scholarly journals Relationship of milking traits and somatic cell count with electrical conductivity of goat milk during different milking phases

2020 ◽  
Vol 70 (4) ◽  
pp. 292-299
Author(s):  
Birutė Šlyžienė ◽  
Lina Anskienė ◽  
Evaldas Šlyžius ◽  
Vida Juozaitienė
Keyword(s):  
Electrical Conductivity ◽  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Somatic Cell Count ◽  
Goat Milk ◽  
Initial Time ◽  
Good Tool ◽  
Saanen Goat ◽  
Milk Flow

The aim of this study was to estimate the relation between milking traits and somatic cell count with electrical conductivity of goat milk during different milking phases. The research was carried out in the herd of Czech White Shorthaired and Saanen goat breeds (n=323) with the help of the electronic milk flow meter LactoCorder®. The milk yield, milking duration, milking flow rate and electrical conductivity of milk in the different phases of milking showed the significant mean differences between the breeds. Almost all (except electrical conductivity during the initial time) investigated indicators of electrical conductivity had a significant positive correlation with SCC. The bimodality of milk flow was determined in 9.69 % of goats and associated with milk yield decrease and SCC increase (P<0.05). The results confirm that the milk flow curve data is a good tool to control milking traits of goats, to predict the prevalence of mastitis and, thus, to improve the health of the udder of goats.

scholarly journals Association between Udder and Quarter Level Indicators and Milk Somatic Cell Count in Automatic Milking Systems

Animals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 3485
Author(s):  
Maddalena Zucali ◽  
Luciana Bava ◽  
Alberto Tamburini ◽  
Giulia Gislon ◽  
Anna Sandrucci
Keyword(s):  
Electrical Conductivity ◽  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Somatic Cell Count ◽  
Udder Health ◽  
Milk Flow ◽  
Automatic Milking ◽  
Automatic Milking Systems ◽  
Over Time

Automatic Milking Systems (AMS) record a lot of information, at udder and quarter level, which can be useful for improving the early detection of altered udder health conditions. A total of 752,000 records from 1003 lactating cows milked with two types of AMS in four farms were processed with the aim of identifying new indicators, starting from the variables provided by the AMS, useful to predict the risk of high milk somatic cell count (SCC). Considering the temporal pattern, the quarter vs. udder percentage difference in milk electrical conductivity showed an increase in the fourteen days preceding an official milk control higher than 300,000 SCC/mL. Similarly, deviations over time in quarter vs. udder milk yield, average milk flow, and milking time emerged as potential indicators for high SCC. The Logistic Analysis showed that Milk Production Rate (kg/h) and the within-cow within-milking percentage variations of single quarter vs. udder milk electrical conductivity, milk yield, and average milk flow are all risk factors for high milk SCC. The result suggests that these variables, alone or in combination, and their progression over time could be used to improve the early prediction of risk situations for udder health in AMS milked herds.

scholarly journals Somatic Cell Count and Milk Yield Losses in Goats

2017 ◽  
Vol 65 (4) ◽  
pp. 1149-1160 ◽  
Author(s):  
Oto Hanuš ◽  
Petr Roubal ◽  
Josef Kučera ◽  
Marcela Klimešová ◽  
Radoslava Jedelská ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Somatic Cell Count ◽  
Crude Protein ◽  
Geometric Mean ◽  
Goat Milk ◽  
Dairy Goat ◽  
Yield And Quality ◽  
The Relationship

This work is aimed at prediction and quantification of goat milk yield (MY, kg) losses by the somatic cell count (SCC, 103.ml−1) in milk recording. The goal is to support the prevention of milk secretion disorders, milk yield and quality. During two years there were evaluated composition and properties of individual milk samples (n = 1 173). There were included animals of brown short‑haired (BSH) breed and BSH × white short‑haired in one flock. The linear and nonlinear regression, interpolation, extrapolation, approximation and qualified estimation were used for milk losses prediction along the SCC. The relevant values of the SCC arithmetic and geometric mean and median and MY arithmetic mean were: 1,400 103.ml−1 (with high variability of 128 %), 745 and 747 103.ml−1; 2.94 kg/ day. The relationship between fat and crude protein had a correlation coefficient of 0.395, P < 0.001. There were stated the correlations between SCC and: lactose −0.416, P < 0.001; solids non fat −0.25, P < 0.001; MY −0.135, P < 0.01. The relationship between SCC and MY was negative along months, 6 cases out of 7 and significant in March and May (P < 0.05 and P < 0.01). For instance predicted MY for SCC intervals 1–1.999, 2–2.999, 3–3.999, 4–4.999, 5–5.999, 6–6.999 and ≥ 7 thousands 103.ml−1 may be 3.99, 3.77, 3.6 , 3.46, 3.33, 3.23 and 3.13 kg in 3rd month etc. The corresponding MY losses by SCC are evident from this trend. The result use is focused on the original dairy goat farm and use elsewhere is possible in farms with similar SCC, goat milk yield and rearing system.

The relationships between udder-quarter somatic-cell counts and milk and milking parameters in cows managed with an automatic milking system

2020 ◽  
Vol 60 (15) ◽  
pp. 1830
Author(s):  
Beata Sitkowska ◽  
Dariusz Piwczyński ◽  
Magdalena Kolenda
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Somatic Cell Count ◽  
Mean Values ◽  
Natural Logarithm ◽  
Cell Counts ◽  
Milk Flow ◽  
Lactation Stage ◽  
Milk Performance

Context Some milking parameters such as milk yield, milk flow, milking duration, milk conductivity and somatic-cell count can all be listed as economically important traits in dairy practice. Aims The aim of the study was to investigate the relationships among lactation stage, lactation number, milking season and milk-performance traits at an udder-quarter level, including somatic-cell count (SCC), milk yield (MY), milking duration (MD), time in box (TB), milk flow (MF) and milk conductivity (MC). An additional aim was to analyse milking-parameter levels in milkings with a SCC lower and higher than 400000 cells/mL. Methods The study included an analysis of 1621582 successful milkings obtained from six herds of dairy cattle equipped with milking robots (AMS). Key results The study confirmed that MD and MY differed greatly between front and rear quarters. Rear quarters took longer to be milked but produced more milk. During the first 100 days of lactation, the primiparous cows spent more time in the robot than did multiparous cows; however, in the second and third lactations, older cows were spending more time in the AMS. For primiparous cows, MF increased with time, being the highest at the end of lactation (&gt;200 days in milk). A different trend has been found in the group of multiparous cows, where a steady decrease in MF was observed with subsequent lactation stages. A lower MC was recorded for cows in their first lactation than for multiparous cows. Data obtained from primiparous cows showed the highest MC to occur between 100 and 200 days of lactation. In the group of multiparous cows, MC increased with the lactation stage. It was also shown that the mean values obtained for MY, MD and TB were higher for cows with a lower SCC (&lt;400000). Correlations between lnSCC (the natural logarithm of SCC) and MY and between lnSCC and MD were negative and low, while those between lnSCC and MC and lnSCC and MF were positive. Moderate correlations were found between lnSCC and total MC. Conclusions The study confirmed the differences in the performance of different udder quarters in relation to MY, MD, TB, MF, MS and SCC. Implications AMS provides farmers with vast data on milk and milking parameters. By monitoring changes in these parameters, farmer may be able to predict the level of production of their herd and the health of cows.

scholarly journals The influence of crossbreeding and LPL genotype on the yield, composition and quality of goat milk

Mljekarstvo ◽  
2021 ◽  
Vol 72 (1) ◽  
pp. 33-42
Author(s):  
Lina Laučienė ◽  
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Quality Indicators ◽  
Milk Yield ◽  
Somatic Cell Count ◽  
Selection Process ◽  
Goat Milk ◽  
Lpl Gene ◽  
Milk Urea

The aim of this study was to investigate the influence of crossbreeding and the LPL genotype on goat milk yield, composition and quality indicators. This research was carried out in a herd of pure-breed Saanen, Anglo-Nubian, and crossbred Saanen and Anglo-Nubian goats (n=137) in Lithuania. Saanen x Anglo-Nubian crossbred goats and Saanen had a significantly (P<0.05) higher (34.91% and 16.03 %, respectively) milk yield compared to Anglo-Nubian goats. The highest (P<0.05) fat and protein and the lowest (P<0.05) lactose percentages and somatic cell count were found in the milk of Anglo-Nubian goats, compared to Saanen x Anglo-Nubian crossbreds and Saanen goats. The highest (P<0.05) milk yield was determined in the CC genotype of the LPL gene (on average 20.08 % higher than in the CG and GG genotypes) of goats. However, the milk yield of the CC genotype was characterised (P<0.05) by the lowest fat, protein and milk urea levels, and the highest amount of lactose compared to the milk of the GG genotype. The study showed that breed and LPL genotype affected goat milk yield and composition and appear to be the valuable biomarkers of the goat selection process.

scholarly journals Effect of somatic cell count on milkability and milk composition of ewes

10.5219/1411 ◽  
2020 ◽  
Vol 14 ◽  
pp. 1035-1041
Author(s):  
Lucia Mačuhová ◽  
Vladimí­r Tančin ◽  
Juliana Mačuhová ◽  
Michal Uhrinčať ◽  
Marta Oravcová ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Somatic Cell Count ◽  
Milk Composition ◽  
Flow Type ◽  
Milk Flow ◽  
Total Milk

The trial aimed to study the effect of somatic cell count, breed, milk flow type, and parity on the milkability and milk composition of ewes. The flock consists of purebred Lacaune ewes (LC; n = 29) and crossbreds ewes of Improved Valachian (IV x LC; n = 35) and Tsigai (TS x LC; n = 37) with LC (with a genetic portion of Lacaune 25 and 50%). Ewes were assigned according to somatic cell count (SCC) to one of the following three groups: SCC ≤300,000 cells per mL (SCC Group 300,000), SCC between 300,000 and 1000,000 cells per mL (SCC Group 300,000 – 1000,000), SCC ≥1000,000 cells per mL (SCC Group 1000,000). 56% of evaluated ewes had less than 300,000 cells per mL and 29% more than 1000,000 cells per mL in milk. No significant differences were observed between different groups of SCC in total, machine milk yield, and the proportion of milk yield in 30 s and 60 s. The significant differences were observed between SCC Group 300,000 and SCC Group 300,000 – 1000,000 in the proportion of machine stripping from total milk yield (41 ±2 vs. 57 ±4%). Milk flow type had a significant effect on all evaluated milkability parameters but not on milk composition. Ewes on fourth parity had the highest proportion of machine stripping from total milk yield then ewes on third, fifth, and sixth and higher (60% vs. 47, 45, 46%; resp.). Effect of SCC Group on milk composition manifested only in solids not fat. The significant differences were observed between SCC Group 1000,000 to SCC Group 300,000 and SCC Group 300,000 – 1000,000 (10.75 ±0.08% vs. 11.05 ±0.06 and 11.15 ±0.11%, p ≤0.0004).

scholarly journals Hyperketonemia Predictions Provide an On-Farm Management Tool with Epidemiological Insights

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1291
Author(s):  
Ryan S. Pralle ◽  
Joel D. Amdall ◽  
Robert H. Fourdraine ◽  
Garrett R. Oetzel ◽  
Heather M. White
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Milk Yield ◽  
Milk Fat ◽  
Somatic Cell Count ◽  
Past Research ◽  
Management Tool ◽  
Milk Analysis ◽  
Linear Regression Models ◽  
High Throughput Detection

Prediction of hyperketonemia (HYK), a postpartum metabolic disorder in dairy cows, through use of cow and milk data has allowed for high-throughput detection and monitoring during monthly milk sampling. The objective of this study was to determine associations between predicted HYK (pHYK) and production parameters in a dataset generated from routine milk analysis samples. Data from 240,714 lactations across 335 farms were analyzed with multiple linear regression models to determine HYK status. Data on HYK or disease treatment was not solicited. Consistent with past research, pHYK cows had greater previous lactation dry period length, somatic cell count, and dystocia. Cows identified as pHYK had lower milk yield and protein percent but greater milk fat, specifically greater mixed and preformed fatty acids (FA), and greater somatic cell count (SCC). Differential somatic cell count was greater in second and fourth parity pHYK cows. Culling (60d), days open, and number of artificial inseminations were greater in pHYK cows. Hyperketonemia prevalence decreased linearly in herds with greater rolling herd average milk yield. This research confirms previously identified risk factors and negative outcomes associated with pHYK and highlights novel associations with differential SCC, mixed FA, and preformed FA across farm sizes and production levels.

scholarly journals Somatic cell count of milk from different goat breeds

2015 ◽  
Vol 8 (1) ◽  
pp. 45-54
Author(s):  
J. Csanádi ◽  
J. Fenyvessy ◽  
S. Bohata
Keyword(s):  
Somatic Cell ◽  
Cell Count ◽  
Somatic Cell Count ◽  
Goat Milk ◽  
Reference Method ◽  
Fermented Milk ◽  
Linear Calibration ◽  
Limit Value ◽  
White Side ◽  
Standard Limit

Abstract There is no standard limit value for somatic cell count (SCC) of raw goat milk in the EU despite that excellent hygienic quality milk is needed for the manufacture of fermented milk products or cheese varieties. Mastitis often results such high SCC - besides the potential risk for humans - that the clotting of milk will not be perfect, resulting slack curd with higher whey releasing; furthermore, wrong structure, ripening, bad sensory properties of cheese can also be its consequences. In this paper, we report the SCC of milk samples from five different goat breeds bred in Hungary, measured with two fast methods compared with the results from the reference method. Furthermore, we investigated the applicability and the accuracy of the MT-02 (Agro Legato Ltd., Hungary) instrument. We determined that the White Side test and the instrument MT were suitable for the estimation of possible risks and consequences in the case of the use of high SCC milk before production. The general summarized average milk SCC was 6.64 × 105 ml−1. The highest difference between the results from MT-02 and the fluorometric (reference) method was 5 × 105 ml−1, but it was a singular, extreme value. The r2 of the calculated linear calibration equation was 0.7819; consequently, this method seems to be applicable in the measurement of SCC with MT-02 instrument. Furthermore, the SCC of samples did not differ significantly by genotypes and by seasons (spring: 5.85 × 105 ml−1, autumn: 6.22 × 105 ml−1).

Sign in / Sign up

Export Citation Format

Share Document