Determination of Cell Abundances and Paralytic Shellfish Toxins in Cultures of the Dinoflagellate Gymnodinium catenatum by Fourier Transform Near Infrared Spectroscopy

Abstract

Harmful algal blooms are responsible worldwide for the contamination of fishery resources, with potential impacts on seafood safety and public health. Most coastal countries rely on an intense monitoring program for the surveillance of toxic algae occurrence and shellfish contamination. The present study investigates the use of near infrared (NIR) spectroscopy for the rapid in situ determination of cell concentrations of toxic algae in seawater. The paralytic shellfish poisoning (PSP) toxin-producing dinoflagellate Gymnodinium catenatum was selected for this study. The spectral modeling by partial least squares (PLS) regression based on the recorded NIR spectra enabled the building of highly accurate (R2 = 0.92) models for cell abundance. The models also provided a good correlation between toxins measured by the conventional methods (high-performance liquid chromatography with fluorescence detection (HPLC-FLD)) and the levels predicted by the PLS/NIR models. This study represents the first necessary step in investigating the potential of application of NIR spectroscopy for algae bloom detection and alerting.

Fast Detection of Diarrhetic Shellfish Poisoning Toxins in Mussels Using NIR Spectroscopy and Improved Twin Support Vector Machines

“…This is because while feeding on toxin-producing algae, mussels can accumulate DSP toxins in their soft tissues. In mussels, a complex set of reactions produces, including metabolic and detoxification processes (Lopes et al, 2018). The DSP toxins have lipophilic properties and tend to accumulate in the adipose tissues.…”

Thickness Variation Characteristics of Tidal Rhythmites—An Example From the Pinghu Formation, Xihu Sag, East China Sea Shelf Basin

“…The linewidth of image information acquisition was measured in PIX units (i.e., pixels), and an appropriate linewidth of the filter kernel was set. When the filter kernel is set too small, the resolution is higher, but it is easily interfered by local factors in the measurement path, such as 1pix (Figure 4); when the filter core is set too large, the influence of the background blot noise can be reduced, and the signal of high-resolution lamination is easily lost, such as 5pix, 7pix, 9pix, and 11pix (Figure 4) (Yi et al, 2010;Wu et al, 2012;Yi, 2012;Lopes et al, 2018). The filter core is generally set as an odd number, but the 1pix filter kernel does not have the filter denoising function (Figure 4).…”

Near infrared spectroscopy: a method for the monitoring and management of the commercial exploitation of the brown mussel (Perna perna) in southeastern Brazil

“…The consumption of contaminated foods can cause adverse effects on human health (Stankovic et al, 2012). Near Infrared Spectroscopy (NIRS) is one of the tools that has been used to estimate food quality parameters and energy storage and consumption in bivalves (Fluckiger et al, 2011;Bartlett et al, 2018), as well as monitoring marine toxins (Lopes et al, 2018), and differentiating mollusk species obtained from both the field and captive stocks (Valladares et al, 2021). The spectroscopic technology of NIRS evaluates molecular vibrations based on the combination of covalent bonds, such as -CH, -NH, -OH, and -SH, referring to the chemical composition of the material, being able to differentiate among apparently identical samples.…”

“…The spectroscopic technology of NIRS evaluates molecular vibrations based on the combination of covalent bonds, such as -CH, -NH, -OH, and -SH, referring to the chemical composition of the material, being able to differentiate among apparently identical samples. The physical composition, for example shape and size, also influences the analysis, affecting the way that the energy is reflected from the sample (Siesler et al, 2008;Lopes et al, 2018;Williams et al, 2019). A NIRS spectrum thus provides by a computer both qualitative and quantitative data that can be used to compile the chemical phenotype of a sample.…”