Analysis of Fat and Protein Content in Milk Using Laser Polarimetric Scatterometry

Monitoring the composition of milk products is an important factor in the management of dairy farms and industry. Information on the quantitative content of milk components is necessary to control milk quality, as well as to optimize dairy cow nutrition and diagnose their clinical condition. The content of fat and protein is considered the main criterion for determining the market value of milk. Increasing the efficiency of dairy production requires the use of inexpensive and compact devices that are capable of performing multicomponent analysis of milk both directly on the farm and in technological lines. We investigated the possibility of fast simultaneous determination of fat and protein content in milk by laser polarimetric scatterometry. The block-diagonal elements of the scattering matrix were measured for a series of commercially produced milk samples with the indicated fat percentage, which were diluted by volume with water. From the measured scattering matrices, the size distributions of fat droplets and casein aggregates were reconstructed. Using the size histograms, the content of fat and protein and protein-to-fat ratio in the studied milk samples are estimated.

Economic Analysis of Offering Different Herbage Allowances to Dairy Cows Fed a Partial Mixed Ration

The economics of grazing dairy cows offered a range of herbage allowances and fed supplements as a partial mixed ration (PMR) were examined where profit was defined as the margin between total milk income and the cost of pasture plus PMR supplement. The analysis made use of milk production and feed intake data from two dairy cow nutrition experiments, one in early lactation and the other in late lactation. In early lactation and at a PMR intake of 6 kg DM/cow per day, the profit from the cows with access to a medium herbage allowance (25 kg DM/cow per day) was AUD 1.40/cow per day higher than that for cows on a low allowance (15 kg DM/cow per day). At a higher PMR intake of 14 kg DM/cow per day, the profit from the cows on a medium herbage allowance was AUD 0.45/cow per day higher than the cows on a low allowance; there was no additional profit from increasing the herbage allowance from medium to high (40 kg DM/cow per day). In late lactation, the profit from the cows fed a PMR with a medium herbage allowance (20 kg DM/cow per day) was only higher than the cows on a low allowance (12 kg DM/cow per day) when the PMR intake was between 6 and 12 kg DM/cow per day. There was also a difference of AUD +0.50/cow per day between the PMR with medium and high herbage allowance (32 kg DM/cow per day). It was concluded that farmers who feed a PMR to dairy cows should offer at least a medium herbage allowance to optimize profit. While feeding additional PMR increases milk production and profit, further gains would be available by offering a higher herbage allowance. These findings provide an estimate of the net benefits of different herbage allowances when feeding a PMR and will enable farmers to manage their feeding systems more profitably.

Chosen biotic factors influencing raw cow milk freezing point

The milk freezing point depression (FPD) is important physical property. FPD is influenced by milk composition especially by components with osmotic pressure activity and by other physiological factors. There is possible to indicate a foreign (extraneous) water addition into milk by FPD. This is necessary to have a good estimated legislative FPD discrimination limit (FPD–L) for purpose of milk quality control. This paper was aimed at obtaining information to improve such estimation. Impacts factors as season variations, estimated state of dairy cow nutrition and some milk components and properties on milk FPD and their relations to FPD were quantified (n 11 540 – 72 607 bulk raw cow milk samples). The highest FPD was in Spring (−0.52097 ± 0.004877 °C), the lowest in Autumn (−0.52516 ± 0.005725 °C; P < 0.001). Correlation between FPD and lactose was 0.35 (P < 0.001). 12% and 5.4% of FPD variability is explainable by lactose and casein variability. Relationship between FPD and urea (U) was 0.26 (P < 0.001) in March. The worst FPD was in group with presupposed (according to milk urea and protein combination) nitrogen matter (NM) and energy (E) insufficiency (−0.51855 ± 0.007288 °C). The best FPD was in group with presupposed NM and E surplus in feeding ration (−0.52536 ± 0.004785 °C; P < 0.001). The FPD was worse in suspicion on E deficiency (on the basis of fat/crude protein ratio) as compared to presumption for balanced E nourishment of dairy herds (−0.52105 ± 0.006436 °C > −0.52244 ± 0.005367 °C; P < 0.001). Results can improve the estimation of objective FPD–L.

Relationship between concentration of health important groups of fatty acids and components and technological properties in cow milk

Groups of fatty acids (FAs) in milk fat can have positive and negative impact on consumer health. Profile of FAs could be influenced by dairy cow nutrition, breed, milk yield level et cetera. The question is what relationships the FAs could have to quality of milk products? Relationships between FAs and their groups to selected milk indicators were studied in Czech Fleckvieh and Holstein cows (64 bulk milk samples). There were 8 herds in 2-year investigation during winter and summer season. The relationship of saturated FAs (SAFA; 66.22%) was significant only to lactose (L) content (0.290; P < 0.05). The relationships of monounsaturated FAs (MUFA; 29.21%) to milk indicators (MIs) were in­si­gni­fi­cant (P > 0.05). The relationships of polyunsaturated FAs (PUFA, beneficial for consumer health; 4.53%) to MIs were narrower: fat (T, 0.321; P < 0.05); lactose (L, 0.458; P < 0.01); milk alcohol stability (AL, 0.447; P < 0.01); titration acidity (SH, 0.342; P < 0.01); cheese curd quality (KV, 0.427; P < 0.01); milk fermentationability (JSH, 0.529; P < 0.001), streptococci count in yoghurt (Strepto, 0.316; P < 0.05); total count of noble bacteria in yoghurt (CPMUK, 0.314; P < 0.05); streptococci/lactobacilly ratio (StreptoLacto, 0.356; P < 0.01). The relationships of conjugated linoleic acid (CLA; markedly beneficial for health; 0.68%) to MIs were: T (0.379; P < 0.01); L (–0.542; P < 0.001); AL (0.266; P < 0.05); KV (0.411; P < 0.01); Strepto (0.260; P < 0.05); StreptoLacto (0.270; P < 0.05). The higher CLA levels were connected in this way with: higher fat content; lower lactose content; lower alcohol stability; lower streptococci count in yoghurt; lower streptococci/lactobacilly ratio in yoghurt. The PUFA and CLA representation decreased with L increase. Simultaneously some technological milk properties such as alcohol sta­bi­li­ty and fermentationability were slightly improved.