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Geological storage of CO2 in basalts provides a new and potentially significant option for carbon capture and storage (CCS). So far, there are only three demonstration projects in the world, namely Nagaoka in Japan, Wallula in the United States of America and Carbfix in Iceland. These examples have confirmed the technical and economic feasibility of geological storage of CO2 in basalts. The main progress achieved on the technology of CO2 capture and storage in basalts are as follows (1) CO2 in flue gas can be better captured by using aqueous solution instead of amine solvent, so that CO2 and other water-soluble gases are easily captured at the same time, while equipment such as scrubbing tower is just simply installed as a gas separation device near the emission point source. (2) The Carbfix method suitable for CO2 saturated solution injection and storage is proposed, and a special system which can inject gas and water solution respectively is designed. (3) In the process of CO2 injection and sequestration, the tracer element monitoring method was firstly adopted, and the percentage of carbonation of CO2 injected was quantitatively estimated by the mass balance method. It was found that at least 95% of basalts were completely mineralized in less than two years after CO2 injection. However, the remain technical problems exist and need to be further studied, which include (1) how to choose the correct injection means between the CO2 saturated and supercritical solutions. (2) Whether sea water can replace fresh water to dissolve CO2. (3) How to improve the accuracy of geochemical simulation of injection and geological storage of CO2 in basalts. (4) How to reduce the cost of carbon capture, separation and transportation. There are still a long way to go before we can effectively deploy such CCS technologies throughout the world.

Milk protein is an important component in milk and dairy products, and its content and composition are important factors influencing the functionality of milk such as nutrition and immunity. Protein components in milk are complex, and the content of different components varies greatly. With the development of functional properties of milk protein, it is of great significance and value to determine the content of milk protein components in a faster and more accurate way. Currently, enzyme-linked immunosorbent assay (ELISA), capillary electrophoresis (CE), high performance liquid chromatography (HPLC) and high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) are the main methods used to determine protein components in milk. In this article, the measurement principle, applicability, and the characteristics of these methods are reviewed, which could provide reliable technical reference for accurate measurement and establishment of a novel method in milk protein evaluation, while this could also be a theoretical support for dairy nutrition research, development of dairy products and infant formula optimization.

The rapid detection of lipid oxidation in frozen pork was carried out by using Raman spectroscopy combined with chemometric methods. Frozen pork stored for 0–360 days was selected in this study, and the regression relationship between acid value or peroxide value and storage time was established by the least squares method. Raman spectra were collected with a portable Raman spectrometer and were preprocessed by Savitzky-Golay with five-point smoothing (SG-5), standard normal variate correction (SNV) or adaptive iteratively re-weighted penalized least squares (airPLS). The partial least square regression (PLSR) was used for modeling and analysis. Then competitive adaptive reweighted sampling (CARS) was used to select the Raman characteristic variables for the best preprocessed spectra to establish a CARS-PLSR model. It was found that the correlation between peroxide value and storage time was more significant during the storage period (P = 0.000 3 < 0.05). The prediction models with spectral preprocessing by using SNV and airPLS performed best. The CARS-PLSR model showed improved prediction performance. The CARS-PLSR models for prediction of acid and peroxide values had the following performance parameters: coefficient of determination for calibration (R2c), 0.88 and 0.84; root mean square error of cross-validation (RMSECV), 0.31 and 2.33; coefficient of determination for prediction (R2p), 0.76 and 0.75; root mean square error of prediction (RMSEP), 0.17 and 1.87, and ratio of performance to deviation (RPD), 2.59 and 1.90, respectively. In conclusion, our results show that the peroxide value of frozen pork is significantly correlated with storage time. The degree of lipid oxidation in frozen pork can be rapidly determined by using Raman spectroscopy.