Supervised Pattern Recognition and its Applications in Food Analyses

Year 2019, , 429 - 438, 18.11.2019

Bahar Demircan Yeşim Elmacı

https://doi.org/10.24323/akademik-gida.647734

Abstract

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.

Keywords

Supervised pattern recognition, Food analysis, Multivariable data analysis, Image processing, Classification

Denetimli Örüntü Tanıma ve Gıda Analizlerinde Uygulamaları

Abstract

Denetimli örüntü tanıma, sınıflandırma için örnek
kategorisi üyeliği hakkında bir ön bilginin kullanıldığı teknikleri ifade etmektedir.
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 örüntü
tanıma yöntemleri çok çeşitlidir ve asıl önemli nokta en uygun yöntemi
seçmektir. Gıda analizlerinde gıda kalite değerlendirmesi, veri yorumlama gibi
çeşitli amaçlarla farklı verilere uygulamaları bulunmaktadır. Denetimli örüntü
tanıma teknikleriyle incelenen gıdalara örnek olarak şarap, yağ, bal, süt
ürünleri, et, meyveler, içecekler, tahıllar ve balık verilebilir. Bu teknikler
kullanılarak gıdalarda doku analizi, aroma analizi, gıda doğrulaması, gıda
kalitesinin değerlendirilmesi, çoklu element analizi, coğrafi ve botanik kökene
göre sınıflandırma gerçekleştirilebilmektedir. Bu derlemede, denetimli örüntü
tanıma tanımlanmış, uygulama teknikleri özetlenmiş ve gıda analizlerinde
kullanılan örüntü tanıma teknikleri konusunda yapılan çalışmalar ile örneklendirilerek
bilgi verilmiştir. 

Keywords

Denetimli örüntü tanıma, Gıda analizi, Çok değişkenli veri analizi, Görüntü işleme, Sınıflandırma

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