Dielectric spectroscopy of Baijiu over 2-20 GHz using an open-ended coaxial probe

Dielectric relaxation parameters combing raw milk compositions to improve the prediction performance of milk somatic cell count

BACKGROUND

Milk somatic cell count (SCC) is an international standard for identifying mastitis in dairy cows and measuring raw milk quality. Milk SCC can be predicted based on dielectric relaxation parameters (DRPs). We noted a high correlation between DRPs and the milk composition content (MCC), and so we hypothesized that combining DRPs with MCC could improve the prediction accuracy of milk SCC. The present study aimed to analyze the relationship between milk SCC, DRPs and MCC, as well as to investigate the potential of combining DRPs with MCC to improve the prediction accuracy of milk SCC.

RESULTS

The dielectric spectra (20-4500 MHz) of 276 milk samples were measured, and their DRPs (εl, εh, Δε, τ and σ) were solved by the modified Debye equation. The SCC prediction models were developed using dielectric full spectra, DRPs and DRPs combined with MCC. The results showed the correlations between DRPs (εl, εh, Δε and σ) and MCC (fat, protein, lactose and total solids) were high, and SCC exhibited a non-linear relationship with DRPs and MCC. The 5DRPs + MCC-generalized regression neural network model had the best prediction, with a standard error of prediction for prediction of 0.143 log SCC mL-1 and residual of the prediction bias of 2.870, which was superior to the models based on full spectra, DRPs and near-infrared or visible/near-infrared.

CONCLUSION

The present study has improved the prediction accuracy of milk SCC based on the DRPs combing MCC and provides a new method for dairy farming and milk quality assessment. © 2024 Society of Chemical Industry.

Review of scientific instruments: Evaluation of adulteration in honey using a microwave planar resonator sensor

A microwave microstrip line resonator sensor is developed as an alternative tool for detecting adulteration in honey. A honey-filled tube is placed at the position with the maximum electric field intensity. When the honey is adulterated, its permittivity is changed, leading to a distinct resonance frequency shift and enabling detection. Compared with the existing microwave sensors, this sensor offers the advantages of low cost, compact size, and easy fabrication. Moreover, quantitative analysis of the adulteration could be achieved. Electromagnetic simulation is performed using a co-simulation with CST and MATLAB. The simulation results reveal that the resonance frequency of the resonator decreases as the added water content increases, following a quadratic polynomial relationship. In the experiments, the results demonstrate a successive decrease in the resonance frequency from the empty tube, honey-filled tube to water-filled tube cases. Furthermore, honey samples with varying water contents (up to 70%) are tested, and the resonance frequency decreases with increasing added water content, which agrees well with the simulation results. In addition, there is a quadratic relationship between the two parameters. Principal component analysis is conducted on the transmission coefficients, and the first principal component decreases with increasing water content. With the addition of the second principal component, the cases of different water contents in honey can be well classified.

Cost-Effective Open-Ended Coaxial Technique for Liquid Food Characterization by Using the Reflection Method for Industrial Applications

A cheap technique based on an open-ended coaxial probe together with a vector network analyzer was set up. The vector network analyzer NanoVNA, a very tiny handheld device, is the affordable component that gives the instrumental chain a cost-effective perspective. The open-ended coaxial probe is a cable with an SMA gold-plated termination. User-friendly programs can be used to calibrate the instrument, carry out the measurements, and save data on PC. Simple liquid solutions (sodium chloride, citric acids, and saccharose) and more complex liquid food (milk, egg products, and fruit juice) were investigated. In addition, the temperature on the electric measurement of milk was measured to evaluate a possible influence for refrigerated storage products. The reflection parameters, such as the real and imaginary parts of S11, were used to build univariate and multivariate models. The best results in terms of coefficient of determination and related error were 0.997 (RMSE 0.05%) for sodium chloride and 0.965 (RMSE 0.71 °Brix) for fruit juice considering the univariate model, and 0.997 (RMSE 0.04%) for sodium chloride and 0.981 (RMSE 4.44%) for yolk using multivariate analysis. The proposed solution is non-destructive, cheap, rapid, and very attractive for potential lab and industrial applications.