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Enhancement of Convective Banana Drying: Effect of Ethanol Pretreatment on Drying Characteristics, Color Properties, Shrinkage Ratio and Comparison of Artificial Neural Network and Thin Layer Modeling

Year 2023, Volume: 13 Issue: 4, 1738 - 1758, 15.12.2023

Tolga Kağan Tepe

https://doi.org/10.31466/kfbd.1333223

Abstract

The effect of ethanol pretreatment on the drying characteristics, color properties, shrinkage ratio and comparison of thin layer and artificial neural network (ANN) were investigated in the current study. Ethanol pretreatment increased drying rate and reduced drying time. In addition to this, ethanol concentration and pretreatment time had positive contribution to drying rate. According to the statistical parameters, ANN modeling showed better performance in the prediction of moisture ratio of the banana samples in comparison to thin layer modeling. On the other hand, color properties were negatively affected by drying and ethanol pretreatments. L* and b* values decreased whereas a* values of the banana samples showed increment tendency. Also, total color difference (∆E) was found to be higher than 5 value, indicating that non-trained observer notices the color change. Besides, it is obviously that ethanol pretreatment affected shrinkage ratio of the banana samples. Especially, diameter shrinkage ratio increased with the increment of ethanol concentration and pretreatment time.

Keywords

Drying Ethanol ANN Modeling Color Shrinkage Ratio Banana

References

  • Adam, I. K., Adam, A. A., & Bello, B. A. (2016). Effect of polyphenol oxidase on browning of apple and garden egg. Dutse Journal of Pure and Applied Sciences, 2(2), 177-184.
  • Aghbashlo, M., Hosseinpour, S., & Mujumdar, A. S. (2015). Application of artificial neural networks (ANNs) in drying technology: a comprehensive review. Drying technology, 33(12), 1397-1462.
  • Azimi-Nejadian, H., & Hoseini, S. S. (2019). Study the effect of microwave power and slices thickness on drying characteristics of potato. Heat and Mass Transfer, 55, 2921-2930.
  • Bai, J. W., Xiao, H. W., Ma, H. L., & Zhou, C. S. (2018). Artificial neural network modeling of drying kinetics and color changes of ginkgo biloba seeds during microwave drying process. Journal of Food Quality, 2018, 1-8.
  • Bassey, E. J., Cheng, J. H., & Sun, D. W. (2021). Novel nonthermal and thermal pretreatments for enhancing drying performance and improving quality of fruits and vegetables. Trends in Food Science & Technology, 112, 137-148.
  • Batu, H. S., & Kadakal, Ç. (2021). Drying characteristics and degradation kinetics in some parameters of goji berry (Lycium Barbarum L.) fruit during hot air drying. Italian Journal of Food Science, 33(1), 16-28.
  • Bhagya Raj, G. V. S., & Dash, K. K. (2022). Comprehensive study on applications of artificial neural network in food process modeling. Critical reviews in food science and nutrition, 62(10), 2756-2783.
  • Bozkir, H., & Ergün, A. R. (2020). Effect of sonication and osmotic dehydration applications on the hot air drying kinetics and quality of persimmon. Lwt, 131, 109704.
  • Bozkır, H., & Ergün, A. R. (2020). Effect of sonication and osmotic dehydration applications on the hot air drying kinetics and quality of persimmon. Lwt, 131, 109704.
  • Brasiello, A., Adiletta, G., Russo, P., Crescitelli, S., Albanese, D., & Di Matteo, M. (2013). Mathematical modeling of eggplant drying: Shrinkage effect. Journal of food engineering, 114(1), 99-105.
  • Chokphoemphun, S., Hongkong, S., & Chokphoemphun, S. (2023). Evaluation of drying behavior and characteristics of the potato slices in multi–stage convective cabinet dryer: application of artificial neural network. Information Processing in Agriculture.
  • de Freitas, L. D. C., Brandão, S. C. R., Fernandes da Silva, J. H., Sá da Rocha, O. R., & Azoubel, P. M. (2021). Effect of ethanol and ultrasound pretreatments on pineapple convective drying. Food Technology and Biotechnology, 59(2), 209-215.
  • Dongbang, W., & Nuantong, W. (2020). Investigation of Mathematical Modeling for Banana Slices Drying using Hot Air Technique. Naresuan University Journal: Science and Technology (NUJST), 28(3), 79-87.
  • Dongbang, W., & Nuantong, W. (2020). Investigation of Mathematical Modeling for Banana Slices Drying using Hot Air Technique. Naresuan University Journal: Science and Technology (NUJST), 28(3), 79-87.
  • E.I.A, 2018. Energy Information Administration: Today in Energy. Linda Doman, Washington DC. González-Cavieres, L., Perez-Won, M., Tabilo-Munizaga, G., Jara-Quijada, E., Díaz-Álvarez, R., & Lemus-Mondaca, R. (2021). Advances in vacuum microwave drying (VMD) systems for food products. Trends in Food Science & Technology, 116, 626-638.
  • Granella, S. J., Bechlin, T. R., & Christ, D. (2022). Moisture diffusion by the fractional-time model in convective drying with ultrasound-ethanol pretreatment of banana slices. Innovative Food Science & Emerging Technologies, 76, 102933.
  • Guiné, R. P., Barroca, M. J., Gonçalves, F. J., Alves, M., Oliveira, S., & Mendes, M. (2015). Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments. Food Chemistry, 168, 454-459.
  • Huang, D., Men, K., Li, D., Wen, T., Gong, Z., Sunden, B., & Wu, Z. (2020). Application of ultrasound technology in the drying of food products. Ultrasonics sonochemistry, 63, 104950.
  • Jarahizadeh, H., & Dinani, S. T. (2019). Influence of applied time and power of ultrasonic pretreatment on convective drying of potato slices. Food science and biotechnology, 28(2), 365-376.
  • Kurtulmuş, F., Polat, A., & Nazmi, İ. Z. L. İ. (2020). Yapay Sinir Ağları Kullanarak Kayısının Farklı Kurutma Yöntemleriyle Kurutulmasında Kuruma Hızı Ve Nem İçeriği Parametrelerinin Modellenmesi. ÇOMÜ Ziraat Fakültesi Dergisi, 8(2), 261-269.
  • La Fuente, C. I., & Tadini, C. C. (2018). Ultrasound pre-treatment prior to unripe banana air-drying: effect of the ultrasonic volumetric power on the kinetic parameters. Journal of food science and technology, 55(12), 5098-5105.
  • Llavata, B., García-Pérez, J. V., Simal, S., & Cárcel, J. A. (2020). Innovative pre-treatments to enhance food drying: A current review. Current Opinion in Food Science, 35, 20-26.
  • Macedo, L. L., Vimercati, W. C., da Silva Araújo, C., Saraiva, S. H., & Teixeira, L. J. Q. (2020). Effect of drying air temperature on drying kinetics and physicochemical characteristics of dried banana. Journal of Food Process Engineering, 43(9), e13451.
  • Murthy, T. P. K., & Manohar, B. (2014). Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network. Journal of Food Science and Technology, 51, 3712-3721.
  • Naderinezhad, S., Etesami, N., Poormalek Najafabady, A., & Ghasemi Falavarjani, M. (2016). Mathematical modeling of drying of the potato slices in a forced convective dryer based on important parameters. Food Science & Nutrition, 4(1), 110-118.
  • Omari, A., Behroozi‐Khazaei, N., & Sharifian, F. (2018). Drying kinetic and artificial neural network modeling of mushroom drying process in microwave‐hot air dryer. Journal of Food Process Engineering, 41(7), e12849.
  • Omari, A., Behroozi‐Khazaei, N., & Sharifian, F. (2018). Drying kinetic and artificial neural network modeling of mushroom drying process in microwave‐hot air dryer. Journal of Food Process Engineering, 41(7), e12849.
  • Qu, J. H., Sun, D. W., Cheng, J. H., & Pu, H. (2017). Mapping moisture contents in grass carp (Ctenopharyngodon idella) slices under different freeze drying periods by Vis-NIR hyperspectral imaging. Lwt, 75, 529-536.
  • Rasooli Sharabiani, V., Kaveh, M., Abdi, R., Szymanek, M., & Tanaś, W. (2021). Estimation of moisture ratio for apple drying by convective and microwave methods using artificial neural network modeling. Scientific reports, 11(1), 1-12.
  • Rojas, M. L., & Augusto, P. E. (2018). Ethanol and ultrasound pre-treatments to improve infrared drying of the potato slices. Innovative food science & emerging technologies, 49, 65-75.
  • Rojas, M. L., Augusto, P. E. D., & Cárcel, J. A. (2020b). Ethanol pre-treatment to ultrasound-assisted convective drying of apple. Innovative Food Science & Emerging Technologies, 61, 102328.
  • Rojas, M. L., Silveira, I., & Augusto, P. E. D. (2020a). Ultrasound and ethanol pre-treatments to improve convective drying: Drying, rehydration and carotenoid content of pumpkin. Food and Bioproducts Processing, 119, 20-30.
  • Şahin, U., & Öztürk, H. K. (2018). Comparison between artificial neural network model and mathematical models for drying kinetics of osmotically dehydrated and fresh figs under open sun drying. Journal of Food Process Engineering, 41(5), e12804.
  • Santos, K. C., Guedes, J. S., Rojas, M. L., Carvalho, G. R., & Augusto, P. E. D. (2021). Enhancing carrot convective drying by combining ethanol and ultrasound as pre-treatments: Effect on product structure, quality, energy consumption, drying and rehydration kinetics. Ultrasonics Sonochemistry, 70, 105304.
  • Seerangurayar, T., Al-Ismaili, A. M., Jeewantha, L. J., & Al-Nabhani, A. (2019). Experimental investigation of shrinkage and microstructural properties of date fruits at three solar drying methods. Solar Energy, 180, 445-455.
  • Senadeera, W. (2008). The drying constant and its effect on the shrinkage constant of different-shaped food particulates. International Journal of Food Engineering, 4(8).
  • Senadeera, W., Adiletta, G., Önal, B., Di Matteo, M., & Russo, P. (2020). Influence of different hot air drying temperatures on drying kinetics, shrinkage, and colour of persimmon slices. Foods, 9(1), 101.
  • Seyedabadi, E., Khojastehpour, M., & Abbaspour-Fard, M. H. (2017). Convective drying simulation of banana slabs considering non-isotropic shrinkage using FEM with the Arbitrary Lagrangian–Eulerian method. International journal of food properties, 20(sup1), S36-S49.
  • Soliva-Fortuny, R. C., & Martı́n-Belloso, O. (2003). New advances in extending the shelf-life of fresh-cut fruits: a review. Trends in Food Science & Technology, 14(9), 341-353.
  • Srimagal, A., Mishra, S., & Pradhan, R. C. (2017). Effects of ethyl oleate and microwave blanching on drying kinetics of bitter gourd. Journal of food science and technology, 54(5), 1192-1198.
  • Tepe, F. B. (2022). Impact of pretreatments and hybrid microwave assisting on drying characteristics and bioactive properties of apple slices. Journal of Food Processing and Preservation, 46(10), e17067.
  • Tepe, F. B. (2022). Impact of pretreatments and hybrid microwave assisting on drying characteristics and bioactive properties of apple slices. Journal of Food Processing and Preservation, 46(10), e17067.
  • Tepe, T. K., & Tepe, B. (2020). The comparison of drying and rehydration characteristics of intermittent-microwave and hot-air dried-apple slices. Heat and Mass Transfer, 56(11), 3047-3057.
  • Tepe, T. K., & Tepe, B. (2020). The comparison of drying and rehydration characteristics of intermittent-microwave and hot-air dried-apple slices. Heat and Mass Transfer, 56(11), 3047-3057.
  • TEPGE, Republic of Turkey Ministry of Agriculture and Forestry Agricultural Economic and Policy Development Institute 2020, https://arastirma.tarimorman.gov.tr/tepge Accessed 27 April 2021
  • Tunckal, C., & Doymaz, İ. (2020). Performance analysis and mathematical modelling of banana slices in a heat pump drying system. Renewable Energy, 150, 918-923.
  • Turkish Statistical Institute. Production of fruits, beverage and spice crops. https://data.tuik.gov.tr/Kategori/GetKategori?p=tarim-111&dil=1. Accessed 22 July 2023
  • Yıldız, A. K., Polatcı, H., & Uçun, H. (2015). Farklı Kurutma Şartlarında Muz (Musa cavendishii) Meyvesinin Kurutulması ve Kurutma Kinetiğinin Yapay Sinir Ağları ile Modellenmesi. Tarım Makinaları Bilimi Dergisi, 11(2), 173-178.

Muz Kurutmada Konvektif Kurutma Yönteminin İyileştirilmesi: Etil Alkol Ön İşleminin Kurutma, Renk Özellikleri ve Büzüşme Oranı Üzerine Etkisi ile Yapay Sinir Ağı ve İnce Tabaka Modellemesinin Karşılaştırılması

Year 2023, Volume: 13 Issue: 4, 1738 - 1758, 15.12.2023

Tolga Kağan Tepe

https://doi.org/10.31466/kfbd.1333223

Abstract

Bu araştırma, etanol ön işleminin kurutma ve renk özellikleri ile büzüşme oranı üzerindeki etkisini incelemeyi ve ince tabaka ile yapay sinir ağı (YSA) yöntemlerini karşılaştırmayı amaçlamaktadır. Etanol ön işleminin kuruma hızını artırdığı ve buna bağlı olarak kuruma süresini kısalttığı gözlenmiştir. Ayrıca, etanol konsantrasyonunun ve ön işlem süresinin kuruma hızına olumlu yönde katkısı bulunmaktadır. İstatistiksel parametreler ele alındığında, YSA modelleme yöntemi ince tabaka kurutma modellerine göre muz örneklerinin nem oranı tahmininde daha iyi performans göstermiştir. Bununla birlikte, renk özellikleri kurutma ve etanol ön işleminden olumsuz yönde etkilenmiştir. L* ve b* değerleri azalırken, muz örneklerinin a* değerleri artış eğilimi göstermiştir. Ayrıca, toplam renk farkı (∆E) 5 değerinden yüksek bulunmuştur, bu da eğitilmemiş gözlemcinin renk değişikliğini fark edebileceğini göstermektedir. Ayrıca, etanol ön işleminin muz örneklerinin büzüşme oranını etkilediği gözlenmiştir. Özellikle örneklerin çapında meydana gelen büzüşme oranı, etanol konsantrasyonunun ve ön işlem süresinin artmasıyla birlikte artmıştır.

Keywords

Kurutma Etanol YSA Modelleme Renk Büzüşme Oranı Muz

References

  • Adam, I. K., Adam, A. A., & Bello, B. A. (2016). Effect of polyphenol oxidase on browning of apple and garden egg. Dutse Journal of Pure and Applied Sciences, 2(2), 177-184.
  • Aghbashlo, M., Hosseinpour, S., & Mujumdar, A. S. (2015). Application of artificial neural networks (ANNs) in drying technology: a comprehensive review. Drying technology, 33(12), 1397-1462.
  • Azimi-Nejadian, H., & Hoseini, S. S. (2019). Study the effect of microwave power and slices thickness on drying characteristics of potato. Heat and Mass Transfer, 55, 2921-2930.
  • Bai, J. W., Xiao, H. W., Ma, H. L., & Zhou, C. S. (2018). Artificial neural network modeling of drying kinetics and color changes of ginkgo biloba seeds during microwave drying process. Journal of Food Quality, 2018, 1-8.
  • Bassey, E. J., Cheng, J. H., & Sun, D. W. (2021). Novel nonthermal and thermal pretreatments for enhancing drying performance and improving quality of fruits and vegetables. Trends in Food Science & Technology, 112, 137-148.
  • Batu, H. S., & Kadakal, Ç. (2021). Drying characteristics and degradation kinetics in some parameters of goji berry (Lycium Barbarum L.) fruit during hot air drying. Italian Journal of Food Science, 33(1), 16-28.
  • Bhagya Raj, G. V. S., & Dash, K. K. (2022). Comprehensive study on applications of artificial neural network in food process modeling. Critical reviews in food science and nutrition, 62(10), 2756-2783.
  • Bozkir, H., & Ergün, A. R. (2020). Effect of sonication and osmotic dehydration applications on the hot air drying kinetics and quality of persimmon. Lwt, 131, 109704.
  • Bozkır, H., & Ergün, A. R. (2020). Effect of sonication and osmotic dehydration applications on the hot air drying kinetics and quality of persimmon. Lwt, 131, 109704.
  • Brasiello, A., Adiletta, G., Russo, P., Crescitelli, S., Albanese, D., & Di Matteo, M. (2013). Mathematical modeling of eggplant drying: Shrinkage effect. Journal of food engineering, 114(1), 99-105.
  • Chokphoemphun, S., Hongkong, S., & Chokphoemphun, S. (2023). Evaluation of drying behavior and characteristics of the potato slices in multi–stage convective cabinet dryer: application of artificial neural network. Information Processing in Agriculture.
  • de Freitas, L. D. C., Brandão, S. C. R., Fernandes da Silva, J. H., Sá da Rocha, O. R., & Azoubel, P. M. (2021). Effect of ethanol and ultrasound pretreatments on pineapple convective drying. Food Technology and Biotechnology, 59(2), 209-215.
  • Dongbang, W., & Nuantong, W. (2020). Investigation of Mathematical Modeling for Banana Slices Drying using Hot Air Technique. Naresuan University Journal: Science and Technology (NUJST), 28(3), 79-87.
  • Dongbang, W., & Nuantong, W. (2020). Investigation of Mathematical Modeling for Banana Slices Drying using Hot Air Technique. Naresuan University Journal: Science and Technology (NUJST), 28(3), 79-87.
  • E.I.A, 2018. Energy Information Administration: Today in Energy. Linda Doman, Washington DC. González-Cavieres, L., Perez-Won, M., Tabilo-Munizaga, G., Jara-Quijada, E., Díaz-Álvarez, R., & Lemus-Mondaca, R. (2021). Advances in vacuum microwave drying (VMD) systems for food products. Trends in Food Science & Technology, 116, 626-638.
  • Granella, S. J., Bechlin, T. R., & Christ, D. (2022). Moisture diffusion by the fractional-time model in convective drying with ultrasound-ethanol pretreatment of banana slices. Innovative Food Science & Emerging Technologies, 76, 102933.
  • Guiné, R. P., Barroca, M. J., Gonçalves, F. J., Alves, M., Oliveira, S., & Mendes, M. (2015). Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments. Food Chemistry, 168, 454-459.
  • Huang, D., Men, K., Li, D., Wen, T., Gong, Z., Sunden, B., & Wu, Z. (2020). Application of ultrasound technology in the drying of food products. Ultrasonics sonochemistry, 63, 104950.
  • Jarahizadeh, H., & Dinani, S. T. (2019). Influence of applied time and power of ultrasonic pretreatment on convective drying of potato slices. Food science and biotechnology, 28(2), 365-376.
  • Kurtulmuş, F., Polat, A., & Nazmi, İ. Z. L. İ. (2020). Yapay Sinir Ağları Kullanarak Kayısının Farklı Kurutma Yöntemleriyle Kurutulmasında Kuruma Hızı Ve Nem İçeriği Parametrelerinin Modellenmesi. ÇOMÜ Ziraat Fakültesi Dergisi, 8(2), 261-269.
  • La Fuente, C. I., & Tadini, C. C. (2018). Ultrasound pre-treatment prior to unripe banana air-drying: effect of the ultrasonic volumetric power on the kinetic parameters. Journal of food science and technology, 55(12), 5098-5105.
  • Llavata, B., García-Pérez, J. V., Simal, S., & Cárcel, J. A. (2020). Innovative pre-treatments to enhance food drying: A current review. Current Opinion in Food Science, 35, 20-26.
  • Macedo, L. L., Vimercati, W. C., da Silva Araújo, C., Saraiva, S. H., & Teixeira, L. J. Q. (2020). Effect of drying air temperature on drying kinetics and physicochemical characteristics of dried banana. Journal of Food Process Engineering, 43(9), e13451.
  • Murthy, T. P. K., & Manohar, B. (2014). Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network. Journal of Food Science and Technology, 51, 3712-3721.
  • Naderinezhad, S., Etesami, N., Poormalek Najafabady, A., & Ghasemi Falavarjani, M. (2016). Mathematical modeling of drying of the potato slices in a forced convective dryer based on important parameters. Food Science & Nutrition, 4(1), 110-118.
  • Omari, A., Behroozi‐Khazaei, N., & Sharifian, F. (2018). Drying kinetic and artificial neural network modeling of mushroom drying process in microwave‐hot air dryer. Journal of Food Process Engineering, 41(7), e12849.
  • Omari, A., Behroozi‐Khazaei, N., & Sharifian, F. (2018). Drying kinetic and artificial neural network modeling of mushroom drying process in microwave‐hot air dryer. Journal of Food Process Engineering, 41(7), e12849.
  • Qu, J. H., Sun, D. W., Cheng, J. H., & Pu, H. (2017). Mapping moisture contents in grass carp (Ctenopharyngodon idella) slices under different freeze drying periods by Vis-NIR hyperspectral imaging. Lwt, 75, 529-536.
  • Rasooli Sharabiani, V., Kaveh, M., Abdi, R., Szymanek, M., & Tanaś, W. (2021). Estimation of moisture ratio for apple drying by convective and microwave methods using artificial neural network modeling. Scientific reports, 11(1), 1-12.
  • Rojas, M. L., & Augusto, P. E. (2018). Ethanol and ultrasound pre-treatments to improve infrared drying of the potato slices. Innovative food science & emerging technologies, 49, 65-75.
  • Rojas, M. L., Augusto, P. E. D., & Cárcel, J. A. (2020b). Ethanol pre-treatment to ultrasound-assisted convective drying of apple. Innovative Food Science & Emerging Technologies, 61, 102328.
  • Rojas, M. L., Silveira, I., & Augusto, P. E. D. (2020a). Ultrasound and ethanol pre-treatments to improve convective drying: Drying, rehydration and carotenoid content of pumpkin. Food and Bioproducts Processing, 119, 20-30.
  • Şahin, U., & Öztürk, H. K. (2018). Comparison between artificial neural network model and mathematical models for drying kinetics of osmotically dehydrated and fresh figs under open sun drying. Journal of Food Process Engineering, 41(5), e12804.
  • Santos, K. C., Guedes, J. S., Rojas, M. L., Carvalho, G. R., & Augusto, P. E. D. (2021). Enhancing carrot convective drying by combining ethanol and ultrasound as pre-treatments: Effect on product structure, quality, energy consumption, drying and rehydration kinetics. Ultrasonics Sonochemistry, 70, 105304.
  • Seerangurayar, T., Al-Ismaili, A. M., Jeewantha, L. J., & Al-Nabhani, A. (2019). Experimental investigation of shrinkage and microstructural properties of date fruits at three solar drying methods. Solar Energy, 180, 445-455.
  • Senadeera, W. (2008). The drying constant and its effect on the shrinkage constant of different-shaped food particulates. International Journal of Food Engineering, 4(8).
  • Senadeera, W., Adiletta, G., Önal, B., Di Matteo, M., & Russo, P. (2020). Influence of different hot air drying temperatures on drying kinetics, shrinkage, and colour of persimmon slices. Foods, 9(1), 101.
  • Seyedabadi, E., Khojastehpour, M., & Abbaspour-Fard, M. H. (2017). Convective drying simulation of banana slabs considering non-isotropic shrinkage using FEM with the Arbitrary Lagrangian–Eulerian method. International journal of food properties, 20(sup1), S36-S49.
  • Soliva-Fortuny, R. C., & Martı́n-Belloso, O. (2003). New advances in extending the shelf-life of fresh-cut fruits: a review. Trends in Food Science & Technology, 14(9), 341-353.
  • Srimagal, A., Mishra, S., & Pradhan, R. C. (2017). Effects of ethyl oleate and microwave blanching on drying kinetics of bitter gourd. Journal of food science and technology, 54(5), 1192-1198.
  • Tepe, F. B. (2022). Impact of pretreatments and hybrid microwave assisting on drying characteristics and bioactive properties of apple slices. Journal of Food Processing and Preservation, 46(10), e17067.
  • Tepe, F. B. (2022). Impact of pretreatments and hybrid microwave assisting on drying characteristics and bioactive properties of apple slices. Journal of Food Processing and Preservation, 46(10), e17067.
  • Tepe, T. K., & Tepe, B. (2020). The comparison of drying and rehydration characteristics of intermittent-microwave and hot-air dried-apple slices. Heat and Mass Transfer, 56(11), 3047-3057.
  • Tepe, T. K., & Tepe, B. (2020). The comparison of drying and rehydration characteristics of intermittent-microwave and hot-air dried-apple slices. Heat and Mass Transfer, 56(11), 3047-3057.
  • TEPGE, Republic of Turkey Ministry of Agriculture and Forestry Agricultural Economic and Policy Development Institute 2020, https://arastirma.tarimorman.gov.tr/tepge Accessed 27 April 2021
  • Tunckal, C., & Doymaz, İ. (2020). Performance analysis and mathematical modelling of banana slices in a heat pump drying system. Renewable Energy, 150, 918-923.
  • Turkish Statistical Institute. Production of fruits, beverage and spice crops. https://data.tuik.gov.tr/Kategori/GetKategori?p=tarim-111&dil=1. Accessed 22 July 2023
  • Yıldız, A. K., Polatcı, H., & Uçun, H. (2015). Farklı Kurutma Şartlarında Muz (Musa cavendishii) Meyvesinin Kurutulması ve Kurutma Kinetiğinin Yapay Sinir Ağları ile Modellenmesi. Tarım Makinaları Bilimi Dergisi, 11(2), 173-178.
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Primary Language English
Subjects Food Engineering
Journal Section Articles
Authors

Tolga Kağan Tepe 0000-0003-0484-7295

Early Pub Date December 18, 2023
Publication Date December 15, 2023
Published in Issue Year 2023 Volume: 13 Issue: 4

Cite

APA Tepe, T. K. (2023). Enhancement of Convective Banana Drying: Effect of Ethanol Pretreatment on Drying Characteristics, Color Properties, Shrinkage Ratio and Comparison of Artificial Neural Network and Thin Layer Modeling. Karadeniz Fen Bilimleri Dergisi, 13(4), 1738-1758. https://doi.org/10.31466/kfbd.1333223
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