首页|Sichuan University Reports Findings in Machine Learning (Machine Learning-Assist ed Portable Microplasma Optical Emission Spectrometer for Food Safety Monitoring )
Sichuan University Reports Findings in Machine Learning (Machine Learning-Assist ed Portable Microplasma Optical Emission Spectrometer for Food Safety Monitoring )
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Chengdu, Peo ple's Republic of China, by NewsRx correspondents, research stated, "To meet the needs of food safety for simple, rapid, and low-cost analytical methods, a port able device based on a point discharge microplasma optical emission spectrometer (mPD-OES) was combined with machine learning to enable on-site food freshness e valuation and detection of adulteration. The device was integrated with two modu lar injection units (i.e., headspace solid-phase microextraction and headspace p urge) for the examination of various samples." Our news editors obtained a quote from the research from Sichuan University, "Ar omas from meat and coffee were first introduced to the portable device. The arom a molecules were excited to specific atomic and molecular fragments at excited s tates by room temperature and atmospheric pressure microplasma due to their diff erent atoms and molecular structures. Subsequently, different aromatic molecules obtained their own specific molecular and atomic emission spectra. With the hel p of machine learning, the portabledevice was successfully applied to the asses sment of meat freshness with accuracies of 96.0, 98.7, and 94.7% f or beef, pork, and chicken meat, respectively, through optical emission patterns of the aroma at different storage times. Furthermore, the developed procedures can identify beef samples containing different amounts of duck meat with an accu racy of 99.5% and classify two coffee species without errors, demo nstrating the great potential of their application in the discrimination of food adulteration."
ChengduPeople's Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine Learning
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