首页|Nanjing University Medical School Reports Findings in Machine Learning [FT-NIR combined with machine learning was used to rapidly detect the adulteratio n of pericarpium citri reticulatae (chenpi) and predict the adulteration concent ration]
Nanjing University Medical School Reports Findings in Machine Learning [FT-NIR combined with machine learning was used to rapidly detect the adulteratio n of pericarpium citri reticulatae (chenpi) and predict the adulteration concent ration]
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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 Nanjing, Peo ple’s Republic of China, by NewsRx correspondents, research stated, “Pericarpium citri reticulatae (PCR) has been used as a food and spice for many years and is known for its rich nutritional content and unique aroma. However, price increas es are often accompanied by adulteration.” Our news editors obtained a quote from the research from Nanjing University Medi cal School, “In this study, two kinds of adulterants (Orange peel-OP and Mandari n Rind-MR) were identified by chromaticity analysis, FT-NIR and machine learning algorithm, and the doping concentration was predicted quantitatively. The resul ts show that colorimetric analysis cannot completely differentiate between PCR a nd adulterants. Using spectral preprocessing combined with machine learning algo rithms, PCR and two adulterants were successfully distinguished, with classifica tion accuracy reaching 99.30 % and 98.64 % respectiv ely. After selecting characteristic wavelengths, the R of the adulterated quanti tative model is greater than 0.99.”
NanjingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine Learning
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