Rapid Determination of Unsaturated Fatty Acids in Vegetable Oil by Raman Spectroscopy and Chemometrics

The application of emerging technologies for the quality and safety evaluation of oilseeds and edible oils

Oilseeds and edible oils are an indispensable part for the human diet and provide nutritional support for the human health. It has been reported a total of above 170 million tons per annum of edible oils consumption were consumed worldwide. Safety and quality of oilseeds and edible oils cannot be ignored, which can pose risk to human health and cause agro-economic loss. Classical techniques widely used to detect the safety and quality attributes of oilseeds and edible oils often involve time-consuming and tedious operation; therefore, the development of low cost, rapid and non-destructive detection method is necessary. This review presents applications of four emerging spectroscopic techniques in recent ten years, such as Raman spectroscopy, fluorescence spectroscopy, fourier transform infrared spectroscopy and near-infrared spectroscopy for determining the quality and safety of oilseeds and edible oils. Meanwhile, the technical challenges and future prospects of these non-destructive spectroscopic technologies are also discussed.

Rice Origin Tracing Technology Based on Fluorescence Spectroscopy and Stoichiometry

The origin of agricultural products is crucial to their quality and safety. This study explored the differences in chemical composition and structure of rice from different origins using fluorescence detection technology. These differences are mainly affected by climate, environment, geology and other factors. By identifying the fluorescence characteristic absorption peaks of the same rice seed varieties from different origins, and comparing them with known or standard samples, this study aims to authenticate rice, protect brands, and achieve traceability. The study selected the same variety of rice seed planted in different regions of Jilin Province in the same year as samples. Fluorescence spectroscopy was used to collect spectral data, which was preprocessed by normalization, smoothing, and wavelet transformation to remove noise, scattering, and burrs. The processed spectral data was used as input for the long short-term memory (LSTM) model. The study focused on the processing and analysis of rice spectra based on NZ-WT-processed data. To simplify the model, uninformative variable elimination (UVE) and successive projections algorithm (SPA) were used to screen the best wavelengths. These wavelengths were used as input for the support vector machine (SVM) prediction model to achieve efficient and accurate predictions. Within the fluorescence spectral range of 475-525 nm and 665-690 nm, absorption peaks of nicotinamide adenine dinucleotide (NADPH), riboflavin (B2), starch, and protein were observed. The origin tracing prediction model established using SVM exhibited stable performance with a classification accuracy of up to 99.5%.The experiment demonstrated that fluorescence spectroscopy technology has high discrimination accuracy in tracing the origin of rice, providing a new method for rapid identification of rice origin.

Error analysis of the spectral shift for partial least squares models in Raman spectroscopy

Raman spectroscopy paired with the partial least squares (PLS) method is commonly used for quantitative or qualitative analysis of complex samples. However, spectral shift induced by different Raman spectroscopy, different environment or different measured time will decrease the accuracy of the PLS model. In this work, the processing algorithms that improve the accuracy by removing the noise, background and varying sources of other spectral interference were first reviewed. The error induced by the spectral shift was analyzed and the formulas of the error were derived. The formulas were then used to calculate the theoretical error in the example of discriminating human and nonhuman blood. A comparison of the actual errors obtained from the mathematical method and experiment with the theoretical value demonstrated the effectiveness of the equation. The compensation for nonhuman blood according to the average error demonstrated the improvement of the accuracy. Finally, the non-uniform sampling of the Raman shift by charge-coupled device (CCD) was considered in the error equation. An accurate error equation was obtained. This work could help improve the stability of PLS models in the case of the spectral shift of the spectrometer in Raman spectroscopy.