dryer

El‐Mesery,

Hu,

Ashiagbor

et al. 2024

Journal of Food Science

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“…Table 4 shows the activation energy and D 0 at all thicknesses examined. The ( E a ) ranged between 19.02 and 29.83 kJ/mol at various investigational settings, which is within the acceptable range of ( E a ) for the majority of goods (12.7–110 kJ/mol) (Shirazi et al., 2022; Tuly et al., 2023). At every level of infrared radiation magnitude, activation energy values rose as airflow velocity surged between 0.5 and 1.5 m/s.…”

Section: Resultsmentioning

confidence: 70%

Mathematical modeling of thin‐layer drying kinetics and moisture diffusivity study of apple slices using infrared conveyor‐belt dryer

El‐Mesery,

Ashiagbor,

et al. 2024

Journal of Food Science

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The drying features of apples at different infrared drying settings were investigated. The drying time, moisture‐effective diffusion, and activation energy of infrared dried apples were measured experimentally and statistically as a function of slice thicknesses, radiation intensity, and air velocity. The infrared intensity of 0.225, 0.130, and 0.341 W/cm2, slice thicknesses of 6, 4, and 2 mm, and airflow of 0.5, 1.0, and 1.5 m/s were used to dry apple slices. The data shows that the drying time reduced as IR increased, but airflow and slice thickness increased. Eight statistical factors were used to compare 11 alternative mathematical drying models. The experimentally acquired drying curves were matched to the thin‐layer drying equations. According to the calculations, the Midilli et al. equation had the greatest (efficiency and R2) and lowest (χ2, sum of squared errors, standard error of estimate, standard error, standard deviation of difference) values. As a result, this equation is the best for modeling the drying curves of apple slices across all drying circumstances. The optimum moisture diffusivity value varied from 2.59 to 9.07 × 10−10 m2/s. The mean activation energy was determined to be 19.02–29.83 kJ/mol under various experimental conditions.

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“…A further critical issue is the complexity of the fruit/vegetable's matrices, which have a heterogeneous composition that shows considerable variability depending on the harvest season, variety of that fruit/vegetable, geographic origin, agricultural practices, environmental conditions, and post-harvest handling. This variability is also reflected in their thermophysical properties, which change dynamically during dehydration operations [17,18].…”

Section: Introductionmentioning

confidence: 99%

“…A natural question that arises at this point is, why are optimization and control so crucial in dehydration, when it is a well-structured and operationally mature industrial process? The answer is that the dehydration behavior of foods and the relationship between process variables (e.g., temperature, humidity, and pressure) is yet to be fully understood [18,21,22], and thus it is an obstacle to achieving the highest quality dehydrated product with minimal energy expenditure, even in the simplest case of convective dehydration [23]. Therefore, although dehydration is one of the most industrially used techniques for stabilizing food products, it requires large amounts of energy to maintain certain temperature levels over time (at an industrial scale), thus making it one of the most energy intensive industrial activities [24].…”

Section: Introductionmentioning

confidence: 99%

Industrial Drying of Fruit and Vegetable Products: Customized Smart Monitoring and Analytical Characterization of Process Variables in the OTTORTO Project

Spagnuolo,

Vetromile,

Masiello

et al. 2023

Processes

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In the era of digitalization, the process industry is one of the sectors most affected by the need for change. The adoption of IoT-based intelligent monitoring systems for the collection of real-time measurements of energy and other essential operational variables, on one hand, makes it possible to accumulate big data useful for the company management to monitor the stability of the production process over time, and on the other hand, helps to develop predictive models that enable more efficient work and production. The OTTORTO project stems from the need of the FARRIS company to adapt its production line to agriculture 4.0 policies, responding to the higher goals of digitization and technological transition imposed at the national and EU level. The objectives of the current study are (i) to present an “ad hoc” customized intelligent and multi-parameter monitoring system to derive real-time temperature and humidity measurements inside the company’s industrial drying kilns; and (ii) to show how it is possible to extract information from operational data and convert it into a decision support too and an effective knowledge medium to better understand the production process. Studying the correlations between temperature and humidity measurements showed that for most of the observation period, the system was thermodynamically quite stable in terms of major operational risks, such as humidity saturation inside the kilns causing condensation on the products to be dried. However, to remedy the occasional occurrence of such inefficiencies, implementing kilns with the introduction of forced air extraction systems could bring significant benefits in terms of improved energy-environmental performance.

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Mathematical modeling of nutritional, color, texture, and microbial activity changes in fruit and vegetables during drying: A critical review

Cited by 23 publications

References 182 publications

A study into how thickness, infrared intensity, and airflow affect drying kinetics, modeling, activation energy, and quality attributes of apple slices using infrared dryer

A study into how thickness, infrared intensity, and airflow affect drying kinetics, modeling, activation energy, and quality attributes of apple slices using infrared dryer

Mathematical modeling of thin‐layer drying kinetics and moisture diffusivity study of apple slices using infrared conveyor‐belt dryer

Industrial Drying of Fruit and Vegetable Products: Customized Smart Monitoring and Analytical Characterization of Process Variables in the OTTORTO Project

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