BALIK TAZELİĞİNİN ELEKTRONİK BURUN VE MAKİNE ÖĞRENMESİ İLE TESPİTİ ÜZERİNE LİTERATÜR ÇALIŞMASI

Year 2020, Volume: 16 Issue: 2, 161 - 170, 30.12.2020

Kutlucan Görür , Onursal Çetin , İlyas Özer , Feyzullah Temurtaş

Abstract

Balık tazelik kontrolü, gıda endüstrisindeki önemi nedeniyle son yıllarda büyük bir ilgi görmektedir. Balık tazeliği çalışmalarında farklı yaklaşımlar olsa da en önemlisi elektronik sensör dizilerinden oluşan elektronik burun yaklaşımıdır. Balıkta kalite özelliklerinden en önemlisi olan tazelik, balığın ilk sudan çıktığı andan tüketicilere kadar olan sürece ve depolama prosedürlerine bağlıdır. Pratik olarak, balıklarda ölüm sonrası meydana gelen fiziksel, kimyasal, biyokimyasal ve mikrobiyolojik değişiklikler, tat ve genel bir kalite kavramı açısından gıda özelliklerinde aşamalı bir kayıpla sonuçlanır. Bu açıdan geçen süre ve sıcaklık ürünün nihai kalitesi için anahtar faktörlerdir. Sinyal işleme ve makine öğrenmesi yaklaşımları balık tazeliğine ait elektronik burun tarafından ölçülen kokunun örüntüsünün tanınmasında oldukça önemli yöntemleri içermektedir. İlgili bu literatür çalışmasında özellikle balık tazeliği, elektronik burun ve sinyal işleme-makine öğrenmesi yaklaşımları açısından değerlendirilmiştir.

Keywords

Balık Tazeliği, Elektronik Burun, Sinyal İşleme, Makine Öğrenmesi

Thanks

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LITERATURE REVIEW ON DETERMINING FISH FRESHNESS BY ELECTRONIC NOSE AND MACHINE LEARNING

Abstract

Fish freshness control has gained a lot of attention in recent years due to its importance in the food industry. Although there are different approaches in fish freshness studies, the most important one is the electronic nose approach consisting of electronic sensor arrays. Freshness, which is the most important quality feature in fish, depends on the process and storage procedures from the moment the fish first emerges to the consumers. Practically, physical, chemical, biochemical and microbiological changes that occur after death in fish result in a gradual loss of food properties in terms of taste and a general concept of quality. In this respect, elapsed time and temperature are key factors for the final quality of the product. Signal processing and machine learning approaches include very important methods in recognizing the pattern of odor measured by the electronic nose of fish freshness. In this related literature study, especially fish freshness was evaluated in terms of electronic nose and signal processing-machine learning approaches.

Keywords

Fish Freshness, Electronic Nose, Signal Processing, Machine Learning

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