Liu Muhua

Qualitative identification of tea by near infrared spectroscopy based on soft independent modelling of class analogy pattern recognition

Near-infrared (NIR) spectroscopy has been successfully utilised for the rapid identification of tea varieties. The spectral features of each tea category are reasonably differentiated in the NIR region and the spectral differences provided enough qualitative spectral information for identification. Soft independent modelling of class analogy (SIMCA) as the pattern recognition was applied in this paper. In this study, both α-error (i.e. the rejection of correct samples from their class) and β-error (i.e. the acceptance of objects that do not belong to that class) are focused on. Four tea classes from Longjing tea, Biluochun tea, Qihong tea and Tieguanyin tea were modelled separately by principal component analysis (PCA). The results showed that at the 99% confidence level, the α-errors were equal to 0.1 only for the Longjing tea class when training and 0.2 only for the Biluochun tea class when testing, while the remaining α-errors and all β-errors were equal to zero. The study demonstrated that NIR spectroscopy technology with a SIMCA pattern recognition method can be successfully applied as a rapid method to identify the class of tea.

Non‐destructive estimation peach SSC and firmness by mutispectral reflectance imaging

Abstract Mutispectral reflectance imaging combined with multi‐linear analysis appears as a new, efficient and cheap method for detecting soluble solids content (SSC) and firmness of peach. Six hundred spectral images from a combination of filter 632, 650, 670, 780, 850, and 900 nm were acquired for each peach sample. The Lorentzian distribution (LD), Gaussian distribution (GD) and Exponential distribution (ED) with three parameters were used to fit scattering profiles of each spectral imaging. LD was found to be the best function for fitting gray distribution of imaging. The multi‐linear regression model was developed relating Lorentzian parameters to fruit firmness and SSC using a single wavelength, double wavelengths, three wavelengths and four wavelengths respectively. The best model with four wavelengths was able to predict peach flesh firmness with r = 0.949, standard error of prediction (SEP) = 1.56 N, and predict peach SSC with r = 0.970, SEP = 0.69° Bnx. Results show that the multispectral scattering imaging is anon‐destructive, fast and cheap method for estimating fruit SSC and firmness.

Discrimination of Ca, Cu, Fe, and Na in Gannan Navel Orange by Laser Induced Breakdown Spectroscopy

Laser induced breakdown spectroscopy (LIBS) has become a powerful tool for the direct analysis of a large variety of materials in order to provide qualitative and/or quantitative information. However, there is a lack of information for LIBS analysis of agricultural products. In this work a LIBS system has been designed for the discrimination of Ca, Cu, Fe, and Na elements in Gannan Navel orange. An experimental setup was established by using a Nd:YAG laser operating at 1064 nm and a grating spectrometer with CCD detector. The LIBS spectra of pericarps and fleshes of Gannan Navel orange were collected. The typical spectrum lines of mineral elements Ca,Cu,Fe,and Na were chosen and identified, and the relative content of four elements in pericarps and fleshes were compared and analyzed respectively. The results showed that the relative content of elements Ca,Cu,Fe,and Na in pericarps was more than in fleshes. The LIBS relative intensity of Na、Fe、Ca、Cu elements in pericarps decreased in turn, while the LIBS relative intensity of Na 、Cu 、 Ca 、Fe elements in fleshes increased in turn. The experimental results also showed that the relative content of mineral elements in farm product may be analyzed fast by LIBS, and the LIBS technique is a novel means for rapid detection the quality of farm product.Laser induced breakdown spectroscopy (LIBS) has become a powerful tool for the direct analysis of a large variety of materials in order to provide qualitative and/or quantitative information. However, there is a lack of information for LIBS analysis of agricultural products. In this work a LIBS system has been designed for the discrimination of Ca, Cu, Fe, and Na elements in Gannan Navel orange. An experimental setup was established by using a Nd:YAG laser operating at 1064 nm and a grating spectrometer with CCD detector. The LIBS spectra of pericarps and fleshes of Gannan Navel orange were collected. The typical spectrum lines of mineral elements Ca,Cu,Fe,and Na were chosen and identified, and the relative content of four elements in pericarps and fleshes were compared and analyzed respectively. The results showed that the relative content of elements Ca, Cu, Fe, and Na in pericarps was more than in fleshes. The LIBS relative intensity of Na, Fe, Ca, Cu elements in pericarps decreased in turn, while the LIBS relative intensity of Na, Cu, Ca, Fe elements in fleshes increased in turn. The experimental results also showed that the relative content of mineral elements in farm product may be analyzed fast by LIBS, and the LIBS technique is a novel means for rapid detection the quality of farm product.