„milk yield“ 19 výsledků

The purpose of the study was to asses the effect of calving season and dams’ parity on milk yield and gestation length of dairy cows. We examined 93 animals of Slovak spotted breed from the farm located in western Slovakia (Lower Váh region), in years 2014-2017. The herds’ average 305-d milk yield was 8133±1380 kg. The calving season was divided into four categories: spring (March to May), summer (June to August), autumn (September to November) and winter (December to February). The factor of dams parity was divided into 4 groups: 1st parity cows, 2nd-3rd parity cows, 4th and higher parity cows. Calving season affected significantly milk yield of dairy cows (P < 0.01). The highest 305-d milk production was oberved in winter calvings (8942±218 kg) and the lowest in spring calvings (7377±287 kg). The gestation length was not signifficantly altered by calving season (P > 0.32). Dams’ parity was not significantly affected by 305-d milk yield (P > 0.22). Nevertheless, the animals on the 4th and higher lactation were numerically more productive (8481±259 kg) compared to the dairy cows on their 1st,2nd-3rd lactation (8123±264 kg; 7884±223 kg; resp.). The dams’ parity significantly affected gestation length (P < 0.02), with the shortest gestation length in 1st parity dams (278±2 days) and the longest gestation in 2nd-3rd parity dams (284±1 days).To sum up, our results suggest significant role of calving season in relation to milk yield and significant effect of dams’ parity on gestation length.

This research aimed to evaluate the effect of live yeast additive to cattle ration on milk yield of dairy cows. The research was conducted on a dairy farm, on a sample of 265 dairy cows during winter. The dairy cows were fed with a feed containing live yeast of Saccharomyces cerevisiae species (CNCM I-1077). The dosage was 2.1010 cfu.head-1.day-1. Milk yield and the components of milk were monitored for a three-month-long period – starting one month before the supplementation of yeast to feed and ending two months after. The addition of live yeast to cattle ration had a significant positive impact already in the first month on milk yield (+1.25 kg.day-1), and the amount of fat (+0.055 kg.day-1), protein (+0.057 kg.day-1), lactose (+0.056 kg.day-1) and milk solids (+0.170 kg.day-1) contained in milk (p<0.001). The general conclusion of the experiment is, that the Saccharomyces cerevisiae additive had an apparent positive impact on milk yield and milk components.

The aim of this work was to clarify impact of somatic cell count (SCC) on milk yield and its composition. The experiment was realized on one dairy farm with Tsigai breed. Totally 252 milk samples from 84 ewes (on their first and second lactation) were analysed. Milk samples within regular test recording day from the whole udder were collected during lactation in April, June and July. On the basis of SCC the samples were divided into the SCC groups: first <200 × 103 cells.ml-1; second ≥200 <400 × 103 cells.ml-1; third ≥400 <600 × 103 cells.ml-1; fourth ≥600 <1000 × 103 cells.ml-1; fifth ≥1000 × 103 cells.ml-1 to see the effect of SCC at the level of regular milk recording test day. The same SCC groups were used for distribution of the lactation means of somatic cell score (SCS) for evaluation of the effect of SCC at the level of whole lactation. Total milk yield per lactation was affected SCS per lactation (P=0.0089). In each month of sampling we observed decrease content of lactose at the level of test day (P<0.001) and at the level of lactation (P=0.001) with increase of SCC. The increase content of protein we detected with increase of SCC at the level of test days (P=0.0281) and decline per lactation (P=0.0452). In content of fat we did not find out change in relation with increase of SCC in regular milk recording test days and per lactation also. The analyses suggest that SCC negatively impact on milk yield and milk composition and SCC should be in high attention of dairy practice.

Global warming is already affecting several areas and a further increase of 1.5°C is expected by 2050. Dairy cattle are particularly sensitive to high temperature. So, the aim of this study was to examine the effect of temperature-humidity index (THI) on milk traits, considering changes of climatic parameters in the different seasons from 2010 to 2018. The study was conducted in 3 farms located in a hilly-mountainous area of Tuscany, the Mugello, situated from 220 to 450 m above sea level. Data on average daily milk yield and composition were monthly collected in the 3 farms from 2010 to 2018, while climatic parameters were recorded by a climatic station located in the area of the farms. As regards the climatic parameters, no significant variations have been observed in the last decade. The THI calculated thanks to the recording of temperature and humidity of the weather station, during the warmest months, was high enough to cause heat stress. The milk quality traits declined when THI increased. In conclusion, there was not any evidence that global warming has been affecting Mugello, but, despite its altitude, high THI usually reached during spring and summer seasons are already high enough to cause heat stress and a further increase could worsen farm productivity.

Pregnancy assessment is a very important tool for the reproductive management in efficient and profitable dairy farms. Nowadays, mid-infrared (MIR) spectroscopy is the method of choice in the routine milk recording system for quality control and to determine standard milk components. Since it is well known that there are changes in milk yield and composition during pregnancy, the aim of this study was to develop a discriminant model to predict the pregnancy state from routinely recorded MIR spectral data. The data for this study was from the Austrian milk recording system. Test day records of Fleckvieh, Brown Swiss and Holstein Friesian cows between 3 and 305 days of lactation were included in the study. As predictor variables, the first derivative of 212 selected MIR spectral wavenumbers were used. The data set contained roughly 400,000 records from around 40,000 cows and was randomly split into calibration and validation set by farm. Prediction was done with Partial Least Square Discriminant Analysis. Indicators of model fit were sensitivity, specificity, balanced accuracy and Area Under Receiver Operating Characteristic Curve (AUC). In a first approach, one discriminant model for all cows across the whole lactation and gestation lengths was applied. The sensitivity and specificity of this model in validation were 0.856 and 0.836, respectively. Splitting up the results for different lactation stages showed that the model was not able to predict pregnant cases before the third month of lactation and vice versa not able to predict non-pregnancy after the third month of lactation. Consequently, in the second approach a prediction model for each different (expected) pregnancy stage and lactation stage was developed. Balanced accuracies ranged from 0.523 to 0.918. Whether prediction accuracies from this study are sufficient to provide farmers with an additional tool for fertility management, it needs to be explored in discussions with farmers and breeding organizations.

The aim of the study was to evaluate the effect of birth season, average maximum temperatures 6 weeks before and after birth of heifers on their first lactation milk yield. In chosen herd, the effect of birth weight, weight gain until weaning on first lactation milk yield was also investigated. Additionally, the effect of the average maximum temperatures before birth, effect of birth season on birth weight were evaluated. The data were collected from the herd “A” in Orava region consisting of Slovak spotted breed (127 records), the herd “B” in Lower Nitra (150 records) and herd “C” in Upper Nitra (116 records) both consisting of black Holstein Friesian cows. Birth season tended to influence the heifers first lactation milk yield in the herd “C” (P <0.06). The maximum average temperatures during the first 6 weeks after birth significantly affected heifers first lactation in the herd “A” (P <0.01). The maximum average temperatures affecting pregnant cows before birth of their heifers did not influence heifers’ milk yield during the first lactation in all herds (P >0.66, herd “A”; P >0.59, herd “B”; P >0.38, herd “C”). In the herd “B” there was insignificant effect of prenatal temperatures, birth season on birth weight of heifers (P >0.97; P >0.74). However, the heifers with the highest weight gains until weaning had numerically higher first lactation milk yield (P >0.20).

DGAT1 gene polymorphism in exon 8 AA→GC which converts lysine to alanine at position 232 (K232A) was determined to have significant influence on bovine milk production characteristics like milk yield, protein content, fat content, and fatty acid composition. The aim of this study was to analyse the effect of DGAT1 gene polymorphism on dairy production traits [milk yield (kg), fat yield (kg), fat content (%), protein yield (kg) and protein content (%)]. Genotyping of 136 Holstein cows was performed using the ACRS-PCR method. The genotypes frequencies were as follows: homozygous genotype AA (80.88%), heterozygous genotype AK (16.91%) and homozygous genotype KK (2.21%). In the monitored population, allele A had a predominance with a frequency of 89.34% over allele K with a frequency of 10.66%. In the study was observed a statistically significant (P <0.0001) effect of DGAT1 K232A marker genotypes on breeding value variability for milk fat and protein content (%) as well as milk yield (kg) was observed.

The objective was to analyse (1) relationships between somatic cell score (SCS) i.e. logarithmic transformation of somatic cell count (SCC) and daily milk yield and milk components (fat, protein and lactose contents), and (2) factors aff ecting variation of these traits in Hostein cows. Test day records (10,892) from 2015 to 2020 were investigated. Relationships were characterized using linear correlations. Eff ects of fi xed factors: SCC class, parity, month in milk, sampling year and season, and random factors of cow and residual error were evaluated using mixed model. The factor SCC class was omitted in the analysis of SCS. There were found negative correlation coeffi cients between SCS and milk yield (-0.25) and lactose content (-0.36), and positive correlation coefficients between SCS and fat content (+0.12), and between SCS and protein content (+0.15). The considered fixed factors showed the significant influence on investigated traits. With increasing SCC, milk yield and lactose content decreased and fat and protein contents increased (this pattern agreed with pattern of correlation coeffi cients). Milk yield, fat and protein contents and SCS were lower in primiparas than in multiparas; lactose content showed the opposite pattern. The lowest milk yield and lactose content were found in autumn; the lowest fat and protein contents were found in summer. The highest SCS found in winter did not confi rm a hypothesis that higher temperatures and humidity have impact on cows’ susceptibility to infections and the number of pathogens to those cows are exposed. Further research is needed.

To maintain adequate dairy productivity in sheep, it is important to focus on establishing appropriate husbandry conditions. Currently, breeders are increasingly confronted with extreme weather fluctuations during the grazing season, which significantly impact pasture quality and the milk produced. Therefore, it is crucial to seek suitable breeding systems with breed representation tailored to various climatic and geographical conditions in order to exploit their productive potential fully. This study compares the dairy productivity and milk quality of three sheep farms in the vicinity of Banská Bystrica, Slovakia, which employ different farming systems and feature different breed compositions under changing climatic conditions with increased heat stress during the summer months. Farm 1, located at 1,200 m above sea level (ASL), follows an extensive grazing system with 350 Tsigai ewes. Farm 2, situated at 500 m ASL, houses 456 Lacaune ewes in a semi-intensive system. Farm 3, at 400 m ASL, manages 470 mixed dairy and combined-breed ewes under a semi-extensive system. The results indicate that Farm 2, employing a semi-intensive system, recorded the highest milk yield (246.7 kg·ewe-1); however, it also exhibited the most pronounced decline in the lactation curve, with lower average milk production and qualitative parameters (fat, not fat solids) for the Lacaune breed during the warm months (June – August) compared to Farms 1 and 3, which focus on raising combined breeds. In conclusion, the most suitable breeding method for the climatic and geographical conditions of the observed region appears to be a semi-extensive system with combined sheep breeds, as the variability in dairy productivity parameters during the hottest months with reduced pasture quality is not as marked as it is in specialized dairy breeds.

The increase of milk production at the farm level requires an accurate balancing of the diet and the nitrogen supply also to minimise the possible environmental pollution deriving from dairy farming. The aim of this study was to evaluate dietary protein utilization at different crude protein (CP) levels and to predict nitrogen content in faeces on the basis of nutritional parameters and milk urea nitrogen content (MUN, mg dL-1). The study was conducted on three groups (A, B, C) of lactating dairy cows (8 cows per group, including Latvian Brown and Holstein Black and White breeds) from 10 to 30 days in milk. Total mixed rations containing different levels of CP (approximately 18.0%, 17.5% and 17.0% for A, B and C, respectively) were fed. The amount of feed consumed by each cow was measured and feed samples collected during the trial. Milk yield (kg d-1-1) and faeces amount were recorded, and samples were collected at day 21 of the study for further analysis. Feed samples were analysed for CP, net energy for lactation (NEL, MJ kg-1) and other parameters. Milk samples were analysed for fat (%), total protein (%), casein (%) and urea content (mg dL-1). The statistical investigation was conducted using ANOVA, and correlation and regression analyses. The results showed that milk yield, fat, total protein, casein, urea, and MUN were not significantly different among groups being not affected by the dietary CP levels. The correlation between faecal nitrogen content and CP content in feed was moderately positive and statistically significant (r=0.44, P=0.03), while the correlation between faecal nitrogen content and MUN was moderately negative and showed tendency towards significance (r=-0.39, P=0.06). The regression analysis showed that feed CP explained approximately 20% of faeces nitrogen content.

Feed efficiency has a major influence on farm profitability and environmental stewardship in the dairy industry. The aim of this study was to describe a new selection index adopted by the Italian Holstein and Jersey Association (ANAFIJ, Cremona, Italy) to improve feed efficiency using data recorded by the official dairy recording system. Predicted dry matter intake (pDMI) was derived from milk yield, fat content, and estimated cow body weight. Fat-protein corrected milk (FPCM) was derived from milk yield corrected for fat, protein, and a fixed coefficient for lactose content (4.80%). Therefore, the predicted feed efficiency (pFE) was estimated as ratio between FPCM and pDMI. Average pFE was 1.27±0.18 (kg.d-1) with heritability of 0.32. Predicted Feed Efficiency index (pFEi), traditional and genomic, has been implemented in the Italian Holstein Friesian evaluation system. Results suggest that pFEi may be a new breeding objective for Italian Friesians. The official selection index (PFT), in use since 2002, is positively correlated with pFEi. However, the introduction of pFEi will improve the positive feed efficiency trend. This approach will permit the Italian Holstein Friesian breeders to improve feed efficiency, without increasing costs of recording system. However, to avoid the risk of selecting animals with an excessive negative energy balance after calving, it would be useful to include in the pFE a correction for body condition score and reproductive performances. Meanwhile, in order to increase the accuracy of the predicted phenotype, an Italian consortium is creating a consistent phenotypic critical mass of individual data for dry matter intake in cows, heifers and young bulls.

Milk thistle [Silybum marianum (L.) Gaertn.] is a medicinal plant from the Asteraceae family that is grown for its silymarin content. In the production of the silymarin complex, oil is obtained as a secondary product that must be removed from the seeds before extraction of silymarin. The oil contains a favorable ratio of fatty acids and essential phospholipids and has a high vitamin E concent. The objective of this study was to determine the quality of the harvest and the oil content in the dry matter of milkthistle fruit in three varieties (Silyb, Silma, Mirel) during growing seasons 2019 and 2020. The field experiment was conducted in a warm climatic region of western Slovakia (at the experimental site, Dolná Malanta locality). The results showed that the average yield of milk thistle fruit was 452.72 ±61.71 kg ha-1. The oiliness results wereat the level of 28.62 ±1.12%. The maximum and minimum oil content values in the dry matter were determined in the variety Silma 2019. The differences between the individual varieties were not statistically significant. The factor of the growing season had a statistically significant effect on the oil content. Based on two-year fertility and oil content results, it is recommended to continue to monitor the quantitative and qualitative potentials of the milk thistle in the following growing season.

This research was conducted on 147 cows of purebred Montbéliarde dairy cattle during their first to seventh lactation. On average, each dairy cow provided 161 values on live weight during lactation via the automatic milking system (AMS). The average live weight of a dairy cow of said herd was 699.94 kg, the daily milk yield was 33.67 kg on average and the average day of lactation (DIM) was 111.75. This research discovered a statistically significant decrease of live weight in dairy cattle before the 60th day of lactation in every observed lactation. On the contrary, the changes in live weight in the last 60 days of standardized lactation proved to be inconclusive. Between days 60 and 240 of the lactation, an increase of live weight of varying intensities was observed, mainly in cows who had undergone less lactation cycles in the past. Similarly, the research has proven an impact of the number of lactation cycles the cow has undergone in the past on the live weight of the cow during the first, second and third lactation (645.21 kg, 700.35 kg and 752.10 kg respectively). On the contrary, there was no conclusive difference in live weight between the third and more lactation cycles. The results have also shown that the changes in live weight during lactation were significantly different in first-calf heifers, as opposed to cows after more lactation cycles, similarly to the differences in milk yield.

The climate in the Czech Republic is mild, transient between oceanic and continental, with a typical alternation of 4-year periods. The continental climate is characterized by high temperatures in summer and low temperatures in winter. During the extreme fluctuation of microclimatic conditions in the stable, there is also a change in individual reproductive indicators due to disruption of hormonal secretion, which further affects individual physiological processes, thus worsening conception or milder manifestations of heat, which we currently try to detect by neck responders and other modern systems.The experiment analyzed the effect of the average monthly temperature and humidity in the stable on the percentage of pregnant cows, in 2017 without the use of neck responders and in 2019, when all cows already had a neck responder. Monitoring was performed in 2017 and 2019 on the private farm GenAgro Říčany, a.s. (GPS 49 ° 12'32.319 "N, 16 ° 23'42.666" V). The values of average temperatures and relative humidity were calculated from 15-minute interval recordings of HOBO brand data loggers (Onset), which were placed in the stable, at the height at the withers of the cows without the possibility of influencing the measurements by the cows themselves. The object of monitoring was a herd of approximately 700 cows of Czech Fleckvieh Simmental various lactations. Data on the conception of cows were obtained both from the monthly reports of the breeding organization and from the data of the breeder.Thermal stress can have a long-lasting effect observable for weeks or months after the summer. This is also evidenced by the results of the work, which shows the worsening conception of cows, especially in late summer and autumn. At the same time, the results show a positive effect of the used neck responders, which help with the detection of heat and thus improve the reproduction of the whole herd.

The objective of this study was to analyse costs and incomes from milk/cheese and lamb production in dairy sheep flocks and to evaluate their economic efficiency by calculating the profit/loss that is expressed as the difference between these two economic indicators. Costs were calculated taking into account their individual item structure, revenues were calculated taking into account sales of milk/cheese and lamb production. The analysis included three-year period i.e. years 2017, 2018 and 2019. The object of investigations were twelve and thirteen dairy sheep flocks per year, respectively. Economic indicators were expressed in Eur per feeding day (costs) and/or in Eur per ewe and year (costs, sales, subsidies, profit/loss). Milk and lamb sales did not cover up costs spent on production and accounting for subsidy improved economic efficiency of dairy sheep only to a lower extent. Sheep farming thus produced with the loss. Across years, milk and lamb sales almost unchanged, whereas costs notably increased. No ability to cover up costs with revenues could become an obstacle for further survival of this livestock sector. The increase of both milk yield and lamb production is therefore needed.

The objective of this study was to analyse eight milk yield and longevity traits in dependence on feeding (grazing) system. Data of purebred Slovak Spotted dairy cows (35,812 heads) culled in the period between 2006 and 2019 were evaluated. Only herds those feeding (grazing) system was known were taken into account. Dairy cows were assigned to four groups: (1) heifers not grazed, cows not grazed (17,628 heads), (2) heifers grazed, cows not grazed (13,056 heads), (3) heifers not grazed, cows grazed (156 heads) and (4) heifers grazed, cows grazed (4,972 heads). The highest average 305-day milk yield (6,139.22 kg) and lifetime milk yield (18,606.78 kg) were found in animals of group (1). Contrariwise, longevity traits were found more favourable in animals of group (4). Their productive life was by 102.78 days longer and average parity was by 0.14 higher in comparison to group (1). The differences between groups were found significant.

The aim of this study was to evaluate lactose in relation to milk production and calving interval in dairy cows of Slovak Spotted cattle. A total of 92,730 lactations from 45,800 dairy cows evaluation from 2015 to 2019 were used for investigating lactose percentage (LP), milk yield (MY), lactose yield (LY), fat percentage (FP), proteins percentage (PP) and calving interval (CI). Data were analysed using the SAS version 9.4 and linear model with fixed effects: herd-years-season (HYS), sire (S), breeding type (BT), coding of milk (Cod-MY) and coding of calving interval (Cod-CI). In the dataset the average of LP was 4.77±0.20 %, while the one of MY, LY, FP, PP and CI were 6,778.53±2,014.18 kg, 325.27±100.45 kg, 3.96±0.47 %, 3.39±0.23 % and 406.66±91.09 days. The correlation of LP with MY, LY, FP, PP and CI was equal to r = 0.1712, r = 0.3157, r = 0.0546, r = 0.1852 and r = -0.0147. These correlation coefficients were statistically highly significant P <0.0001. Among all fixed effects in the analysis of variance of LP, the most relevant effect was observed for HYS (P<.0001).

The aim of this review is to consolidate the already much published knowledge concerning the gastrointestinal tract of the dairy cow in relation to nutrition. This review document deals with the essential living conditions of dairy cows, with an attention to nutrition, and highlights the importance of correct ration design. Dairy cows in different production cycles have special requirements for the composition, structure and nutrient composition of their rations. This review document provides more detailed information on the physical structure of feedstuffs as well as the need for individual nutrients for the right functioning of the dairy cow. These elements determine total health, feed intake, rumination, the development of metabolic diseases and last but not least, milk yield and composition. Rumination is an important and valuable tool that indicates the correctness of these aspects. Many published studies point to the relationship between rumination and health status where early intervention can be made to prevent a reduction in milk yield and consequent negative selection from the breeding stock. Many studies describe rumination as an indicator that forms the basis of the herd on which the very substantial and developing benefits of breeding as well as reproduction itself are built. The rumination-based relationships of heat stress and dairy cow health are also nowadays receiving a great deal of attention in studies. In nowadays also receiving a great deal of attention in studies about relationship not only between rumination - heat stress but also dairy cow health status. Heat stress is characteristically labelled as an unwanted factor that has an adverse effect on dairy cow milk yield.