Prediction of Peking duck intramuscle fat content by near-infrared spectroscopy.

Peking duck is the most representative of the meat-type duck breed, and it is also one of the most popular meats in Asia. Few studies were reported on the fast assessment of duck meat quality. This study aimed to develop a fast measuring of duck fat content by using the near-infrared spectroscopy (NIRS) method. We measured 273 duck breast muscle intramuscle fat (IMF) content and spectra. Partial least-squares regression (PLSR) was used to model the fat content prediction by using the spectra in the wavelengths between 950 and 1650 nm. The best predictive abilities were obtained after the first derivative pretreatment, with coefficient of calibration (R2C) of 0.92, with coefficient of prediction (R2P) of 0.90, ratio performance to deviation (RPD) of 2.72, and ratio of error range (RER) of 15.45, for samples of 30 g duck. Results demonstrated that the near-infrared spectroscopy is a useful tool for fat content assessment of Peking duck meat.

[Nondestructive analysis of protein and fat in whole-kernel soybean by NIR].

Near-infrared diffusion reflectance spectroscopy is a fast technique that can provide component information about intact soybean samples. We have combined this technique with partial least-squares (PLS) regression to perform a quantitative determination of protein and fat contents in soybean samples. In calibration set, the NIR model determination coefficient R2 of protein and fat is 0.9930 and 0.9752 respectively, and the relative standard deviation (RSD) is 0.76% and 1.3% respectively. The correlation coefficient r of validation set is 0.9473 and 0.8695 respectively. This NIR model is used to predict the contents of protein and fat in 264 soybean samples, using R-error to assess the deviation of analysis results. The minimum RSD of prediction of protein and fat is 0.04% and 2.46% respectively, and the maximum RSD of prediction of protein and fat is 2.45% and 4.25% respectively. These results are of great importance in early screening of crop breeding.

[A basic research to share Fourier transform near-infrared spectrum information resource].

A method to share the information resource in the database of Fourier transform near-infrared(FTNIR) spectrum information of agricultural products and utilize the spectrum information sufficiently is explored in this paper. Mapping spectrum information from one instrument to another is studied to express the spectrum information accurately between the instruments. Then mapping spectrum information is used to establish a mathematical model of quantitative analysis without including standard samples. The analysis result is that the relative coefficient r is 0.941 and the relative error is 3.28% between the model estimate values and the Kjeldahl's value for the protein content of twenty-two wheat samples, while the relative coefficient r is 0.963 and the relative error is 2.4% for the other model, which is established by using standard samples. It is shown that the spectrum information can be shared by using the mapping spectrum information. So it can be concluded that the spectrum information in one FTNIR spectrum information database can be transformed to another instrument's mapping spectrum information, which makes full use of the information resource in the database of FTNIR spectrum information to realize the resource sharing between different instruments.