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

Tolga Kağan Tepe

doi:10.31466/kfbd.1333223

EN TR

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

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

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

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

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Details

Primary Language

English

Subjects

Food Engineering

Journal Section

Research Article

Authors

Tolga Kağan Tepe ^*
0000-0003-0484-7295
Türkiye

Early Pub Date

December 18, 2023

Publication Date

December 15, 2023

Submission Date

July 26, 2023

Acceptance Date

October 23, 2023

Published in Issue

Year 2023 Volume: 13 Number: 4

DOI

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

IZ

https://izlik.org/JA84TY94TT

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

AMA

1.Tepe TK. 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. KFBD. 2023;13(4):1738-1758. doi:10.31466/kfbd.1333223

Chicago

Tepe, Tolga Kağan. 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): 1738-58. https://doi.org/10.31466/kfbd.1333223.

EndNote

Tepe TK (December 1, 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.

IEEE

[1]T. K. Tepe, “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”, KFBD, vol. 13, no. 4, pp. 1738–1758, Dec. 2023, doi: 10.31466/kfbd.1333223.

ISNAD

Tepe, Tolga Kağan. “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 (December 1, 2023): 1738-1758. https://doi.org/10.31466/kfbd.1333223.

JAMA

1.Tepe TK. 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. KFBD. 2023;13:1738–1758.

MLA

Tepe, Tolga Kağan. “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, vol. 13, no. 4, Dec. 2023, pp. 1738-5, doi:10.31466/kfbd.1333223.

Vancouver

1.Tolga Kağan Tepe. 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. KFBD. 2023 Dec. 1;13(4):1738-5. doi:10.31466/kfbd.1333223

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