首页|Researchers from Jadavpur University Report Findings in Biomarkers (A Smart Methodology for Assessment of Hexanal In Potato Crisps Using Electronic Nose Technology: Sensor Screening By Scalar Machine Learning Classifier Method)
Researchers from Jadavpur University Report Findings in Biomarkers (A Smart Methodology for Assessment of Hexanal In Potato Crisps Using Electronic Nose Technology: Sensor Screening By Scalar Machine Learning Classifier Method)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Diagnostics and Screening - Biomarkers have been presented. Accordingto news originating from Kolkata, India, by NewsRx correspondents, research stated, “There is apertinent need to develop a rapid and accurate methodology for the detection of the onset and the progressionof rancidity in the most popular savory product worldwide, viz. fried potato crisps for food safety andhealth concerns. Rancidity in the fried crisps-one set prepared using C18:2-lean deodorized virgin coconutoil under modified deep frying conditions (140 degrees C, 5 min),-and another set deep fried (170 degreesC, 3 min) in C18:2-rich oil (simulating commercial frying conditions) was determined by ‘rancidity indices’generated (using Mahalanobis distance) from the data obtained by MO-based electronic nose analysis ofhexanal (in Likens-Nickerson extract of volatiles from potato crisps), the most prominent rancidity marker,using screened sensors calibrated with standard hexanal, and classified using support vector machine.”
KolkataIndiaAsiaBiomarkersCyborgsDiagnostics and ScreeningEmerging TechnologiesHealth and MedicineMachine LearningTechnologyJadavpur University
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