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Casein measurement is important for cheesemaking and control of dairy cow nutrition. Reference Kjeldahl method is not suitable for routine purposes. Infra-red spectroscopy MIR and MIR-FT use can be a solutin. However, their casein specifity is relatively limited. Aim of the work was to assess the quality of performed calibrations for validation of calibration parameters. A retrospective analysis of MIR and MIR-FT calibrations was performed for estimation of limits their suitable parameters. Mean casein values of reference sample sets varied from 2.49 to 2.7% (2.61 ± 0.155). Mean variation range was 0.561 ± 0.164%. The mean correlation coefficient of calibration (KKK) was 0.974 ± 0.018 (P < 0.001). The mean standard deviation of mean for individual differences (SDID) was 0.03 ± 0.011% (from 0.01 to 0.08). MIR-FT results were slightly better both for calibration and for proficiency testing. The high and low KKKs were higher in the case of accepted calibration as in proficiency testing for MIR-FT and MIR (0.986 > 0.964 and 0.970 > 0.948; 0.982 > 0.947 and 0.947 > 0.911; P < 0.001). The casein number varied from 79.4 to 80.56% in bulk milk samples in three years, its variability was low from 1.4 to 1.5% relatively, which shows on relatively reliable casein analyses by methods MIR and MIR-FT. It does not need to agree fuly for individual milk samples. It is linked more to MIR than MIR-FT. Limits for acceptable calibration parameters were derived: > 0.945 for KKK; 0.048 for SDID and 0.029% for mean difference as maximum.

Citric acid (KC) in milk is indicator of cow energy metabolism. Milk laboratories set up KC determination. A method can be infra-red analyse (MIR-FT). The goal was to develop a relevant method for reference sample preparation for MIR-FT (indirect method, Lactoscope FTIR and MilkoScan FT 6000) calibration. As reference was used a photometric method (c; 428 nm). KC was added (n = 3) into some reference milk samples (n = 10, bulk milk). Mean value was 9.220 ± 3.094 mmol.l^-1 with variation range from 6.206 to 15.975 mmol.l^-1. Recovery c was from 100.8 to 120.2 %. Correlation between c and MIR-FT were from 0.979 to 0.992 (P < 0.001). These were lower in the set of native milk samples (n = 7), from 0.751 (Lactoscope FTIR; P < 0.05) to 0.947 (MilkoScan FT 6000; P < 0.001) in comparison to original values from 0.981 to 0.992 (n = 10; P < 0.001). Correlations between calibrated MIR-FT instruments were from 0.958 to 1.0 (P < 0.001). Average recovery for instruments (n = 12) was 101.6 ± 18.1 %. The mean differences between c method and MIR-FT after calibration (n = 4) moved from -0.001 across zero to 0.037 %. Standard deviation of differences was from 0.0074 to 0.0187 % at MilkoScan FT 6000 and from 0.0105 to 0.0117 % for Lactoscope FTIR. Relative variability of differences (MIR-F (filter technology) and FT) for major components fat (T), proteins (B) and lactose (L) in total and minor components KC and free fatty acids (VMK) was estimated to 1.0 and 7.2 and 34.4 %. The KC result is inferior than T, B and L superior than VMK. Autocorrelation (0.042; P > 0.05) of results demonstrated the independence of consecutive measurements. Milk preservation effect amounted 0.2323 (P < 0.001) with bronopol and 0.0339 (P > 0.05) mmol.l^-1 with dichromate. It was (3.0 and 0.44 %) practically negligible, redeemable via relevant calibration. The results of proficiency testing in post-calibration period and evaluation of double transport stress effect samples (difference was -0.006 ± 0.071 mmol.l^-1 (P > 0.05)) demonstrated the useability for central calibration system. Milk KC results of MIR-FT calibration were good and can be suitable for practical screening.

Essential part of raw milk component measurement is indirect infraanalyse. The checking of time measurement stability is important there. The preparation of pilot samples was described. Information about deep frozen milk pilot sample stability are sporadic. Aim of this work was to verify the stability of long-term stored and deep frozen pilot samples (FPSs). Pilot samples were frozen in liquid nitrogen bath -196 °C and after that stored at -21 °C for one month (A) and more months (B) till analyse. The pilot samples were measured by CombiFoss 6000: fat F (%); protein CP (%); lactose L (%); casein C (%); solid non fat SNF (%); urea U (mg/100ml); somatic cell count SCC (ths./ml). In the short-term (A) experiment the impact of freezing on pilot milk samples was relatively small, in the framework of acceptable value of repeatability (±0.02 %) for components. The stability of values of FPSs was better according to standard deviations for important F evaluation in H (Holstein) breed samples. The repeatability of values of FPSs in the time was very good for other components. The repeatability was better for SCC in J (Jersey) breed samples (±16.5 thousands/ml). That is why the higher variability (±30.1 thousands/ml) in H sample is visible less sceptically. The apparent result trends were not observable in the repeatability development of important milk indicators in FPSs. The mild trend was only in CP, but this trend covered absolutely very small shift (variation range). There are only oscillations, which are similar between J and H samples. It is possible to attribute these oscillations rather to instrument effects than to sample effects. The oscilations were markedly higher in the long-term (B) experiment. Between J and H samples the oscilations were very similar in curves F and L. It is also possible to attribute them more to instrumental effects. The repeatability values (standard deviations sd) of FPSs were mostly lower than ±0.06 %. It is acceptable for result agreement between indirect and reference method. Relevant sd varied from ±0.025 % for L to ±0.059 % for F (in J breed) with exception CP ±0.085 % in J sample. Also B procedure was shown as applicable for instrumental sability control in half year period. In practice the one reference value for concrete FPS is valid from one to next calibration. Persistent trend in repeatability of FPSs can indicate an inadequate instrumental drift. The applied FPS procedure is usable for stability control of instrumental measurement in milk laboratories.

Because of economical reasons the substitution of maize by feed corn as wheat (Sulamit) and triticale (Kitaro) was revolved in concentrate part of dairy cow feeding rations. The design of mentioned replacement in feeding rations was carried out according to results of previous research (Pozdíšek and Vaculová, 2008) for nutrition experiment. The aim of this paper was to evaluate the possible effects of corn replacement in cow feeding rations on milk composition and properties. The expressively different variants of corn were selected for experiment in comparison to maize (reference). Dairy cows were fed by total mixed ration on the basis of maize and clover silage and hay. Otherwise the identical day feeding rations among cow groups differed only in concentrate portions ((K, control group) maize 1.5 kg, wheat (P1) 2.0 kg and triticale (P2) 2.0 kg (experimental groups)). Group feeding rations 1 (K), 2 (P1) and 3 (P2) had: NEL/kg dry (DM) matter (6.524, 6.512 and 6.491); NL % in DM (17.9, 18.2 and 17.9); fibre % in DM (15.96, 15.74 and 15.72); PDIN/PDIE (1.189, 1.189 and 1.191). The experiment took six weeks, there were included 8, 9 and 9 cows (n = 26) of Czech Fleckvieh breed. Feed groups were well balanced in terms of milk yield, days in milk and number of lactation. The tie stable and pipeline milking equipment were used in experiment. Animals were milked twice a day and sampled at morning milking in intervals about seven days approximately. Cows were relatively healthy in terms of occurrence of milk secretion disorders. Within groups the individual milk samples (in total 182 in experiment) were aggregated into bulk samples (n = 21 = 3 groups × 7 sampling periods), which were analysed on 45 milk indicators, 18 of them were evaluated in this paper. The differences in milk yield were significantly advantageous for K group (15.32 > 14.07 (wheat) or 13.86 kg (triticale) at morning milking), while fat (3.27 < 3.47 or 3.44 %) was lower (P < 0.05). Lactose was not influenced. More important differences were in total dry matter, 12.09 (K) < 12.23 (P1) or 12.40 % (P2). While for wheat was not for triticale was similar effect observed in crude protein (CP) of milk (3.08 (K) or 3.05 (P1) < 3.23 % (P2)). Similar trend was also confirmed in casein (CAS; 2.43 or 2.44 < 2.55 %; from P < 0.05 to P < 0.001 for CP and CAS). There were insignificant differences between groups for casein number, pH acidity, electrical conductivity, Mg and Cu (P > 0.05). Milk specific weight was lowest in P1 (P < 0.01), but this indicator is practically less important. More expressive differences were in somatic cell count (SCC) in geometric mean 249 (P2) > 76 (K) or 72 10³/ml (P1). Because of quite typical high SCC variability in triticale P2 group (in opposite to this low variability in K and P1 groups) it could be caused by chance in animal selection for groups and all values met the standard demand for extra quality of milk. Therefore, it is not necessary to over estimate this result. Milk urea as metabolical indicator was higher in wheat group, significantly (P < 0.05) versus triticale group (23.39 (P1) > 20.80 (K) and 20.50 mg/100ml (P2), but all values lay in respected physiological range (from 20 to 30 mg/100ml). In the Ca case it was significantly hig

Somatic cell count (SCC) is an indicator of mammary gland health state. Lactose (L) can be reduced with mastitis and SCC increase. Mammary gland health is an essential factor of milk quality. Monitoring of mammary gland health is important for prevention and treatment of milk secretion disorders. The goal of this work was to analyse the relationship between SCC and L in various biological species. 7 sets of individual and bulk milk samples (MSs) were analysed (n = 479, 479, 345, 80, 90 and 102) for SCC and L content. 3 sets were with cow (C) milk and 1 set with goat (G), 1 with sheep (S) and 1 with human (H) MSs. The relations in C milk were used as reference. SCC geometric means were markedly lower in C milk (62, 99 and 81 10³.ml^-1) and H milk (103 10³.ml^-1) as compared to small ruminants (G 3 509 and S 609 10³.ml^-1). The mean L values were lower in small ruminants (G 4.36% and S 4.42%) as compared to C milk (4.95%, 4.97% and in 1st lactation 5.10%) and higher in H milk (5.77%). L contents in Czech Fleckvieh and Holstein correlated negatively to SCC (log SCC)) in all lactations (-0.36 P < 0.001 and -0.33 P < 0.001). L content in 1st lactation correlated with SCC markedly narrower than in cows for all lactations (-0.49 P < 0.001). The SCC×L relationship in G (White short-haired) milk (-0.35 P < 0.01) was in good relation to C milk and in S (Tsigai) milk (-0.51 P < 0.001) was markedly narrower as in C and G milk. Lower mean SCC in H milk as compared to G and S milk and comparable to C milk did not show significant negative relationship to L which was 0.08 (P > 0.05) for original SCC values. Surprisingly there was not found the SCC×L relationship in H milk which could be comparable to other mammal species milk. It could be caused by bacteriologically negative results in MSs with higher SCC (> 300 10³.ml^-1). As well as at C milk also at G and S milk and in contrast to H milk it is possible to use the SCC×L relationship for improvement of result interpretation and prevention control in occurrence of milk secretion production disorders in routine monitoring systems such as milk recording with individual MSs and milk quality control with bulk MSs. The quality of decision-making schemes in algorithms for practical monitoring of mammary gland health could be improved.

The aim of our study was to evaluate the relationship between reproduction and milk traits in cows of the Czech Fleckvieh. In the period of 90-180 days after calving milk of each dairy cow was analysed for constituent milk components and milk features (40 analyses in total for each sample). The database contained data concerning to the origin and reproduction traits (service period, services per conception and interval between calving and first insemination) for every single cow.
When the calculated correlations were evaluated the milk yield reached significant (* p < 0.05) to very significant (**p < 0.01) negative correlation to content of some milk components: fat (-0.253**); rough protein (-0.256**); casein (-0.197**); pure protein (-0.247**); and also to content of some macroelements as: phosphorus (-0.245**); sodium (-0.261**); magnesium (-0.151*).
Relation of milk yield (in kg) and reproduction traits (number of inseminations and length of service period) shows non-significant positive correlations. With increasing of milk yield, there are a higher number of services per conception and longer service period. It confirms a general tendency of deterioration of reproduction with an increasing milk yield.
We have found out that when the concentration of urea, acetone, number of somatic cells and percentage of fat in milk of Czech Fleckvieh cows was increased, reproduction traits worsened (number of inseminations, length of service period). The differences were not statistically significant. This negative relation was not proven to an interval (number of days between calving and the first insemination), where a company management may have a significant influence.

Based on the linear type classification of 49 246 young cows of the Czech Fleckvieh breed the overall udder score was proposed. Calculation of the overall udder score is derived from the particular type traits, especially from those traits, where the optimal development is not scored by maximum. Cubic regression coefficients were used for recalculation and obtained a new scale for traits such as udder depth, teat length, teat thickness, teat position and teat placement. These re-calculated traits together with other particular traits described on the udder were combined to the model for overall udder score - model 1. In the model 2 the same proportion of the particular traits was used with restriction by extreme development of the udder dept, where two different levels of penalization (-3 and -6 points) were used. Both models were compared with the current used system, where the x = 77.1, s = 5.22; for model 1 x = 84.94 (s = 2.65); for model 2 x = 84.40, s = 2.74. In both proposed models the distribution of the overall score for udder showed significantly smooth distribution, than in current system.
The coefficient of correlation between current system and new proposals reached r = 0.799.
Estimated breeding values for new models decreased from x = 0.199, s = 0.946 by the current used system, to x = 0.087 for model 1, x = 0.089 for model 2 respectively. Also the variability of the breeding values decreased. Estimated coefficients of heritability also decreased from 0.22 by the current system to 0.15 by the model 1 and 0.15 by the model 2, respectively.

Milk freezing point (MFP) is important quality indicator. Aim was to analyse the relationships of MFP to selected udder health milk indicators (MIs) by comparison between cows (reference), goats and sheep. Bulk milk samples came from 3 herds of Czech Fleckvieh (B, n 93) and 1 goat herd and sheep flock (White short-haired, W, n 60; Tsigai, C, n 60). Animal nutrition was performed under the typical country conditions. MIs which were investigated: DM, dry matter; SNF, solid non fat; L, lactose (all in %); SCC, somatic cell count (10³ ml^-1); EC, electrical conductivity (mS cm^-1); MFP (°C); Na and K (in mg kg^-1). W MFP was -0.5544 ± 0.0293, B -0.5221 ± 0.0043 and C -0.6048 ± 0.0691 °C. The B MFP was related to L (-0.36; P < 0.01), W was not related to L (-0.07; P > 0.05) and C was related to L (0.40; P < 0.01). These facts could be explainable by worse SCC geometric averages for used W (3,646 10³ ml^-1) and C (560 10³ ml^-1) milk as compared to B (159 10³ ml^-1). Only 0.5 and 10.5% of variations in MFP were explainable by variations in DM and SNF in B, 32.7 and 12.8% in W but already 49.4 and 45.0% in C. Higher C values were caused by high MFP variability, 11.8% (C) versus 0.8% (B). There is possible to derive the more reliable MFP qualitative limits for more efficient monitoring rules of milk quality problems in B, W and C.