چکیده مقاله
Food spoilage and contamination pose critical challenges to safety and quality, driven by microbial dynamics and chemical alterations This study employs high resolution Orbitrap mass spectrometry Orbitrap MS integrated with convolutional neural networks CNNs and recurrent neural networks RNNs for real time monitoring of microbial shifts and chemical profiles in perishable foods like dairy and seafood Orbitrap MS achieved resolutions >500,000 FWHM, detecting metabolites at ppb levels, while deep learning models classified microbial genera with 97% accuracy and predicted spoilage timelines within _x0000__x0000__x0000__x0000_ _x0000__x0000__x0000_ _x0000__x0000__x0000__x0000_ _x0000__x0000__x0000__x0000_ _x0000__x0000__x0000__x0000_ _x0000__x0000__x0000__x0000_ _x0000__x0000__x0000__x0000_ _x0000__x0000__x0000__x0000__x0000__x0000__x0000__x0000__x0000__x0000_ _x0000_ _x0000__x0000__x0000__x0000__x0000__x0000__x0000_ _x0000__x0000__x0000__x0000__x0000_ _x0000__x0000__x0000_ 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کلیدواژهها
نویسندگان
Asal Jami Ostadil
Bachelor of Science in Food Hygiene, Faculty of Veterinary Medicine, Islamic Azad University, Science and Research Branch, Tehran, Iran
Kazem Roshani
PhD in Food Technology, Islamic Azad University, North Tehran Branch, Tehran, Iran
Morteza Jamshid Eini
PhD in Food Technology, Islamic Azad University, North Tehran Branch, Tehran, Iran
Behzad Beizaei
PhD student in Food Technology, Islamic Azad University, Tehran Medical Sciences Branch, Tehran, Iran
شیوه ارجاع
Ostadil, Asal Jami and Roshani, Kazem and Jamshid Eini, Morteza and Beizaei, Behzad,1404,Monitoring Microbial Changes and Precise Chemical Profiling of Food Products Using Advanced Mass Spectrometry (Orbitrap-MS) and Deep Learning Systems,The first national conference environment, smart agriculture, food security,Varamin
ارائهشده در
مجموعه مقالات اولین همایش ملی محیط زیست، کشاورزی هوشمند، امنیت غذایی28 آبان 1404 · ورامین