VEŠTAČKE NEURONSKE MREŽE ZA PREDVIĐANJE KVALITETA RAZLIČITIH GENOTIPOVA PARADAJZA

  • Mladenka Pestorić Univerzitet u Novom Sadu, Naučni institut za prehrambene tehnologije, Novi Sad
  • Јаsna Маstilović Univerzitet u Novom Sadu, Naučni institut za prehrambene tehnologije, Novi Sad
  • Žarko Кеvrešan Univerzitet u Novom Sadu, Naučni institut za prehrambene tehnologije, Novi Sad
  • Lato Pezo Univerzitet u Beogradu, Institut za opštu i primenjenu fiziku, Beograd
  • Miona Belović FINS Novi Sad
  • Svetlana Glogovac Institut za ratarstvo i povrtarstvo, Novi Sad
  • Dubravka Škrobot Univerzitet u Novom Sadu, Naučni institut za prehrambene tehnologije, Novi Sad
  • Nebojša Ilić Univerzitet u Novom Sadu, Naučni institut za prehrambene tehnologije, Novi Sad
  • Adam Takač Institut za ratarstvo i povrtarstvo, Novi Sad
Ključne reči: kvalitet svežeg paradajza, senzorska ocena, fizičko-hemijska svojstva, model veštačkih neuronskih mreža

Sažetak


Senzorska analiza predstavlja najbolje sredstvo za precizno opisivanje kvaliteta svežih namirnica. Međutim, to je skupa i dugotrajna metoda koja se ne može koristiti za merenje pokazatelja kvaliteta u realnom vremenu. Cilj ovog rada bio je da doprinese proučavanju odnosa između podataka dobijenih primenom senzorske analize i instrumentalnih metoda i da definiše odgovarajući model za predviđanje senzorskih svojstava svežeg paradajza pomoću određivanja fizičko-hemijskih svojstava. Analiza glavnih komponenti (PCA) primenjena je na eksperimentalne podatke da bi se okarakterisali i diferencirali posmatrani genotipovi, objašnjavajući 73,52% od ukupne varijanse, koristeći prve tri glavne komponente. Model veštačke neuronske mreže (ANN) korišćen je za predviđanje senzorskih svojstava na osnovu rezultata dobijenih osnovnim hemijskim i instrumentalnim određivanjima. Razvijeni ANN model predviđa senzorska svojstva sa visokom adekvatnošću, sa ukupnim koeficijentom determinacije od 0,859.

Biografija autora

Miona Belović, FINS Novi Sad
Naučni saradnik

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2021/02/10
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