Quantitatively determining the total bacterial count of raw goat milk using dielectric spectra

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.

Possibility of Using Different Calcium Compounds for the Manufacture of Fresh Acid Rennet Cheese from Goat's Milk

Calcium can be added to cheese milk to influence the coagulation process and to increase cheese yield. Calcium compounds used in the dairy industry show substantial differences in their practical application. Therefore, this study aimed to evaluate the potential use of 0, 5, 10, 15, and 20 mg Ca 100 g-1 of milk in the form of calcium gluconate, lactate, and carbonate as alternatives to calcium chloride in manufacturing fresh acid rennet cheese from high-pasteurized (90 °C, 15 s) goat's milk. The pH value of the cheese was reduced most strongly by the addition of increasing doses of calcium lactate (r = -0.9521). Each cheese sample showed increased fat content with the addition of calcium. Only calcium chloride did not reduce protein retention from goat's milk to cheese. The addition of 20 mg Ca 100 g-1 of milk in the form of gluconate increased cheese yield by 4.04%, and lactate reduced cheese yield by 2.3%. Adding each calcium compound to goat's milk significantly increased Ca and P levels in the cheese (p ≤ 0.05). The highest Ca levels were found in cheese with the addition of 20 mg Ca 100 g-1 of milk in the form of lactate. In all groups, similar contents of Mn, Mo, and Se were found. Calcium addition significantly affected cheese hardness, while higher calcium concentrations increased hardness. Carbonate caused the greatest increase in the cohesiveness of cheese. The addition of calcium compounds increased the adhesiveness and springiness of cheese compared to controls. The cheese with calcium chloride had the highest overall acceptability compared to the other cheese samples. The addition of calcium carbonate resulted in a lower score for appearance and consistency, and influenced a slightly perceptible graininess, sandiness, and stickiness in its consistency, as well as provided a slightly perceptible chalky taste.

Measuring the effects of diethyl phthalate microplastics on marine algae growth using dielectric spectroscopy

This paper presents the development of a dielectric spectroscopy-based method using a customized, transmission line probe, fabricated on a printed circuit board (PCB), for monitoring the effect of diethyl phthalate (DEP) microplastics on marine algae growth. Experiments were performed by exposing marine algae (Chlorella pyrenoidosa) to DEP (0-50 mg) for up to 6 days. In order to amplify the electrophysiological effects and improve the sensing, a glutaraldehyde crosslinking agent was used and encapsulated on the surface of the probe. The reflection coefficient (S₁₁) and the complex permittivity (ɛ' & ɛ″) of the Medium Under Test (MUT) were investigated in the frequency range of 30 kHz-800 MHz. Without the presence of DEP, the number of algae (10⁴ cells/mL) and chlorophyll content (mg/L) increased at the rates of 207.73 × 10⁴ cells/mL and 148.1 mg/L per day, respectively. After 6 days of exposing Chlorella pyrenoidosa (C. pyrenoidosa) algae to different DEP concentrations, the growth rate decreased down to -11.92 × 10⁴ cells/mL and -19.19 mg/L (50 mg DEP), respectively. Additionally, the linearity of the relationship kept decreasing as the DEP content increased from R² = 0.9716 to R² = 0.1050 and from R² = 0.9293 to R² = 0.4961, respectively. Dielectric spectroscopy using the custom, transmission line probe, at 740 MHz, showed linear relationship (-1.22 dB/day) between the reflection coefficient (S₁₁) and hence complex permittivity (ɛ' & ɛ″) without the presence of DEP. However, as the DEP content increased, algae growth was prohibited more intensely, shown both from the number of algae and the chlorophyll content. This trend was reflected on S₁₁ and subsequently on the complex permittivity. This relationship confirms the capability of this method to monitor the growth of marine algae in almost real-time. This dielectric spectroscopy method could be a potential, low-cost tool to examine the impact of microplastic pollutants on marine microorganisms.

Qualitative identification of mature milk adulteration in bovine colostrum using noise-reduced dielectric spectra and linear model

BACKGROUND

The rapid and accurate identification of colostrum, a strong non-homogeneous food, remains a challenge. In the present study, the dielectric spectra including the dielectric constant (ε') and loss factor (ε″) of 154 colostrum samples adulterated with 0-50% mature milk were measured from 20 to 4500 MHz.

RESULTS

The results showed that the noise-reducing spectral preprocessing, including Savitzky-Golay (S-G), second derivative (SD), and S-G + SD, was significantly better than scattering-eliminating, including standard normal variate (SNV), multiplicative scatter correction (MSC), and SNV + MSC. The combination of S-G and SD was the best. Principal component analysis results demonstrated that dielectric spectroscopy is less susceptible to the inhomogeneity of colostrum and can be used to identify doped colostrum. The identification performance of linear models was better than that of non-linear models. The established linear discriminant analysis model based on full spectra had the best accuracy rates of 99.14% and 97.37% in the calibration and validation sets, respectively. Confirmatory tests on samples from different sources confirmed the satisfactory robustness of the proposed model.

CONCLUSION

We found that the main unfavorable effect on the identification based on dielectric spectroscopy was noise interference, rather than scattering effect caused by inhomogeneity of colostrum. The satisfactory results undoubtedly cast light on rapid detection of strongly non-homogeneous foods based on dielectric spectroscopy. © 2022 Society of Chemical Industry.

Quantitative determination of acacia honey adulteration by terahertz-frequency dielectric properties as an alternative technique

The dielectric characteristics in the terahertz region contribute to a revealing insight into the material components and provide intermolecular information. The dielectric properties of adulterated honey, described as the real and imaginary parts of the complex dielectric constant (Re[ε] and Im[ε]), were obtained from 0.3 to 1.5 THz. The relationship between invert syrup proportions and complex dielectric constants at different frequencies implied the possibility of using the dielectric property as an indicator of honey authenticity. The selected effective dielectric variables of Re[ε] and Im[ε] and their combination were chosen by stability competitive adaptive reweighted sampling (SCARS) algorithm and then used to establish PLS models. The accuracy and uncertainty result revealed SCARS-PLS model based on the combination of Re[ε] and Im[ε] is the best model relatively. These findings indicated the potential utility of this rapid, non-destructive, and on-site method for authenticity verification.

An ultrasensitive electrochemiluminescence biosensor for the detection of total bacterial count in environmental and biological samples based on a novel sulfur quantum dot luminophore

An electrochemiluminescence sensor for total bacterial count detection based on sulfur quantum dots with β-nicotinamide adenine dinucleotide as an important parameter.