Denetimli Örüntü Tanıma ve Gıda Analizlerinde Uygulamaları

Denetimli örüntü tanıma, sınıflandırma için örnek kategorisi üyeliği hakkında bir ön bilginin kullanıldığı teknikleri ifadeetmektedir. Sınıflandırma modeli, kategorileri olan örneklerin bir eğitim seti üzerinde geliştirilmektedir. Kimya, biyoloji,ilaç ve gıda bilimi içinde denetimli örüntü tanıma uygulaması giderek daha önemli hale gelmektedir. Denetimli örüntütanıma yöntemleri çok çeşitlidir ve asıl önemli nokta en uygun yöntemi seçmektir. Gıda analizlerinde gıda kalitedeğerlendirmesi, veri yorumlama gibi çeşitli amaçlarla farklı verilere uygulamaları bulunmaktadır. Denetimli örüntütanıma teknikleriyle incelenen gıdalara örnek olarak şarap, yağ, bal, süt ürünleri, et, meyveler, içecekler, tahıllar vebalık verilebilir. Bu teknikler kullanılarak gıdalarda doku analizi, aroma analizi, gıda doğrulaması, gıda kalitesinindeğerlendirilmesi, çoklu element analizi, coğrafi ve botanik kökene göre sınıflandırma gerçekleştirilebilmektedir. Buderlemede, denetimli örüntü tanıma tanımlanmış, uygulama teknikleri özetlenmiş ve gıda analizlerinde kullanılanörüntü tanıma teknikleri konusunda yapılan çalışmalar ile örneklendirilerek bilgi verilmiştir.

Supervised Pattern Recognition and its Applications in Food Analyses

Supervised pattern recognition is a technique for classification that the prior knowledge is used regarding member of sample category. Classification model is improved by using samples separated into category as training set. Supervised pattern recognition is getting more important for chemistry, biology, pharmacology and food science. There are many supervised pattern recognition methods. The main part is to select the most appropriate method. There are implementations to different inputs for various purposes such as food quality assessment and data interpretation. Wine, oil, honey, dairy products, meat, fruits, beverages, cereals and fish could be given as examples analyzed by supervised pattern recognition techniques. Also by using this techniques, texture and aroma analyses, food verification, food quality assessment, multiple element analysis, classification based on geographical and botanical origins can be performed. In this review, supervised pattern recognition is defined, its application techniques are summarized, and information is provided by exemplifying studies on pattern recognition techniques used in food analysis.

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