Rationale:Authentication of fish is of importance in the view of toxins, allergen warnings and economic fraud control. Traditional methods in the authentication of fish, e.g. morphological, genetic and proteomic analysis, are either at low throughput or at high-cost. Methods:A high-throughput matrix-assisted laser desorption/ionization time-offlight mass spectrometry (MALDI TOF MS)-based approach was developed to analyze biomaterials from fish skin, and mass spectra from different fish species were compared by chemometric methods to differentiate fish species.Results: A total of 51 fish samples were used to generate more than 150 fingerprinting mass spectra. The fish belonging to the same genus can be identified at species level. A mass spectral database of different fishes can be built as reference for authentication. The analysis can be performed based on micrograms of fish-skin sample and accomplished in 1-3 hours. Conclusions:The developed strategy holds potential to be applied to fish authentication in the fishing industry and as a scientific method to avoid mislabeling. It has promise to be practically used for fast and effective identification of closely related fish species to guarantee the quality of fishery products to consumers.
The accurate estimation of nearshore bathymetry is necessary for multiple aspects of coastal research and practices. The traditional shipborne single-beam/multi-beam echo sounders and Airborne Lidar bathymetry (ALB) have a high cost, are inefficient, and have sparse coverage. The Satellite-derived bathymetry (SDB) method has been proven to be a promising tool in obtaining bathymetric data in shallow water. However, current empirical SDB methods for multispectral imagery data usually rely on in situ depths as control points, severely limiting their spatial application. This study proposed a satellite-derived bathymetry method without requiring a priori in situ data by merging active and passive remote sensing (SDB-AP). It realizes rapid bathymetric mapping with only satellite remotely sensed data, which greatly extends the spatial coverage and temporal scale. First, seafloor photons were detected from the ICESat-2 raw photons based on an improved adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which could calculate the optimal detection parameters for seafloor photons by adaptive iteration. Then, the bathymetry of the detected seafloor photons was corrected because of the refraction that occurs at the air–water interface. Afterward, the outlier photons were removed by an outlier-removal algorithm to improve the retrieval accuracy. Subsequently, the high spatial resolution (0.7 m) ICESat-2 derived bathymetry data were gridded to match the Sentinel-2 data with a lower spatial resolution (10 m). All of the ICESate-2 gridded data were randomly separated into two parts: 80% were employed to train the empirical bathymetric model, and the remaining 20% were used to quantify the inversion accuracy. Finally, after merging the ICESat-2 data and Sentinel-2 multispectral images, the bathymetric maps over St. Thomas of the United States Virgin Islands, Acklins Island in the Bahamas, and Huaguang Reef in the South China Sea were produced. The ICESat-2-derived results were compared against in situ data over the St. Thomas area. The results showed that the estimated bathymetry reached excellent inversion accuracy and the corresponding RMSE was 0.68 m. In addition, the RMSEs between the SDB-AP estimated depths and the ICESat-2 bathymetry results of St. Thomas, Acklins Island, and Huaguang Reef were 0.96 m, 0.91 m, and 0.94 m, respectively. Overall, the above results indicate that the SDB-AP method is effective and feasible for different shallow water regions. It has great potential for large-scale and long-term nearshore bathymetry in the future.
The potential of Brillouin scattering lidar for detecting the mixed layer depth (MLD) was studied. We simulated the Brillouin scattering lidar signal in various water environmental parameters and developed an MLD retrieval model for Brillouin scattering lidar data. We first analyzed the theoretical maximum detectable depth for Brillouin scattering lidar in low-latitude sea regions based on the multiple scattering lidar equations. Subsequently, a theoretical method for calculating the Brillouin scattering frequency shift and linewidth was derived based on the international thermodynamic equation of seawater-2010 and the coupled wave equations. Then we used the theoretical method and the temperature-salinity (T-S) profile of the global Argo data in low-latitude regions to simulate the vertical profile distribution of the Brillouin scattering frequency shift and linewidth. Furthermore, we used a maximum angle method to estimate the ocean MLD in low-latitude regions based on the vertical profile distribution of the Brillouin scattering frequency shift and density in seawater. They are well correlated, which indicates that the frequency-shift component of the Brillouin scattering lidar signal for estimating ocean MLD is feasible and reliable. It appears that airborne or spaceborne Brillouin scattering lidar technology provides great potential for high-efficiency, large-area, and long-term monitoring of the global ocean MLD and upper-ocean water bodies.
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