Sensing Technology for Fish Freshness and Safety: A Review.

Standard analytical methods for fish freshness assessment are based on the measurement of chemical and physical attributes related to fish appearance, color, meat elasticity or texture, odor, and taste. These methods have plenty of disadvantages, such as being destructive, expensive, and time consuming. All these techniques require highly skilled operators. In the last decade, rapid advances in the development of novel techniques for evaluating food quality attributes have led to the development of non-invasive and non-destructive instrumental techniques, such as biosensors, e-sensors, and spectroscopic methods. The available scientific reports demonstrate that all these new techniques provide a great deal of information with only one test, making them suitable for on-line and/or at-line process control. Moreover, these techniques often require little or no sample preparation and allow sample destruction to be avoided.

A Non-Invasive Soil Moisture Sensing System Electronic Architecture: A Real Environment Assessment.

This paper will show the electronic architecture of a portable and non-invasive soil moisture system based on an open rectangular waveguide. The spectral information, measured in the range of 1.5-2.7 GHz, is elaborated on by an embedded predictive model, based on a partial least squares (PLS) regression tool, for the estimation of the soil moisture (%) in a real environment. The proposed system is composed of a waveguide, containing Tx and Rx antennas, and an electronic circuit driven by a microcontroller (MCU). It will be shown how the system provides a useful and fast estimation of moisture on a silty clay loam soil characterized by a moisture range of about 9% to 32% and a soil temperature ranging from about 8 °C and 18 °C. Using the PLS approach, the moisture content can be predicted with an R2 value of 0.892, a root mean square error (RMSE) of 1.0%, and a residual prediction deviation (RPD) of 4.3. The results prove that it is possible to make accurate and rapid moisture assessments without the use of invasive electrodes, as currently employed by state-of-the-art approaches.

Real-time gas mass spectroscopy by multivariate analysis.

Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical technique. Even if the presented physical implementation could be used with gas chromatography columns, the aim of high miniaturization requires investigating its detection performance with no aid. As a study case, in the first experiment, dichloromethane (CH2Cl2) and cyclohexane (C6H12) with concentrations in the 6-93 ppm range in single and compound mixtures were used. The nano-orifice column-free approach acquired raw spectra in 60 s with correlation coefficients of 0.525 and 0.578 to the NIST reference database, respectively. Then, we built a calibration dataset on 320 raw spectra of 10 known different blends of these two compounds using partial least square regression (PLSR) for statistical data inference. The model showed a normalized full-scale root-mean-square deviation (NRMSD) accuracy of [Formula: see text] and [Formula: see text] for each species, respectively, even in combined mixtures. A second experiment was conducted on mixes containing two other gasses, Xylene and Limonene, acting as interferents. Further 256 spectra were acquired on 8 new mixes, from which two models were developed to predict CH2Cl2 and C6H12, obtaining NRMSD values of 6.4% and 13.9%, respectively.