Species discrimination and total polyphenol prediction of porcini mushrooms by fourier transform mid‐infrared (FT‐MIR) spectrometry combined with multivariate statistical analysis

The plateau specialty agricultural products, wild porcini mushrooms, have great value both as a superb cuisine and as a potential medication. Due to quality different between species added with the fraud behavior in sales process, make poor quality or poisonous sample inflow into the market, which p...

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Veröffentlicht in:	Food Science & Nutrition 2020-02, Vol.8 (2), p.754-766
Hauptverfasser:	Li, Xiu‐Ping, Li, Jieqing, Li, Tao, Liu, Honggao, Wang, Yuanzhong
Format:	Artikel
Sprache:	eng
Schlagworte:	Agricultural products Analysis Antioxidants Correlation coefficient Correlation coefficients data fusion Data integration Discriminant analysis Embedding Food quality Fourier analysis Fourier transforms Fraud Fruits FT‐MIR spectroscopy Health risks Infrared analysis Morphology Multisensor fusion Multivariate statistical analysis Mushrooms Original Research Particle swarm optimization Phenols Polyphenols porcini mushroom Prediction models Predictions Principal components analysis Species species discrimination Spectrometry Spectroscopy Statistical analysis Statistical methods Statistical prediction Stipes Support vector machines total polyphenol prediction Variables
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