Determining farming methods and geographical origin of chinese rice using NIR combined with chemometrics methods

This study was conducted to develop fast and nondestructive models for the discrimination of different farming methods determine geographical origin rice samples from administrative regions in China using near-infrared (NIR) spectroscopy. Principal component analysis (PCA) partial least squares discriminant (PLS-DA) were applied build NIR spectral models. Norris smoothing derivative (NSD) multiplicative scatter correction (MSC) used as preprocessing reduce noise enhance effective information. The results show that it difficult distinguish with original spectra plots PCA score except Heilongjiang Province. In addition, a PLS-DA model combined NSD provided optimal predictive accuracy 89.7% identification methods. or MSC best traceability. total Northeast 100%, South, East, Central Southwest 98.2%. Heilongjiang, Anhui, Jiangsu, Hubei, Sichuan Provinces 98.8%, 95.3%, 93.6%, respectively. These indicate can provide powerful method Chinese rice.