Optimization of the Drying Process for Gamma-Irradiated Mushroom Slices Using Mathematical Models and Machine Learning Algorithms Article Swipe
Ehsan Fartash Naeimi
,
Mohammad Hadi Khoshtaghaza
,
K. Selvi
,
N. Ungureanu
,
Soleiman Abbasi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/agriculture14122351
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/agriculture14122351
Concerns over dried product quality and energy consumption have prompted researchers to explore integrated techniques for improving quality and reducing energy use. This study investigates the effect of gamma irradiation pretreatment (0, 1.2, 2.4, and 3.6 kGy) on button mushroom slices, followed by thin-layer drying at 50, 60, and 70 °C. The results indicated that increasing irradiation dose and drying temperature significantly reduced drying time. The Midilli model provided the best fıt to the drying data (R2 = 0.9969–0.9998). Artificial neural networks (ANN) accurately predicted moisture variations, achieving R2 = 0.9975 and RMSE = 0.0220. The Support Vector Machine (SVM) algorithm, employing the Pearson universal kernel in normalized mode, also performed well, with R2 = 0.9939 and RMSE = 0.0344. Similarly, in the k-nearest neighbors (kNN) algorithm with three neighbors (k = 3), the R2 and RMSE values were 0.9888 and 0.0458, respectively. Gamma irradiation enhanced the effective diffusion coefficient (Deff) to 10.796 × 10−8 m2/s, and reduced activation energy (Ea) to 11.09 kJ/mol. The highest heat utilization efficiency (41.1%) was observed at 3.6 kGy and 50 °C. These findings highlight the potential of integrating gamma irradiation pretreatment and advanced drying techniques to optimize energy use and improve the quality of dried mushroom slices.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/agriculture14122351
- https://www.mdpi.com/2077-0472/14/12/2351/pdf?version=1735014885
- OA Status
- gold
- Cited By
- 4
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405725303
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- OpenAlex ID
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https://openalex.org/W4405725303Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/agriculture14122351Digital Object Identifier
- Title
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Optimization of the Drying Process for Gamma-Irradiated Mushroom Slices Using Mathematical Models and Machine Learning AlgorithmsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-20Full publication date if available
- Authors
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Ehsan Fartash Naeimi, Mohammad Hadi Khoshtaghaza, K. Selvi, N. Ungureanu, Soleiman AbbasiList of authors in order
- Landing page
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https://doi.org/10.3390/agriculture14122351Publisher landing page
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https://www.mdpi.com/2077-0472/14/12/2351/pdf?version=1735014885Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2077-0472/14/12/2351/pdf?version=1735014885Direct OA link when available
- Concepts
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Mean squared error, Irradiation, Algorithm, Mushroom, Coefficient of determination, Machine learning, Artificial intelligence, Support vector machine, Materials science, Mathematics, Computer science, Chemistry, Biological system, Food science, Statistics, Physics, Nuclear physics, BiologyTop concepts (fields/topics) attached by OpenAlex
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4Total citation count in OpenAlex
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2025: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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