Progress and Challenge of Sensors for Dairy Food Safety Monitoring.

One of the most consumed foods is milk and milk products, and guaranteeing the suitability of these products is one of the major concerns in our society. This has led to the development of numerous sensors to enhance quality controls in the food chain. However, this is not a simple task, because it is necessary to establish the parameters to be analyzed and often, not only one compound is responsible for food contamination or degradation. To attempt to address this problem, a multiplex analysis together with a non-directed (e.g., general parameters such as pH) analysis are the most relevant alternatives to identifying the safety of dairy food. In recent years, the use of new technologies in the development of devices/platforms with optical or electrochemical signals has accelerated and intensified the pursuit of systems that provide a simple, rapid, cost-effective, and/or multiparametric response to the presence of contaminants, markers of various diseases, and/or indicators of safety levels. However, achieving the simultaneous determination of two or more analytes in situ, in a single measurement, and in real time, using only one working 'real sensor', remains one of the most daunting challenges, primarily due to the complexity of the sample matrix. To address these requirements, different approaches have been explored. The state of the art on food safety sensors will be summarized in this review including optical, electrochemical, and other sensor-based detection methods such as magnetoelastic or mass-based sensors.

Modified lanthanide-doped carbon dots as a novel nanochemosensor for efficient detection of water in toluene and its potential application in lubricant base oils.

A fast and efficient method was developed for obtaining europium(III)-doped surface-modified carbon dots with a hydrophobic coating. This surface functionalization improved the dispersibility of the nanoparticles in non-polar media, as well as modified the accessibility of water molecules to the europium ions. These two features allowed studying the application of doped carbon dots as moisture nanochemosensor, demonstrating high stability over time of both the photoluminescent signal intensity and the stability of the dispersions. The developed nanochemosensor was used to determine water in toluene with a detection limit of 8.5 × 10-4 M and a quantification limit of 2.4 × 10-3 M. The proposed system matches and even improves other methodologies for water determination in organic solvents; it has a low detection limit and a fast response time (almost instantaneous) and requires neither expensive material nor trained personnel. The results suggest a promising future for the development of a new sensing phase for moisture determination in lubricant base oil.

Artificial Intelligence and fourier-transform infrared spectroscopy for evaluating water-mediated degradation of lubricant oils.

The presence of water in lubricant oils is a parameter related to the lubricant deterioration, which can be indicative of a serious loss of tribological efficiency and, therefore, an increase in maintenance costs. Likewise, controlling the aging of the lubricant oil is a keynote issue to prevent damage on the lubricated surfaces (e.g. engine pieces). The combination of Attenuated Total Reflectance (ATR) techniques with Fourier-Transform Infrared Spectrometry (FTIR) result in an easy, simple, fast and non-destructive way for obtaining accurate information about the actual situation of a lubricant oil. The analysis of this ATR-FTIR information using Artificial Neural Networks (ANN) as well as Linear Discriminant Analysis (LDA) results in the proper classification of lubricant oils regarding the presence/absence of water, age and viscosity. The methodology proposed in this work describes procedures for identifying the deterioration degree of oils with as high as 100% success (aging week) or 97.7% (for viscosity and water presence).

Alkyl-capped copper oxide nanospheres and nanoprolates for sustainability: water treatment and improved lubricating performance.

Metal oxide nanoparticles of different nature have been used in different fields such as therapeutics, biomarkers, tribology or environmental remediation, among others. Besides, the surface modification of such nanoparticles is of particular interest to bring designed functions. In this paper we describe the synthesis of CuO nanoparticles with two different geometries (spherical and prolate) and decorated with long alkyl chains in order to use as dye removers by adsorption and/or photo-degradation of a persistent model dye (Congo Red) and as lubricant additives to improve the tribological performance of base lubricant oils. Alkyl-functionalized CuO nanoparticles demonstrated a high stability in oily suspensions and an improvement in the friction reducing the CoF ca. 26%; the alkyl-decorated nanoparticles showed also higher adsorption kinetics for Congo Red than the neat ones following a pseudo-second-order trend, although with lower adsorption efficiency. The synthesis, surface modification and physic-chemical characterization of spherical and prolate CuO nanoparticles are described as well as their applications as lubricant additives and Congo Red photocatalytic removal.

Metabolomic prediction of pregnancy viability in superovulated cattle embryos and recipients with fourier transform infrared spectroscopy.

We analyzed embryo culture medium (CM) and recipient blood plasma using Fourier transform infrared spectroscopy (FTIR) metabolomics to identify spectral models predictive of pregnancy outcome. Embryos collected on Day 6 from superovulated cows in 2 countries were individually cultured in synthetic oviduct fluid medium with BSA for 24 h before embryo transfer. Spent CM, blank controls, and plasma samples (Day 0 and Day 7) were evaluated using FTIR. The spectra obtained were analyzed. The discrimination capability of the classifiers was assessed for accuracy, sensitivity (pregnancy), specificity (nonpregnancy), and area under the ROC curve (AUC). Endpoints considered were Day 60 pregnancy and birth. High AUC was obtained for Day 60 pregnancy in CM within individual laboratories (France AUC = 0.751 ± 0.039, Spain AUC = 0.718 ± 0.024), while cumulative data decreased the AUC (AUC = 0.604 ± 0.029). Predictions for CM at birth were lower than Day 60 pregnancy. Predictions with plasma at birth improved cumulative over individual results (Day 0: France AUC = 0.690 ± 0.044; Spain AUC < 0.55; cumulative AUC = 0.747 ± 0.032). Plasma generally predicted pregnancy and birth better than CM. These first results show that FTIR metabolomics could allow the identification of embryos and recipients with improved pregnancy viability, which may contribute to increasing the efficiency of selection schemes based on ET.

Natural Logarithm Derivative Method: a novel and easy methodology for finding maximums in overlapping experimental peaks.

The method of the First Derivative usually fails to detect overlapped peaks, especially when they appear as shoulders of the main one. Furthermore, the determination of the position of the maximum with this method is based on a single point, and it is highly dependent of the noise level of the experimental data. In this work, we propose an easy method to accurately estimate peak positions, based on a linearization of Gaussian curves. The method, which we called Natural Logarithm Derivative Method (NLDM), is also able to detect to a certain extent overlapping peaks, even when appearing as shoulders. Several factors such as the Lorentzian influence in the peak shape, the experimental error in the numerical calculations, or the minimum separation between peaks in order to be properly resolved are studied. The method is assayed with real samples, demonstrating the possibility of finding overlapping peaks in dyes, and in mixtures of dyes.

Insights into the reaction of beta-lactam antibiotics with copper(II) ions in aqueous and micellar media: kinetic and spectrometric studies.

Degradation of beta-lactam antibiotics by means of metallic cations seems to have a very complex chemistry, involving not only the catalytic effect of the metal ion but also complex formation. Many different compounds, such as methylpyrazines, oxazolones, penicilloic, penicillenic, and penicillonic acids, have been reported as degradation products of such antibiotics, although not many details about the progress of the reaction can be found in the literature. Two novel fluorimetric and spectrophotometric methods previously published by the authors, as well as kinetic studies, have been used to propose a possible reaction mechanism for the ampicillin degradation in the presence of copper(II) ions. Likewise, we have proposed the chemical structure required by the beta-lactam antibiotics to develop absorption or fluorescence properties. Kinetics in micellar and aqueous media shows that the copper-ampicillin reaction proceeds through different pathways depending on the reaction medium.