Study on the identification for quality of mushrooms by Fourier Transform near infrared spectroscopy (FT-NIR) technology

• Main Authors: Yu-Hsin Chen, 陳譽心
• Other Authors: Yu-Shun Chen
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/33316501929511868405

碩士 === 弘光科技大學 === 食品科技所 === 102 === The FT-NIR (Fourier Transform near infrared spectroscopy) has characteristics on real-time, nondestructive character, on-site detection, including physical properties and chemical compositions can be detected simultaneously. FT-NIR can be used on qualitative or quantitative analysis or other raw materials of food. General commercial mushroom health food, more use shaped objects when maltodextrin, and maltodextrin are also rich in polysaccharide component. In addition, Pleurotus eryngii itself is easily to get and cost cheaper, also rich in polysaccharide component, compared with the general edible and medicinal mushrooms, will be mix in process, to deceive consumers. The aim of technique can be applied on health food industry, for avoiding passing off fish eyes as pearls with the regression analysis to establish statistical software calibration equation, and identify components of mushrooms and functional analysis of class composition analysis. In this study, Ganoderma lucidum , Cordyceps militaris, Agaricus blazei Murill, Antrodia cinnamomea classes were mixed in different proportions with mushroom maltodextrin to be analyzed by FT-NIR qualitative and quantitative, after scanning analysis, selection of optimal statistical software system to analyze the chemical composition of the sample spectral data correlation, and the unknown object has the best predictive ability. The results after software statistics, forecasts and verification of its effect coefficient of determination R2 up to 95%, standard error of calibration (SEC) and standard error of prediction (SEP) were less than 5%. In general, the advantages of FT-NIR showed real-time, differentiated identification of unknow components, simultaneously and continuously measurement of spectral data. So as establish the health food industry quickly and in a non-destructive analytical methods for environmental quality as an alternative to traditional detection analysis.And also to consumer checks.