Effect of Sulfur and Urea Fortification of Fresh Cassava Root in Fermented Total Mixed Ration on the Improvement Milk Quality of Tropical Lactating Cows

The aim of the present research was to determine the influence of sulfur and urea combined with fresh cassava root in fermented total mixed ration (FTMR) on digestibility, fermentation in the rumen, blood metabolite, milk yield, and milk quality in tropical lactating dairy cows. Four mid-lactation Thai Holstein–Friesian crossbred cows were studied. Pre-experiment milk yield was 12.7 ± 0.30 kg/day, and the body weight was 495 ± 40.0 kg. Animals were evaluated in a 2 × 2 factorial in a 4 × 4 Latin square design to receive diets followed by: factor A, which was a dose of sulfur inclusion at 1.0% and 2.0%, and factor B, which was level of urea inclusion at 1.25% and 2.5% DM in FTMR. The hydrogen cyanide (HCN) concentrations reduced 99.3% to 99.4% compared with fresh cassava root when FTMR was supplemented with 1.0% and 2.0% sulfur, respectively. Intake of crude protein was increased based on urea level addition (p < 0.05). Blood thiocyanate concentration was increased by 21.6% when sulfur was supplemented at 2.0% compared to 1.0% (p < 0.05). There was no difference in protozoal concentration, whereas bacterial populations at 4 h after feeding were significantly greater by 6.1% with the FTMR supplemented with 2.0% sulfur and 2.5% urea (p < 0.01). Allantoin concentrations, excretion, absorption, and microbial crude protein showed significant interactions between sulfur levels and urea levels in cows fed diets supplemented with 2.0% sulfur and 2.5% urea (p < 0.05). The molar ratios of the volatile fatty acid (VFA) profile were affected by dietary FTMR (p < 0.01). Furthermore, propionic acid increased by 4.6% when diets were supplemented by 2.5% sulfur (p < 0.01). Milk fat and total solids increased when feed was supplemented with 2.0% sulfur and 2.5% urea (p < 0.05). The diets supplemented with 2.0% sulfur levels resulted in greater concentrations of milk thiocyanate (p < 0.05). The somatic cell count was significantly reduced throughout the experiment with increasing sulfur supplementation (p < 0.05). Animals fed diets supplemented with 2.0% sulfur exhibited a decreased somatic cell count by 18.3% compared with those fed diets supplemented with 1.0% sulfur. Thus, inclusion of 2.0% sulfur with 2.5% urea in FTMR containing fresh cassava root improved digestibility, ruminal fermentation, microbial crude protein synthesis, and milk qualities in dairy cows.

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Comparative analyses of enteric methane emissions, dry matter intake and milk somatic cell count in different residual feed intake categories of dairy cows

Canadian Journal of Animal Science ◽

10.1139/cjas-2019-0085 ◽

2020 ◽

Author(s):

Dagnachew Hailemariam ◽

Ghader Manafiazar ◽

John A. Basarab ◽

Paul Stothard ◽

Filippo Miglior ◽

...

Keyword(s):

Dairy Cows ◽

Somatic Cell ◽

Cell Count ◽

Milk Yield ◽

Feed Intake ◽

Somatic Cell Count ◽

Dry Matter ◽

Residual Feed Intake ◽

Dry Matter Intake ◽

Milk Traits

This study compared the different residual feed intake (RFI) categories of lactating Holsteins with respect to methane emission, dry matter intake (kg), milk somatic cell count (SCC, 103/mL) and β-hydroxybutyrate (BHB, mmol/L). RFI was calculated in 131 lactating Holstein cows that were then categorized into –RFI (RFI<0) vs. +RFI (RFI>0) and low (RFI<-0.5 SD) vs. high RFI (RFI>0.5 SD) groups. Milk traits were recorded in 131 cows while CH4 and CO2 were measured in 83. Comparisons of –RFI vs. +RFI and low vs. high RFI showed 7.8% (22.3±0.40 vs. 24.2±0.39) and 12.9% (21.1±0.40 vs. 24.2±0.45) decrease (P<0.05) in DMI of –RFI and low RFI groups, respectively. Similarly, –RFI and low RFI cows had lower (P<0.05) CH4 (g/d) by 9.7% (343.5±11.1 vs. 380.4±10.9) and 15.5% (332.5±12.9 vs. 393.5±12.6) respectively. Milk yield was not different (P>0.05) in –RFI vs. +RFI and low vs. high comparisons. The –RFI and low RFI cows had lower (P<0.05) SCC in –RFI vs. +RFI and low RFI vs. high RFI comparisons. BHB was lower (P<0.05) in low RFI compared to the high RFI group. Low RFI dairy cows consumed less feed, emitted less methane (g/d), and had lower milk SCC and BHB without differing in milk yield.

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Effect of subclinical mastitis detected in the first month of lactation on somatic cell count linear scores, milk yield, fertility, and culling of dairy cows in certified organic herds

Journal of Dairy Science ◽

10.3168/jds.2020-19153 ◽

2020 ◽

Author(s):

L. Fernandes ◽

I. Guimaraes ◽

N.R. Noyes ◽

L.S. Caixeta ◽

V.S. Machado

Keyword(s):

Dairy Cows ◽

Somatic Cell ◽

Cell Count ◽

Milk Yield ◽

Somatic Cell Count ◽

Subclinical Mastitis ◽

Certified Organic

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Effect of Somatic Cell Count on Milk Yield and Composition of First and Second Lactation Dairy Cows

Italian Journal of Animal Science ◽

10.4081/ijas.2015.3646 ◽

2015 ◽

Vol 14 (1) ◽

pp. 3646 ◽

Cited By ~ 13

Author(s):

Mahmut Cinar ◽

Ugur Serbester ◽

Ayhan Ceyhan ◽

Murat Gorgulu

Keyword(s):

Dairy Cows ◽

Somatic Cell ◽

Cell Count ◽

Milk Yield ◽

Somatic Cell Count

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Somatic Cell Count and Milk Yield Losses in Goats

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun201765041149 ◽

2017 ◽

Vol 65 (4) ◽

pp. 1149-1160 ◽

Cited By ~ 1

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.

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A cohort study of the effect of Streptococcus agalactiae on milk yield and somatic cell count in Norwegian dairy cows

Journal of Dairy Science ◽

10.3168/jds.2018-16155 ◽

2019 ◽

Vol 102 (9) ◽

pp. 8385-8399 ◽

Cited By ~ 1

Author(s):

Ingrid H. Holmøy ◽

Ingrid Toftaker ◽

Carsten Kirkeby ◽

Olav Østerås ◽

Hannah J. Jørgensen ◽

...

Keyword(s):

Cohort Study ◽

Dairy Cows ◽

Somatic Cell ◽

Cell Count ◽

Milk Yield ◽

Streptococcus Agalactiae ◽

Somatic Cell Count ◽

Norwegian Dairy

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Reliability of Milk Recording Data Under Conditions of Automatic Milking System

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun201462050911 ◽

2014 ◽

Vol 62 (5) ◽

pp. 911-917 ◽

Cited By ~ 1

Author(s):

Oto Hanuš ◽

Pavel Hering ◽

Gustav Chládek ◽

Daniel Falta ◽

Petr Roubal ◽

...

Keyword(s):

Dairy Cows ◽

Cell Count ◽

Milk Yield ◽

Somatic Cell Count ◽

Crude Protein ◽

Cattle Breeding ◽

Automatic Milking System ◽

Automatic Milking ◽

Daily Milk Yield ◽

Daily Milk

Automatic milking system (AMS) brings a change in approach to ensure the data reliability in the official milk recording (MR). The AMS is equipped with flowmeter. AMS software provides the daily milk yield (DMY) and average of the last 7 daily milk yields (AVG7) for MR. Classic MR uses DMY. AVG7 could be more reliable value. Origin of both records (DMY and AVG7) is from AMS flowmeter. The aim of paper was to compare the values of milk yield of cows from daily (DMY) and the extended records (AVG7) from AMS for objective assess of lactations to be used in cattle breeding. Study (2013) with 2 AMS herds (DeLaval and Lely Astronaut): herd 1 – Holstein (H) dairy cows; herd 2 – Czech Fleckvieh (CF) dairy cows. There were following milk records: n = 521 DeLaval (H); n = 567 Lely Astronaut (CF); 70 (H) and 68 (CF) dairy cows. MR samples were analyzed on: fat content; crude protein; somatic cell count. Correlations between AVG7 and DMY were: 0.888 (H); 0.898 (CF, both P ≤ 0.001). There were insignificant differences (P > 0.05; −0.07 ± 3.29 kg for H and 0.28 ± 3.3 kg for CF) between AVG7 and DMY for both robots. The same is valid for differences in the production of milk components. According to this comparison experiment the AVG7 of AMS is a suitable equivalent for the DMY regarding official MR for assessment of lactations.

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Genetic Aspects of Somatic Cell Count in Holstein Dairy Cows in Iran

Animals ◽

10.3390/ani11061637 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1637

Author(s):

Hadi Atashi ◽

Miel Hostens

Keyword(s):

Dairy Cows ◽

Somatic Cell ◽

Cell Count ◽

Genetic Correlation ◽

Milk Yield ◽

Somatic Cell Count ◽

Random Regression ◽

Fat Percentage ◽

Protein Percentage ◽

Holstein Dairy Cows

The aim of this study was to estimate the genetic parameters of somatic cell count (SCC) and its relationship with production traits in the first three parities in Iranian Holstein dairy cows. Data were 1,891,559 test-day records of SCC, milk yield, and milk compositions on 276,217 lactations on 147,278 cows distributed in 134 herds. The number of test-day records in the first, second and third parities were 995,788 (on 147,278 cows), 593,848 (on 85,153 cows), and 301,923 (on 43,786 cows), respectively. Test-day SCCs were transformed to somatic cell scores (SCS). A random regression test-day animal model through four-trait three-lactation was used to estimate variance components for test-day records of SCS and lactation traits were included. Gibbs sampling was used to obtain marginal posterior distributions for the various parameters using a single chain of 200,000 iterates in which the first 50,000 iterates of each chain were regarded as a burn-in period. The mean heritability estimates for SCS (0.15 to 0.18) were lower than those for milk yield (0.36 to 0.38), fat yield (0.30 to 0.31), protein yield (0.31 to 0.32), fat percentage (0.21 to 0.25), and protein percentage (0.21 to 0.22). Low negative genetic correlations ranging from −0.05 to −0.30 were found between SCS and yield traits (milk, fat, and protein yields). The genetic correlation found between SCS and fat percentage was close to zero, however, a low positive genetic correlation ranging from 0.12 to 0.17 was found between SCS and protein percentage. Based on the results, it can be concluded that genetic selection for decreasing SCS would also increase lactation yield. The estimates found in this study can be used to perform breeding value estimations for national genetic evaluations in Iranian Holsteins using a multiple-trait, multiple-lactation random regression model.

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