Circannual changes in major chemical composition of bulk dromedary camel milk as determined by FT-MIR spectroscopy, and factors of variation

Yield and Composition Variations of the Milk from Different Camel Breeds in Saudi Arabia

With the increasing interest in the identification of differences between camel breeds over the last decade, this study was conducted to estimate the variability of milk production and composition of four Saudi camel breeds during different seasons. Milk records were taken two days per week from females of Majahem, Safra, Wadha, and Hamra breeds distributed over Saudi Arabia. The milk yield during winter indicated that the weekly average of the Wadha breed was significantly lower (27.13 kg/week) than Majahem and Hamra breeds. The Safra breed had the lowest milk yield (30.7 kg/week) during summer. During winter, the Hamra breed had a lower content of all analyzed milk components except proteins and was characterized by a lower pH than the milk of the other breeds. However, the Hamra breed had significantly higher contents of milk fat and lactose than the other breeds during summer, with the corresponding values of 3.87 and 4.86%, respectively. Milk collected during winter from Majahem, Safra, and Wadha breeds was characterized by a significant increase in all milk components and milk pH. Finally, the isoelectric focusing analysis revealed noticeable variability of casein purified from camel milk within the different Saudi breeds, with the highest significant value of 2.29 g per 100 mL recorded for the Wadha breed.

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.

Bioactive natural products in donkey and camel milk: a perspective review

Mammalian milk has numerous components that exhibit chemical and functional activities. They support human homeostasis. Immunoglobulins, peptides with antibacterial and antimicrobial activities, carbohydrates, lipids, and minor molecules have positive effects on health. Beyond the nutritional values of milk, milk-borne biologically active compounds such as proteins and other minor constituents exhibit essential physiological and biochemical functions. Human milk guarantees a healthy development and improves immunity. It is hypoallergenic. Sometimes, it is necessary to substitute this food with other milk for different reasons. Cow, sheep, goat, camel and donkey milk are natural alternatives. We evaluated the different compounds within donkey and camel milk analysing their biomolecular characteristics and potential benefits for human health. Camel and donkey milk bioactive products could be good candidates for controlling several diseases and excellent substitutes in the case of milk protein allergies in infants. However, more research should be conducted to further evaluate their nutraceutical potential.

Annual and seasonal trends in cow's milk quality determined by FT-MIR spectroscopy in Hungary between 2011 and 2020

We analysed and monitored the major chemical composition of cow's bulk milk by Fourier transform mid-infrared (FT-MIR) spectroscopy over a 10-year period in the whole territory of Hungary. In addition, the two most important key parameters for milk quality assessment, total bacterial count (TBC) and somatic cell count (SCC) were also followed. Production parameters showed significant seasonal and yearly changes. The overall mean fat, protein, lactose and solids-non-fat (SNF) contents of cow's milk were 3.81%, 3.32%, 4.74% and 8.76%, respectively. A circannual variation was observed in the chemical composition and yield of milk components of samples examined between 2011 and 2020. Concerning milk fat, milk protein and SNF, the values were the lowest in summer and the highest in winter. In the case of lactose, the minimum values were measured in autumn and the maximum values in spring. An obvious trend of long-term elevation of lactose and SNF was found in the raw cow milk samples over the observed period. The overall mean TBC and SCC of cow's milk were 52 × 103 CFU ml-1 and 270 × 103 cells/ml, respectively. Although there were differences in the monthly average values, no seasonal cyclicality was observed.

Comprehensive biochemical and proteomic characterization of seasonal Australian camel milk

Although camel milk is increasingly becoming a popular alternative to bovine milk around the world including Australia, studies of Australian camel milk are still lacking. A comprehensive and systematic analysis of major nutritional components, physical properties, antimicrobial enzymes and whey proteomes of Australian camel milk obtained over four seasons was conducted, for the first time in present study. The composition and physical properties of Australian camel milk varied with season, milking frequency and yield. The highest lactoperoxidase and polyamine oxidase activity was observed in summer and winter, respectively. A total of 97 proteins were quantified, on a relative basis, across all the seasonal bulk milk samples. Summer camel milk contained higher amounts of functional whey proteins, such as lactotransferrin, peptidoglycan recognition protein 1, osteopontin and lactoperoxidase. These results contribute to a better understanding of the Australian camel milk and provide insights into processing of dairy products from this milk.

Effects of Pasteurization and High-Pressure Processing of Camel and Bovine Cheese Quality, and Proteolysis Contribution to Camel Cheese Softness

The effects of high-pressure processing (HPP) compared to thermal treatments on the quality of camel vs. bovine cheeses were studied. The study showed that camel milk has a lower microbial load compared to bovine milk, which is maintained during 7 days' storage of the processed milk. The effect of three HPP treatments (350, 450, and 550 MPa for 5 min at 4°C) and two pasteurization treatments (65°C for 30 min and 75°C for 30 s) on the quality of soft unripened camel and bovine milk cheeses were accessed. The cheeses were evaluated for pH, yield, proximate composition, textural and rheological properties, microstructure, and protein profile by SDS-PAGE electrophoresis. The effects of the treatments on cheese's hardness were different between the camel and bovine cheeses; while heat treatment at 65°C for 30 min gave the hardest bovine milk cheese (1,253 ± 20), HPP treatment at 350 MPa for 5 min gave the highest value for camel milk cheese (519 ± 5) (p < 0.05). The hardness of the cheeses was associated with low yield and moisture content. SDS-PAGE electrophoresis revealed that extensive proteolysis might have contributed to the softness of camel cheeses compared to bovine and suggested the involvement of some residual enzyme activities.

Use of near and mid infra-red spectroscopy for analysis of protein, fat, lactose and total solids in raw cow and camel milk

Milk samples (150 cow and 217 camel milk samples) were analyzed for protein, fat, lactose and total solids by near and mid-infrared transmission spectroscopy. Excellent positive correlations between the two methods were obtained for both types of milk (p < 0.001); for protein (r ≥ 0.96), fat (r ≥ 0.99), lactose (r = 0.82) and total solids (r = 0.90). The mean of the relative difference ((MIR values - NIR values)/0.5 (MIR values + NIR values) × 100%) for cow and camel milk were, for protein (+8.2 & +13.4%), fat (-9.3 & +0.9%), lactose (-5.4 &-0.7%) and total solids (-2.2 &-3.4%), respectively. The difference between the two methods may be due to the effects of differences in milk homogeneity, especially with respect to casein micelles and fat globules.

Species discrimination and total polyphenol prediction of porcini mushrooms by fourier transform mid-infrared (FT-MIR) spectrometry combined with multivariate statistical analysis

The plateau specialty agricultural products, wild porcini mushrooms, have great value both as a superb cuisine and as a potential medication. Due to quality different between species added with the fraud behavior in sales process, make poor quality or poisonous sample inflow into the market, which pose a health risk for consumers, but also disrupted the mushroom market. Traditional analysis way is time-consuming and laborious. Therefore, the aim of this study is to develop a way using fourier transform mid-infrared (FT-MIR) spectrometry and data fusion strategies for the fast and accurate species discrimination and predict amount of total polyphenol in four porcini mushrooms. The t-distributed stochastic neighbor embedding based on mid-level data fusion showed two species of Boletus edulis and B. umbriniporus have been identified. The order of correct rate of PLS-DA models was mid-level data fusionq (100%) > mid-level data fusione (97.06%) = mid-level data fusionv (97.06%) = stipes (97.06%) > low-level data fusion (94.12%) > caps (91.18%). The order of correct rate of grid-search support vector machine models was low-level data fusion (100%) > caps (94.12%) > stipes (91.18%), and the order of particle swarm optimization support vector machine was low-level data fusion (100%) > caps (97.06%) > stipes (88.24%). The mid-level data fusionq and low-level data fusion had best discrimination accuracy (100%) allowing each mushroom classed into its real species, which could be used for accurate discrimination of samples. B. edulis mushrooms had highest total polyphenol, with 14.76 mg/g dw and 17.33 in caps and stipes mg/g dw, respectively. The phenols were easier to accumulate in the caps in Leccinum rugosiceps (1.03) and B. tomentipes (1.19), and the opposite phenomenon is observed in B. edulis (0.85) and B. umbriniporus (0.95). The correlation coefficient and residual predictive deviation of best prediction model were 86.76% and 2.40%, respectively, indicating that that there is good relevance between FT-MIR and total polyphenol content, which could be used to predict roughly polyphenols content in mushrooms.