HAMSIYE UYGULANAN ISIL İŞLEMIN KOKUŞMA ÜZERINE ETKILERINININ ELEKTRONIK BURUN İLE BELIRLENMESI

Yıl 2025, Cilt: 50 Sayı: 4, 620 - 628, 10.08.2025

Emre Yavuzer

https://doi.org/10.15237/gida.GD25066

Öz

Bu çalışmada, hamsi balıklarının bözulma seviyelerine ısıl işlemin etkisi elektronik burun sistemi kullanılarak araştırılmıştır. Depolama süreleri boyunca çiğ ve pişmiş hamsi örneklerinden elde edilen sensör verileri (MQ3, MQ4, MQ5, MQ9, MQ131, MQ135, MQ136, MQ137, MQ138, MQ139, MG811 ve TGS813) ve sensörlerin koku değişikliklerine olan hassasiyetleri analiz edilmiştir. İki durum arasındaki sinyal farklılıklarına (ΔS) dayanarak, ısıl işlemin koku dinamikleri üzerindeki etkisi doğrusal regresyon modelleri ile modellenmiştir. Örneğin, MQ136 sensörü için modelleme sonuçları ΔS(t) = -16.59t + 37.33 (R² = 0.84) biçiminde belirlenmiş ve ısıl işlemin sensör tepkilerini zamanla önemli ölçüde azalttığını göstermiştir. Bulgular, pişirmenin muhtemelen lipit oksidasyonu ve uçucu bileşik dinamiklerindeki değişiklikler nedeniyle koku oluşumunu geciktirdiğini ve düşük maliyetli sensörlerin gelişmiş bir elektronik burun sistemine dönüştürülebileceğini göstermiştir.

Anahtar Kelimeler

Hamsi , elektronik burun , MQ sensörü , ısıl işlem , kokuşma

DETERMINATION OF THE EFFECTS OF HEAT TREATMENT APPLIED TO ANCHOVY ON PUTREFACTION BY ELECTRONIC NOSE

Öz

In this study, the effect of heat treatment on the putrefaction levels of anchovy fish was investigated using an electronic nose system. Sensor data (MQ3, MQ4, MQ5, MQ9, MQ131, MQ135, MQ136, MQ137, MQ138, MQ139, MG811 and TGS813) obtained from raw and cooked anchovy samples during storage periods and the sensitivity of the sensors to odour changes were analysed. Based on the differences of their signals (ΔS) between two states, the effect of heat treatment on the odour dynamics was modelled by linear regression models. For example, modelling results for the MQ136 sensor were determined in the form ΔS(t) = -16.59t + 37.33 (R² = 0.84), showing that cooking significantly decreases sensor responses over time. The findings indicated that cooking was found to delay odorization, likely due to changes in lipid oxidation and volatile compound dynamics, and that low-cost sensors can be developed into an advanced electronic nose system.

Anahtar Kelimeler

Anchovy , electronic nose , MQ sensor , heat treatment , putrefaction

Kaynakça

• Al Isyrofie, A. I. F., Kashif, M., Aji, A. K., Aidatuzzahro, N., Rahmatillah, A., Winarno, Susilo, Y., Syahrom, A., Astuti, S. D. (2022). Odor clustering using a gas sensor array system of chicken meat based on temperature variations and storage time. Sensing and Bio-Sensing Research, 37, 100508. https://doi.org/10.1016/ J.SBSR.2022.100508
• Amorim, T. L., Fuente, M. A. de la, Oliveira, M. A. L. de, Gómez-Cortés, P. (2021). ATR-FTIR and Raman Spectroscopies Associated with Chemometrics for Lipid Form Evaluation of Fish Oil Supplements: A Comparative Study. ACS Food Science and Technology, 1(3), 318–325. https://doi.org/10.1021/ACSFOODSCITECH.0C00122/ASSET/IMAGES/LARGE/FS0C00122_0004.JPEG
• Astuti, S. D., Tamimi, M. H., Pradhana, A. A. S., Alamsyah, K. A., Purnobasuki, H., Khasanah, M., Susilo, Y., Triyana, K., Kashif, M., Syahrom, A. (2021). Gas sensor array to classify the chicken meat with E. coli contaminant by using random forest and support vector machine. Biosensors and Bioelectronics: X, 9, 100083. https://doi.org/ 10.1016/J.BIOSX.2021.100083
• Crisinel, A.-S., Cosser, S., King, S., Jones, R., Petrie, J., Spence, C. (2012). A bittersweet symphony: Systematically modulating the taste of food by changing the sonic properties of the soundtrack playing in the background. Food Quality and Preference, 24(1), 201–204. https://doi.org/10.1016/j.foodqual.2011.08.009
• Dağtekin, M., Gücü, A. C., Genç, Y. (2022). Concerns about illegal, unreported and unregulated fishing, carbon footprint, and the impact of fuel subsidy - An economic analysis of the Black Sea anchovy fishery. Marine Policy, 140, 105067. https://doi.org/10.1016/ J.MARPOL.2022.105067
• Darvishi, P., Mirzaee-Ghaleh, E., Ramedani, Z., Karami, H., Wilson, A. D. (2024). Detecting whey adulteration of powdered milk by analysis of volatile emissions using a MOS electronic nose. International Dairy Journal, 157, 106012. https://doi.org/10.1016/J.IDAIRYJ.2024.106012
• Kumar, T., Doss, A. (2023). AIRO: Development of an Intelligent IoT-based Air Quality Monitoring Solution for Urban Areas. Procedia Computer Science, 218, 262–273. https://doi.org/ 10.1016/J.PROCS.2023.01.008
• Lu, L., Hu, Z., Hu, X., Li, D., Tian, S. (2022). Electronic tongue and electronic nose for food quality and safety. Food Research International, 162, 112214. https://doi.org/10.1016/ j.foodres.2022.112214
• Moon, S. Y., Kim, H. (2024). Feeding habits of Pacific anchovy, Engraulis japonicus (Actinopterygii: Clupeiformes: Engraulidae), captured off the southern coasts of Korea. Acta Ichthyologica et Piscatoria, 54, 1–11. https://doi.org/ 10.3897/AIEP.54.109601
• Öğretmen, Ö. Y. (2022). The effect of migration on fatty acid, amino acid, and proximate compositions of the Black Sea anchovy (Engraulis encrasicolus, Linne 1758) from Turkey, Georgia, and Abkhazia. Journal of Food Composition and Analysis, 105, 104197. https://doi.org/ 10.1016/J.JFCA.2021.104197
• Özoğul, F. (2004). Production of biogenic amines by Morganella morganii, Klebsiella pneumoniae and Hafnia alvei using a rapid HPLC method. European Food Research and Technology, 219(5), 465–469. https://doi.org/10.1007/s00217-004-0988-0
• Özoğul, F., Yavuzer, E., Özoğul, Y., Kuley, E. (2013). Comparative Quality Loss in Wild and Cultured Rainbow Trout (Oncorhynchus mykiss) during Chilling Storage. Food Science and Technology Research, 19(3), 445–454. https://doi.org/ 10.3136/fstr.19.445
• Park, J. A., Joo, S. Y., Cho, M. S., Oh, J. E. (2018). Changes in the physicochemical and microbiological properties of dried anchovy Engraulis japonicus during storage. Fisheries Science, 84(6), 1091–1098. https://doi.org/ 10.1007/S12562-018-1244-Z/TABLES/2
• Viciano-Tudela, S., Parra, L., Navarro-Garcia, P., Sendra, S., Lloret, J. (2023). Proposal of a New System for Essential Oil Classification Based on Low-Cost Gas Sensor and Machine Learning Techniques. Sensors 2023, Vol. 23, Page 5812, 23(13), 5812. https://doi.org/10.3390/ S23135812
• Wang, B., Deng, J., Jiang, H., Chen, Q. (2022). Electronic nose signals-based deep learning models to realize high-precision monitoring of simultaneous saccharification and fermentation of cassava. Microchemical Journal, 182, 107929. https://doi.org/10.1016/J.MICROC.2022.107929
• Yavuzer, E. (2018). Development of defective fish egg sorting machine with colour sensor for trout facilities. Aquaculture Research, 49(11), 3634–3637. https://doi.org/10.1111/are.13831
• Yavuzer, E. (2020). Determination of rainbow trout quality parameters with Arduino microcontroller. Journal of Food Safety, 40(6). https://doi.org/10.1111/jfs.12857
• Yavuzer, E. (2021). Determination of fish quality parameters with low cost electronic nose. Food Bioscience, 41, 100948. https://doi.org/10.1016/ j.fbio.2021.100948
• Yavuzer, E. (2023). Rapid detection of sea bass quality level with machine learning and electronic nose. International Journal of Food Science & Technology, 58(5), 2355–2359. https://doi.org/ 10.1111/IJFS.16365
• Yavuzer, E., Köse, M., Uslu, H. (2024). Determining the quality level of ready to-eat stuffed mussels with Arduino-based electronic nose. Journal of Food Measurement and Characterization, 18(7), 5629–5637. https://doi.org/10.1007/s11694-024-02593-9
• Ye, Y., Zhou, T., Liu, T., Shi, W. (2024). Quality-based selection of the optimal hot air gradient drying method for anchovy and modeling of drying kinetics. Aquaculture and Fisheries. https://doi.org/10.1016/J.AAF.2024.03.002