Library transfer between distinct Laser-Induced Breakdown Spectroscopy systems with shared standards

The mutual incompatibility of distinct spectroscopic systems is among the most limiting factors in Laser-Induced Breakdown Spectroscopy (LIBS). The cost related to setting up a new LIBS system is increased, as its extensive calibration is required. Solving the problem would enable inter-laboratory reference measurements and shared spectral libraries, which are fundamental for other spectroscopic techniques. In this work, we study a simplified version of this challenge where LIBS systems differ only in used spectrometers and collection optics but share all other parts of the apparatus, and collect spectra simultaneously from the same plasma plume. Extensive datasets measured as hyperspectral images of heterogeneous specimens are used to train machine learning models that can transfer spectra between systems. The transfer is realized by a pipeline that consists of a variational autoencoder (VAE) and a fully-connected artificial neural network (ANN). In the first step, we obtain a latent representation of the spectra which were measured on the Primary system (by using the VAE). In the second step, we map spectra from the Secondary system to corresponding locations in the latent space (by the ANN). Finally, Secondary system spectra are reconstructed from the latent space to the space of the Primary system. The transfer is evaluated by several figures of merit (Euclidean and cosine distances, both spatially resolved; k-means clustering of transferred spectra). The methodology is compared to several baseline approaches.Comment: 32 pages, 22 figure

Chemical, physical and technological properties of milk as affected by the mycotoxin load of dairy herds

The aim of the study was to determine the impacts of different levels of mycotoxin load of Czech dairy herds on the larger scale of the milk indicators including milk physical and technological properties. During three subsequent years individual milk samples (IMSs) were collected from four herds of Czech Fleckvieh (C) and from four herds of Holstein cows (H). The IMSs were collected regularly twice in summer and twice in winter, resulting in a total of 936 IMSs. The feeding rations consisted mainly of conserved roughage and supplemental mixtures according to milk yield and standard demands. Samples of feedstuffs were collected at the same time as IMSs and were analysed for content of deoxynivalenol (DON), fumonisins (FUM), zearalenone (ZEA), aflatoxin (AFL), and T-2 toxin using enzyme-linked immunosorbent assay (ELISA) methods. Based on the mycotoxin load, herds were divided into three groups – Load 1 (negligible, <i>n</i> =  36), Load 2 (low, <i>n</i> =  192), and Load 3 (medium, <i>n</i> =  708). All feedstuff samples were positive for at least one mycotoxin. The most frequently occurring mycotoxins were FUM, DON, and ZEA. Relatively high incidence of AFL (56 % positive samples) was observed. The following milk indicators were influenced by the mycotoxin load of herds: fat, acetone (Ac), log Ac, pH, electric conductivity, alcohol stability, curds quality, curd firmness, whey volume, whey protein, non-protein nitrogen (NPN), urea N in NPN, fat ∕ crude protein ratio, and casein numbers on crude and true protein basis, respectively (<i>P</i> &lt; 0.05). The overall level of mycotoxin load was relatively low, with no clear effect on milk characteristics