Fu Xp

Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits

Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) regression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 °Brix.

Quality determination of Chinese rice wine based on Fourier transform near infrared spectroscopy

To evaluate the applicability of near infrared (NIR) spectroscopy for the determination of five enological parameters (alcoholic degree, pH value, total acid, amino acid nitrogen and °Brix) in Chinese rice wine, transmission spectra were collected in the spectral range from 800 nm to 2500 nm in a 1 mm path length rectangular quartz cuvette with air as the reference at room temperature. Five calibration equations for the enological parameters were established between the reference data and NIR spectra by partial least squares (PLS) regression, separately. The best calibration results were achieved for the determination of alcoholic degree and °Brix. The coefficients of determination in calibration (R2cal) for alcoholic degree and °Brix were 0.93 and 0.96, respectively. The predictive deviation ratio (RPD) value of the calibration for alcoholic degree was higher than 3 (3.95), which demonstrated the robustness of the calibration model. The RPD value for °Brix was 2.34. The performance of the calibration models for pH, total acid and amino acid nitrogen were not as good as that of alcoholic degree and °Brix. The RPD values for the three parameters were 1.41, 1.38 and 1.27, respectively and R2cal values were 0.97, 0.83 and 0.90, respectively. In the validation step, r2val values for alcoholic degree and °Brix were all higher than 0.9. The performance of pH and total acid were acceptable [the coefficients of determination in validation (r2val) for pH and total acid were 0.82 and 0.77, respectively]. The performance of amino acid nitrogen model was the worst, with an r2val value of 0.62. The results demonstrated that the NIR spectroscopic technique could be used to predict the concentrations of these five enological parameters in Chinese rice wine.