Fuzzy Logic Modeling of Yoghurt Incubation

Year 2022, Volume: 19 Issue: 1, 167 - 176, 28.06.2022

Hüseyin Nail Akgül Filiz Yıldız-akgül Ayşe Demet Karaman

https://doi.org/10.25308/aduziraat.1119592

Abstract

Yoghurt production was modeled in this study based on different incubation temperatures, inoculum ratio of starter culture and incubation times. Experimental yoghurts were produced in two replicates and incubation final pH values of 343 yoghurt samples were determined. Resultant pH values were used in fuzzy logic modeling system. Fuzzy logic modelling was conducted in two sections: fuzzy rules were set and membership function was generated in the first section and defuzzification was conducted in the second section. Three different fuzzy sets (triangle membership function) were used for fuzzification of incubation temperature, inoculum ratio of culture and incubation time values. Since there were 7 membership functions of input parameters, 343 (7 x 7 x 7) rows of rule were generated. Mamdani method was used to tabulate fuzzy rules. Three trapezoidal sections of membership functions generated for defuzzification were used and membership function values were determined with the use of weighted average method. Incubation final pH values of 343 samples were assessed in modeling study and model outputs were compared with the expert decisions. Matlab (R2016b) software was used to assess model performance and model general performance was calculated as 90.27%. Automated yoghurt production lines should be designed in the future and put into service of food industry for present model to be used in industrial scale

Keywords

yoghurt, fuzzy logic, artificial intelligence, automation

Supporting Institution

Aydın Adnan Menderes Üniversitesi Bilimsel Araştırma Projeleri Başkanlığı

Project Number

KOMYO-17001

Thanks

Authors express their thanks to ADU-BAP for financial support and also thanks to TARBİYOMER for facilities of laboratory.

Bulanık Mantık ile Yoğurt İnkübasyonunun Modellenmesi

Abstract

Bu çalışmada farklı inkübasyon sıcaklıkları, starter kültür inokülasyon oranı ve inkübasyon süreleri baz alınarak yoğurt üretimi modellenmiştir. Deneme yoğurtları iki tekerrürlü olarak üretilmiş ve 343 yoğurt örneğinin inkübasyon sonundaki pH değerleri belirlenmiştir. Elde edilen pH değerleri bulanık mantık modelleme sisteminde kullanılmıştır. Bulanık mantık modellemesi iki bölümde gerçekleştirilmiştir: birinci bölümde bulanık kurallar belirlenmiş ve üyelik fonksiyonu oluşturulmuş, ikinci bölümde berraklaştırma yapılmıştır. İnkübasyon sıcaklığı, kültür inokülasyon oranı ve inkübasyon süresi değerlerinin bulanıklaştırılması için üç ayrı bulanık küme (üçgen üyelik fonksiyonu) kullanılmıştır. Girdi parametrelerinin 7 üyelik fonksiyonu olduğu için 343 (7 x 7 x 7) satırlık kural oluşturulmuştur. Bulanık kurallar tablosu için Mamdani yöntemi kullanılmıştır. Berraklaştırma için oluşturulan üyelik fonksiyonlarının üç yamuk alanı kullanılmış ve ağırlıklı ortalama yöntemi kullanılarak üyelik fonksiyonu değerleri belirlenmiştir.Modelleme çalışmasında 343 örneğin inkübasyon sonundaki pH’ları değerlendirilmiş ve model çıktıları uzman kararları ile karşılaştırılmıştır. Model performansını değerlendirmek için Matlab (R2016b) yazılımı kullanılmış ve model genel performansı %90.27 olarak hesaplanmıştır. Gelecekte otomatik yoğurt üretim hatlarının tasarlanarak gıda sektörünün hizmetine sunulması düşünülmektedir.

Keywords

yoğurt, bulanık mantık, yapay zeka, otomasyon

Project Number

KOMYO-17001

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