Milk Fat Yield Research Articles

Assessing heat tolerance through productive vs physiological indicators. Data from dairy sheep under on-farm conditions

The search for criteria that allow the quantification of the level of thermotolerance of an animal is a major challenge in animal production. Different criteria have been proposed to date, mainly the use of routine milk recording and weather information or the collection of physiological measures related with heat stress. This study aimed at quantifying the association between indicators of heat tolerance derived from productive and physiological traits. For this purpose, two physiological traits, rectal temperature (RT) and respiratory rate (RR), and nine productive traits (milk yield, fat, protein and lactose yields and contents, casein and urea contents) were measured from June to September of 2018 in three flocks of Manchega sheep. A total of 462 lactating ewes participated in the study. Air temperature (Ta), relative humidity (RH) and associated temperature and humidity index (THI) were recorded inside the barn and also obtained from the closest weather station from the national meteorological network, and used to produce several measurements of heat load on animals. Based on the results of fits for quadratic and cubic regressions on the alternative heat load measures, the cubic regression on Ta and THI obtained inside the barn at time of recording yielded the best fit for physiological and productive parameters. The use of weather information taken from the official weather station closest to the farm also produced similar estimates and could be considered as a good alternative when on-farm meteorological data are not available. Two-trait random regression models that involved individual intercept and slope of response to heat load were used to obtain correlations between basal levels and heat tolerance within and across traits. Estimated correlations showed that animals with smaller vs larger basal levels of RT and RR tend to be more vs less heat tolerant (correlations up to 0.46) and that slopes of increase for RR and RT under heat stress were highly correlated (0.82). Estimated correlations between tolerance criteria from production vs physiology were up to −0.5 (between milk yield and RT), indicating that animals that show less increase in body temperature also tend to show a smaller decrease in production under heat stress. However, because of the non-unity correlation between the two types of indicators of heat tolerance, both sources of information, productive and physiological ought to be taken into account to ensure the long-term sustainability of selection programmes aiming at improving productive levels when heat stress is a concerning issue.

Genome-wide association analysis of milk production, somatic cell score, and body conformation traits in Holstein cows.

Milk production and body conformation traits are critical economic traits for dairy cows. To understand the basic genetic structure for those traits, a genome wide association study was performed on milk yield, milk fat yield, milk fat percentage, milk protein yield, milk protein percentage, somatic cell score, body form composite index, daily capacity composite index, feed, and leg conformation traits, based on the Illumina Bovine HD100k BeadChip. A total of 57, 12 and 26 SNPs were found to be related to the milk production, somatic cell score and body conformation traits in the Holstein cattle. Genes with pleiotropic effect were also found in this study. Seven significant SNPs were associated with multi-traits and were located on the PLEC, PLEKHA5, TONSL, PTGER4, and LCORL genes. In addition, some important candidate genes, like GPAT3, CEBPB, AGO2, SLC37A1, and FNDC3B, were found to participate in fat metabolism or mammary gland development. These results can be used as candidate genes for milk production, somatic cell score, and body conformation traits of Holstein cows, and are helpful for further gene function analysis to improve milk production and quality.

Quantitative relationships between ingested and intestinal flows of linoleic and alpha-linolenic acids, body weight and milk performance in mid-lactation dairy cows

Linoleic acid (LA) and alpha-linolenic acid (ALA) are essential fatty acids found in variable quantities in ruminant feedstuffs. Revision of French feed unit systems in 2018 has proposed the reassessment of energy requirements through a between-experiment approach expressing metabolisable energy supply as a function of the energy expenditures for maintenance and production, with these expenditures that reflect homeorhetic regulations. Based on the same approach, LA and ALA intake can be related to animal characteristics (i.e., BW) reflecting maintenance expenditures and secretion characteristics (i.e., milk yield, milk fat content and contents of LA and ALA in milk fat). Therefore, the objective of this work was to analyse the between-experiment relationships between ingested, duodenal, or absorbed flows of LA and ALA, BW and milk LA and ALA secretion by meta-analysis in mid-lactation dairy cows. These relationships were analysed using LA and ALA subsets of 96 and 99 experiments, respectively. Between-experiment regressions of daily flows of ingested, duodenal or absorbed LA and ALA on BW and milk LA and ALA flows were studied, with statistical unit defined as the mean of within-experiment treatments. For LA, the BW-associated coefficient was 0.019 (±0.0034) g absorbed LA/d per kg BW and milk LA secretion-associated coefficient was 0.70 (±0.081) g absorbed LA/g of LA secreted into milk. For ALA, the BW-associated coefficient was 0.0058 (±0.00093) g absorbed ALA/d per kg BW and milk ALA secretion-associated coefficient was 0.57 (±0.097) g absorbed ALA/g of ALA secreted into milk. When coding the diets as either control or milk fat depression diets, the BW-associated coefficient for LA was 0.017 (±0.0032) g absorbed LA/d per kg BW for both diets. For milk fat depression diets, milk LA secretion-associated coefficient was 1.02 (±0.119) g absorbed LA/g of LA secreted into milk, whereas it was 0.70 (±0.075) g absorbed LA/g of LA secreted into milk for control diets. Significant BW and milk performance coefficients were obtained in all LA and ALA equations, allowing the calculation of ingested and intestinal flows of LA and ALA based on measured BW, milk fat yield and milk fat content of LA and ALA. The relationships between ingested and intestinal flows of LA and ALA, BW and milk performance obtained in the present work could be integrated into renewed feed unit systems for energy and protein in dairy cows.

Models to predict milk fat concentration and yield of lactating dairy cows: A meta-analysis.

Few models have attempted to predict total milk fat because of its high variation among and within herds. The objective of this meta-analysis was to develop models to predict milk fat concentration and yield of lactating dairy cows. Data from 158 studies consisting of 658 treatments from 2,843 animals were used. Data from several feed databases were used to calculate dietary nutrients when dietary nutrient composition was not reported. Digested intake (DI, g/d) of each fatty acid (FA; C12:0, C14:0, C16:0, C16:1, C18:0, C18:1 cis, C18:1 trans C18:2, C18:3) and absorbed amounts (g/d) of each AA (Arg, His, Ile, Leu, Lys, Met, Phe, Thr, Trp, Val) were calculated and used as candidate variables in the models. A multi-model inference method was used to fit a large set of mixed models with study as the random effect, and the best models were selected based on Akaike's information criterion corrected for sample size and evaluated further. Observed milk fat concentration (MFC) ranged from 2.26 to 4.78%, and milk fat yield (MFY) ranged from 0.488 to 1.787 kg/d among studies. Dietary levels of forage, starch, and total FA (dry matter basis) averaged 50.8 ± 10.3% (mean ± standard deviation), 27.5 ± 7.0%, and 3.4 ± 1.3%, respectively. The MFC was positively correlated with dietary forage (0.294) and negatively associated with dietary starch (-0.286). The DI of C18:2 (g/d) was more negatively correlated with MFC (-0.313) than that of the other FA. The best variables for predicting MFC were days in milk, FA-free dry matter intake, forage, starch, DI of C18:2, DI of C18:3, and absorbed Met, His, and Trp. The best predictor variables for MFY were FA-free dry matter intake, days in milk, absorbed Met and Ile, and intakes of digested C16:0 and C18:3. This model had a root mean square error of 14.1% and concordance correlation coefficient of 0.81. Surprisingly, DI of C18:3 was positively related to milk fat, and this relationship was consistently observed among models. The models developed can be used as a practical tool for predicting milk fat of dairy cows, while recognizing that additional factors are likely to also affect fat yield.

Effect of arginine supplementation on the production of milk fat in dairy cows.

Arginine, one of the conditionally essential AA, has been reported to affect fat synthesis and metabolism in nonruminant animals by influencing adenosine monophosphate activated protein kinase (AMPK) in some organs. In dairy cows, the effect of Arg on milk fat production is not clear, and any potential mechanism that underlies the effect is unknown. We tested the hypothesis that Arg infusion would improve the production of milk fat, and explored possible mechanism that might underlie any effect. We used 6 healthy lactating cows at 20 ± 2 d in milk, in fourth parity, with a body weight of 508 ± 14 kg, body condition score of 3.0 ± 0, and a milk yield of 30.6 ± 1.8 kg/d (mean ± standard deviation). The cows were blocked by days in milk and milk yield and each cow received 3 treatments in a replicated 3 × 3 Latin square design, with each of the experimental periods lasting 7 d with a 14-d washout between each period. The treatments, delivered in random order, were (1) infusion of saline (control); (2) infusion of 0.216 mol/d of l-Arg in saline (Arg); (3) infusion of 0.868 mol/d of l-Ala in saline (the Arg and Ala treatments were iso-nitrogenous) through a jugular vein. On the last day of each experimental period, blood was sampled to measure insulin, nitric oxide, glucose, and nonesterified fatty acid, and the liver and mammary gland were biopsied to measure the expression of genes. Milk yield was recorded, and milk fat percentage was measured daily during each of the experimental periods. The yield and composition of fatty acid (FA) in milk was measured daily on the last 3 d during each of the experimental periods. The data were analyzed using a mixed model with treatment as a fixed factor, and cow, period, and block as random factors. The daily milk yield and milk fat yield when the cows were infused with Arg were 2.2 kg and 76 g, respectively, higher than that in control, and 1.8 kg and 111 g, respectively, higher than that in Ala. When the cows were infused with Arg they had higher concentration and yield of de novo synthesized FA, than when they received the control or Ala infusions, although milk fat percentage, daily feed intake, and the digestibility of nutrients were not affected by treatment. The serum concentration of nitric oxide and insulin were higher during Arg than during control or Ala, with no difference between control and Ala. In the liver, the expression of the genes coding for AMPK (PRKAA1, PRKAB1, and PRKAG1) and genes related to the oxidation of FA were higher during Arg than during control or Ala, whereas in the mammary gland the expression PRKAB1 was lowest, and the expression of genes involved in the synthesis of milk fat were highest, during Arg infusion. The results suggest the intravenous infusion of Arg enhanced the production of milk fat by promoting the de novo synthesis of FA and increasing milk yield.

Effects of corn distillers grains with yeast bodies and manipulation of dietary cation and anion difference on production, nutrient digestibility, and gas emissions from manure in lactating cows.

In a randomized complete block design, 40 lactating Holstein cows (average 98 d in milk and 41 kg/d of milk yield) were randomly assigned to 1 of 4 diets: (1) containing soybean meal as the major protein supplement (CON diet); (2) CON diet with high-protein dried corn distillers grains at 20% on a dry matter (DM) basis by replacing mainly soybean meal (DG diet); (3) DG diet except that high-protein dried corn distillers grains with yeast bodies (extracted after corn ethanol production) was used (DGY diet); or (4) DG diet supplemented with sodium bicarbonate and potassium carbonate to elevate the dietary cation and anion difference (DCAD; DG-DCAD diet). The DCAD of CON, DG, DGY, and DG-DCAD were 185, 62, 67, and 187 mEq/kg of DM, respectively. The experiment began with a 10-d covariate period and then cows were fed the experimental diets for 5 wk (2-wk diet adaptation and 3-wk data collection periods). Dry matter intake and milk yield were measured daily, and spot urine and fecal samples were collected in the last week of the experiment to measure nutrient digestibility; N, S, and P utilization and excretion; and in vitro NH3 and H2S emissions from manure. All data were analyzed using the MIXED procedure of SAS (random effect: block; fixed effects: diets, repeated week, and interactions). During data collection, DM intake was not different among treatment groups, but milk yield tended to be lower (42.4 vs. 39.9 kg/d) for DG, DGY, and DG-DCAD versus CON, which could have been caused by decreases in organic matter and neutral detergent fiber digestibility. Milk protein yield tended to be lower (1.33 vs. 1.24 kg/d) for DG, DGY, and DG-DCAD versus CON. Milk fat yield was lower (1.26 vs. 1.55 kg/d) for DG and DGY versus CON, but that for DG-DCAD (1.43 kg/d) did not differ from CON. Similarly, energy-corrected milk was lower (38.0 vs. 43.3 kg/d) for cows on DG and DGY versus those on CON, but it did not differ between DG-DCAD (40.7 kg/d) and CON. Urinary and fecal N excretion were greater for DG, DGY, and DG-DCAD compared with CON due to greater dietary crude protein content and N intake. However, NH3 emissions did not differ across treatments. Intakes of dietary P and S were greater for DG, DGY, and DG-DCAD, resulting in greater excretion of those in manure and greater H2S emissions from manure compared with CON. These data suggest that the negative effects of feeding distillers grains on production of lactating cows can be partly explained by a decrease in nutrient digestibility (milk yield) and excessive anion load (milk fat). The milk fat response to DG-DCAD suggests that milk fat depression observed with a diet with high content of distillers grains can be partially alleviated by supplementation of cations. In the current study, we observed no beneficial effects of DG containing yeast bodies.

Predicting methane emission in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks.

Interest in reducing eructed CH4 is growing, but measuring CH4 emissions is expensive and difficult in large populations. In this study, we investigated the effectiveness of milk mid-infrared spectroscopy (MIRS) data to predict CH4 emission in lactating Canadian Holstein cows. A total of 181 weekly average CH4 records from 158 Canadian cows and 217 records from 44 Danish cows were used. For each milk spectra record, the corresponding weekly average CH4 emission (g/d), test-day milk yield (MY, kg/d), fat yield (FY, g/d), and protein yield (PY, g/d) were available. The weekly average CH4 emission was predicted using various artificial neural networks (ANN), partial least squares regression, and different sets of predictors. The ANN architectures consisted of 3 training algorithms, 1 to 10 neurons with hyperbolic tangent activation function in the hidden layer, and 1 neuron with linear (purine) activation function in the hidden layer. Random cross-validation was used to compared the predictor sets: MY (set 1); FY (set 2); PY (set 3); MY and FY (set 4); MY and PY (set 5); MY, FY, and PY (set 6); MIRS (set 7); and MY, FY, PY, and MIRS (set 8). All predictor sets also included age at calving and days in milk, in addition to country, season of calving, and lactation number as categorical effects. Using only MY (set 1), the predictive accuracy (r) ranged from 0.245 to 0.457 and the root mean square error (RMSE) ranged from 87.28 to 99.39 across all prediction models and validation sets. Replacing MY with FY (set 2; r = 0.288-0.491; RMSE = 85.94-98.04) improved the predictive accuracy, but using PY (set 3; r = 0.260-0.468; RMSE = 86.95-98.47) did not. Adding FY to MY (set 4; r = 0.272-0.469; RMSE = 87.21-100.76) led to a negligible improvement compared with sets 1 and 3, but it slightly decreased accuracy compared with set 2. Adding PY to MY (set 5; r = 0.250-0.451; RMSE = 87.66-100.94) did not improve prediction ability. Combining MY, FY, and PY (set 6; r = 0.252-0.455; RMSE = 87.74-101.93) yielded accuracy slightly lower than sets 2 and 3. Using only MIRS data (set 7; r = 0.586-0.717; RMSE = 69.09-96.20) resulted in superior accuracy compared with all previous sets. Finally, the combination of MIRS data with MY, FY, and PY (set 8; r = 0.590-0.727; RMSE = 68.02-87.78) yielded similar accuracy to set 7. Overall, sets including the MIRS data yielded significantly better predictions than the other sets. To assess the predictive ability in a new unseen herd, a limited block cross-validation was performed using 20 cows in the same Canadian herd, which yielded r = 0.229 and RMSE = 154.44, which were clearly much worse than the average r = 0.704 and RMSE = 70.83 when predictions were made by random cross-validation. These results warrant further investigation when more data become available to allow for a more comprehensive block cross-validation before applying the calibrated models for large-scale prediction of CH4 emissions.

Predicting dry matter intake in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks.

Dry matter intake (DMI) is a fundamental component of the animal's feed efficiency, but measuring DMI of individual cows is expensive. Mid-infrared reflectance spectroscopy (MIRS) on milk samples could be an inexpensive alternative to predict DMI. The objectives of this study were (1) to assess if milk MIRS data could improve DMI predictions of Canadian Holstein cows using artificial neural networks (ANN); (2) to investigate the ability of different ANN architectures to predict unobserved DMI; and (3) to validate the robustness of developed prediction models. A total of 7,398 milk samples from 509 dairy cows distributed over Canada, Denmark, and the United States were analyzed. Data from Denmark and the United States were used to increase the training data size and variability to improve the generalization of the prediction models over the lactation. For each milk spectra record, the corresponding weekly average DMI (kg/d), test-day milk yield (MY, kg/d), fat yield (FY, g/d), and protein yield (PY, g/d), metabolic body weight (MBW), age at calving, year of calving, season of calving, days in milk, lactation number, country, and herd were available. The weekly average DMI was predicted with various ANN architectures using 7 predictor sets, which were created by different combinations MY, FY, PY, MBW, and MIRS data. All predictor sets also included age of calving and days in milk. In addition, the classification effects of season of calving, country, and lactation number were included in all models. The explored ANN architectures consisted of 3 training algorithms (Bayesian regularization, Levenberg-Marquardt, and scaled conjugate gradient), 2 types of activation functions (hyperbolic tangent and linear), and from 1 to 10 neurons in hidden layers). In addition, partial least squares regression was also applied to predict the DMI. Models were compared using cross-validation based on leaving out 10% of records (validation A) and leaving out 10% of cows (validation B). Superior fitting statistics of models comprising MIRS information compared with the models fitting milk, fat and protein yields suggest that other unknown milk components may help explain variation in weekly average DMI. For instance, using MY, FY, PY, and MBW as predictor variables produced a predictive accuracy (r) ranging from 0.510 to 0.652 across ANN models and validation sets. Using MIRS together with MY, FY, PY, and MBW as predictors resulted in improved fitting (r = 0.679-0.777). Including MIRS data improved the weekly average DMI prediction of Canadian Holstein cows, but it seems that MIRS predicts DMI mostly through its association with milk production traits and its utility to estimate a measure of feed efficiency that accounts for the level of production, such as residual feed intake, might be limited and needs further investigation. The better predictive ability of nonlinear ANN compared with linear ANN and partial least squares regression indicated possible nonlinear relationships between weekly average DMI and the predictor variables. In general, ANN using Bayesian regularization and scaled conjugate gradient training algorithms yielded slightly better weekly average DMI predictions compared with ANN using the Levenberg-Marquardt training algorithm.

Evaluation of dehydrated corn silage as the primary forage for lactating dairy cows

The objective was to compare productivity of lactating dairy cows fed dehydrated corn silage with those fed whole-crop barley silage. Twelve multiparous Holstein cows in mid lactation were fed diets containing dehydrated corn silage (DCS) or barley silage with additional grain (BSHG) or without (BSLG) in a 3 × 3 Latin square design, with 21-d periods, balanced for carryover effects. The dietary starch content was similar for DCS and BSHG diets, and dietary forage content was similar for DCS and BSLG diets. Experimental diets did not affect dry matter intake, but cows fed DCS diet decreased milk yield compared with those fed barley silage regardless of the dietary starch content. Apparent total-tract digestibility of starch and crude protein was also lower for cows fed DCS compared with those fed barley silage, and milk urea N content was lowest for cows fed DCS diet, indicating that DCS likely had less protein degradation in the rumen than barley silage. Milk fat content and yield, energy-corrected milk yield, and feed efficiency were not different between cows fed BSHG and DCS diets, but higher for cows fed BSLG than those fed BSHG or DCS diet, which can be attributed to the difference in dietary starch content. Feeding DCS in place of barley silage did not improve productivity of lactating dairy cows in the current study, and further research is warranted to optimize its utilization in dairy diets.

Energy utilization and milk fat responses to rapeseed oil when fed to lactating dairy cows receiving different dietary forage to concentrate ratio

We evaluated energy and N utilization, performance, and milk fatty acid (FA) profile using grass silage-based diets when rapeseed oil (RO) was included in high- or low-forage diets. Four multiparous Nordic Red cows averaging 101 ± 16 days in milk at the beginning of the study were randomly assigned to a 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments. Each 21-d period consisted of a 14-d diet adaptation period and 7-d collection period. Cows were fed the following diets comprised total mixed rations based on grass silage with forage to concentrate (FC) ratio of 35:65 and 65:35 containing 0 or 50 g/kg of RO. Significant FC × RO interactions were observed for milk yield, milk protein and lactose yields, milk fat concentration, and milk proportions of trans-11 18:1, trans-10 18:1, trans-10, cis-12 18:2, and saturated FA. Feeding low-forage diet was effective in increasing milk yield compared with the high-forage diet, and the RO supplementation increased it further (P ≤ 0.01). A similar pattern was observed for the yields of milk protein and lactose. Supplementing the low-forage diet with RO reduced milk fat concentration by 19% relative to other diets without affecting milk fat yield. The proportion of N intake lost as urine decreased (P ≤ 0.05) with the RO supplementation of low-forage diet without affecting energy and N balances. Nutrient intakes were greater (P ≤ 0.01) in cows fed low-forage diet, whereas RO decreased (P < 0.05) protein, starch, and fiber intakes. Methane production, expressed as a proportion of energy intake, decreased with low-forage compared with high-forage diets and this variable declined similarly by RO supplementation of both diets (P < 0.01). The milk proportions of trans-10 18:1 and trans-10, cis-12 CLA increased (P ≤ 0.01) by RO supplementation of the low-forage but not high-forage diet. However, RO supplementation of both high- and low-forage diets increased (P < 0.01) total trans FA and decreased saturated FA proportions, even though the changes were more profound in low-forage diet (P ≤ 0.01). In addition, RO increased (P < 0.01) cis monounsaturated FA in milk for both high- and low-forage diets. Overall, the low-forage diets had lower methane emissions and RO increased partitioning of N towards milk secretion (P ≤ 0.01) without influencing energy or N balances. According to the results, RO supplementation did not compromise intake of nutrients with low-forage diets containing 150 g/kg starch, and oil could be preferentially used to improve milk production and milk fat quality accompanied by a reduction in methane energy loss.

THE INFLUENCE OF VARIOUS FACTORS ON MILK PRODUCTIVITY IN THE AGRICULTURAL PRODUCTION BRANCH (APB) “ZAOZERIE” OF JSC “VITEBSK MEAT PROCESSING PLANT”

Various factors influence the milk productivity of cows. The article presents the results of studies conducted in the APB “Zaozerie” of JSC “Vitebsk Meat Processing Plant” on 326 cows with completed lactation. In the course of scientific and economic&#x0D; experiment, it was found that the highest milk yield of 8417 kg was obtained from the cows of the 3rd lactation, with a significant increase in milk fat to the level of 316.4 kg. Gain in the live weight of cows in the herd to 651-700 kg contributes to a significant increase in their milk productivity to the level of 8430 kg of milk with a milk fat yield of 312.1 kg. The highest milk yield was obtained from cows with a dry period of 51-70 days - 9415 kg of milk (p≤0.001) with a milk fat yield of 358.7 kg and with a service period of 61-90 days - 7675 kg of milk with a milk fat yield of 285.5 kg (p≤0.001).

PSXI-17 Evaluation of Influence of the Total Accumulation of Toxic Elements in Blood Serum on the Indicators of Milk Productivity of the Holstein Cows

Abstract The main objective was to study the milk productivity of lactating cows depending on the level of total accumulation of toxic metals in the blood serum. The experimental part of work was carried out on clinically healthy Holstein cows (n=45; lactation stage - 20-40 days after calving) bred in a single farm. The elemental composition of blood serum was studied for 4 chemical elements (Al, Pb, Sn, Sr) by ICP AES and ICP MS. The indicators of milk productivity of cows were evaluated by the yield of milk fat, protein, lactose, dry matter, SOMO and the average daily milk yield. To assess the magnitude of the toxic load on the body of cows, the coefficient of the total toxic load Ktox (µg/ml) was calculated. To calculate the coefficient, the sum of the concentrations of some toxic elements in the blood serum was used: Ktox=Al+Pb+Sn+Sr. Based on the data on the value of the total toxic load coefficient Ktox in blood serum, three groups were formed: group I included cows with a minimum value of the toxic load coefficient (Ktox=0.128 (0.088-0.142) μg/ml relative to the study sample; group II with an average (Ktox=0.229 (0.206-0.276) µg/ml; Group III included cows with the maximum coefficient (Ktox=0.395 (0.306-0.453) µg/ml. Comparative analysis showed that cows with the minimum Ktox value (group I) outperformed individuals from I and group II in terms of milk fat yield by 15.4 (P£0.001) and 19.7% (P£0.001), protein by 5.6 and 12.5% (P£0.05), lactose -10.9 (P£0.01) and 18.4% (P£0.001), dry matter by -7.6 and 12.8% (P£0.05) and average daily milk yield by 9.4 and 17.5% (P£0.01), respectively. Thus, in the course of the study, it was registered that with an increase in the total accumulation of heavy metals in the body of animals, the milk productivity of cows decreases.

PSXV-6 Influence of GDF5 Gene Polymorphism on the Concentration of Essential and Toxic Elements in Blood Serum and Milk Productivity of the Holstein Cows

Abstract The aim of this study was to evaluate the effect of GDF5 (growth differentiation factor 5) gene polymorphism on metabolism of chemical elements and milk production of cows. The studies were performed on Holstein cows (n=100). To determine the single nucleotide polymorphism of GDF5 (T586C in exon 1), blood samples were taken. DNA samples were isolated from whole blood using the IsoGeneLab reagent kit. The thermal cycler "MyCycler" was used for DNA amplification. The elemental composition of blood serum was estimated according to 13 chemical elements (Al, As, Pb, Sn, Sr, Co, Cr, Cu, Fe, I, Mn, Se, Zn) by ICP AES and ICP MS. The frequency of occurrence of polymorphic groups in the GDF5 gene was established, which was for homozygous alleles: TT (n=41), CC (n=10), heterozygous (TS)–(n=49). The analysis of the data obtained showed that blood serum of cows with the CC genotype, relative to animals with the TT and TC genotypes had a greater concentration of I - by 19.3 (P£0.001) and 10.4% (P£0.01), Se - by 18.3 (Р£0.001) and 11.7% (Р£0.01), Zn – by 15.8 (Р£0.01) and 13.2% (Р£0.01), while relatively low concentrations of Al were registered - by 10.8 (Р£0.001) and 21.2% (Р£0.01), Pb - by 16.4 (Р£0.01) and 23.7% (Р£0.001) respectively. In terms of milk fat yield (kg/day), animals with CC genotype advanced over animals with the TT and TC genotypes by 4.8 (P£0.05) and 5.2% (P£0.01), protein by 1.2 and 1.4% (Р£0.05), milk yield - by 4.8 (Р£0.05) and 5.3% (Р£0.01). Thus, we can conclude that the metabolism of chemical elements and the milk productivity of cows are significantly determined by the polymorphism of the GDF5 gene. In order to select cows of the Holstein breed according to the GDF5 gene polymorphism, it is advisable to select homozygous animals for the CC genotype.

Transfer of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) from oral exposure into cow's milk - Part I: state of knowledge and uncertainties.

Polychlorinated dibenzo-para-dioxins (PCDDs) and dibenzofurans (PCDFs) (collectively and colloquially referred to as 'dioxins') as well as polychlorinated biphenyls (PCBs) are persistent and ubiquitous environmental contaminants that may unintentionally enter and accumulate along the food chain. Owing to their chronic toxic effects in humans and bioaccumulative properties, their presence in feed and food requires particular attention. One important exposure pathway for consumers is consumption of milk and dairy products. Their transfer from feed to milk has been studied for the past 50 years to quantify the uptake and elimination kinetics. We extracted transfer parameters (transfer rate, transfer factor, biotransfer factor and elimination half-lives) in a machine-readable format from seventy-six primary and twenty-nine secondary literature items. Kinetic data for some toxicologically relevant dioxin congeners and the elimination half-lives of dioxin-like PCBs are still not available. A well-defined selection of transfer parameters from literature was statistically analysed and shown to display high variability. To understand this variability, we discuss the data with an emphasis on influencing factors, such as experimental conditions, cow performance parameters and metabolic state. While no universal interpretation could be derived, a tendency for increased transfer into milk is apparently connected to an increase in milk yield and milk fat yield as well as during times of body fat mobilisation, for example during the negative energy balance after calving. Over the past decades, milk yield has increased to over 40 kg/d during high lactation, so more research is needed on how this impacts feed to food transfer for PCDD/Fs and PCBs.

The potential of milk productivity of Kazakh Bactrians in the Balkhash zone

Camel breeding in the Republic of Kazakhstan is an eff ective branch of herd animal husbandry in the harsh climatic conditions of deserts and semi-deserts. The purpose of the research was to determine the potential of dairy productivity of camels of Kazakh Bactrian in the Balkhash zone. The object of research was camels of Kazakh Bactrian breed in the Balkhash zone of Kazakhstan. The research was carried out in 2021–2022 on the basis of the camel farm of LLP “ESPC Bayserke-Agro” to ensure an optimal level of feeding and breeding work. The research was carried out in accordance with the methodology of experimental work adopted in livestock science. Dams of Kazakh Bactrian camels signifi cantly exceeded their daughters by 214 kg or 24,0 % (P ≥ 0,999) in milk yield for 210 days of lactation. In terms of the mass fraction of fat in milk, dams were inferior to their daughters by 0,2 abs.%, and the yield of milk fat in dams was higher by 9,2 kg or 19,5 % (P ≥ 0,999). In dams the mass fraction of protein in milk was signifi cantly lower in comparison with daughters by 0,3 abs.% (P ≥ 0,999), at the same time the yield of milk protein was higher by 5,3 kg or 14,9 % (P ≥ 0,999). According to the results of the research a high percentage of the implementation of the parent index of camels in terms of their milk productivity during the fi rst lactation was established, which ranged from 92,8 to 103,9 %. Monitoring of the average daily milk yield in uterine livestock showed that over 3 months of observations it tended to increase. The selection and genetic parameters of productivity ensuring the progress of breeding of Kazakh Bactrian camels of the South Kazakhstan type in the Balkhash zone of Kazakhstan were considered.

PIT 1 gene polymorphism and seasonality affect milk production traits in dairy cattle of Kashmir

The study aimed at identifying the best genotypes for important candidate PIT 1 gene and seasonality influencing the yield and quality of milk, in the Jersey and Crossbred HF cattle population maintained at an organized farm in Mountain Livestock Research Institute, Manasbal, Kashmir. The Jersey and Crossbred HF cows (60 each) were genotyped for quality and yield traits. Milk samples (50 ml) were collected on weekly basis for quality evaluation for the years 2016-18, among all the four seasons of Kashmir. The milk quality traits studied were fat%, lactose%, protein%, SNF, density and ash. The quantity traits were average monthly milk yield, protein yield and fat yield. Genomic DNA was extracted using Phenol-chloroform method and association analysis was done. The PIT 1 exon VI (451 bp) was screened for polymorphisms using PCR-RFLP using HinfI restriction enzyme, revealing two genotypes (Pp and pp) for both the breeds. Allele ‘p’ was most frequently present in Crossbred HF cows (0.95) and Jersey cows (0.82). The genotype Pp in crossbred HF cows and pp in Jersey cows showed higher values for yield traits in all four seasons under study. In crossbred HF cows, the effect of genotype Pp was significant on fat% and SNF. The genotype pp effect was significant on fat% in Jersey cows. Winter and autumn seasons had significant effect on fat% in both breeds under study. Based on the study, it was concluded that breed, season, and genotype of the PIT 1 gene are highly associated with the milk quality and yield in the dairy cattle of Kashmir. Genome wide association studies are recommended for better understanding the effects of all genes on milk quality and quantity.

Effect of 2-hydroxy-4-(methylthio)butanoate (HMTBa) on milk fat, rumen environment and biohydrogenation, and rumen protozoa in lactating cows fed diets with increased risk for milk fat depression.

Biohydrogenation-induced milk fat depression (MFD) is a reduction in milk fat synthesis caused by bioactive fatty acids (FA) produced during altered ruminal microbial metabolism of unsaturated FA. The methionine analog 2-hydroxy-4-(methylthio)butanoate (HMTBa) has been shown to reduce the shift to the alternate biohydrogenation pathway and maintain higher milk fat yield in high-producing cows fed diets lower in fiber and higher in unsaturated FA. The objective of this experiment was to verify the effect of HMTBa on biohydrogenation-induced MFD and investigate associated changes in rumen environment and fermentation. Twenty-two rumen cannulated high-producing Holstein cows [168 ± 66 d in milk; 42 ± 7 kg of milk/d (mean ± standard deviation)] were used in a randomized design performed in 2 blocks (1 = 14 cows, 2 = 8 cows). Treatments were control (corn carrier) and HMTBa (0.1% of diet dry matter). The experiment included a 7-d covariate period followed by 3 phases that fed diets with increasing risk of MFD. The diet during the covariate and low-risk phase (7 d) was 32% neutral detergent fiber with no additional oil. The diet during the moderate-risk phase (17 d) was 29% neutral detergent fiber with 0.75% soybean oil. Soybean oil was increased to 1.5% for the last 4 d. The statistical model included the random effect of block and time course data were analyzed with repeated measures including the random effect of cow and tested the interaction of treatment and time. There was no effect of block or interaction of block and treatment or time. There was no overall effect of treatment or treatment by time interaction for dry matter intake, milk yield, and milk protein concentration and yield. Overall, HMTBa increased milk fat percent (3.2 vs. 3.6%) and yield (1,342 vs. 1,543 g/d) and there was no interaction of treatment and dietary phase. Additionally, HMTBa decreased the concentration of trans-10 18:1 in milk fat and rumen digesta. Average total ruminal concentration of volatile FA across the day and total-tract dry matter and fiber digestibility were not affected by HMTBa, but HMTBa increased average rumen butyrate and decreased propionate concentration and increased total protozoa abundance. Additionally, HMTBa increased the fractional rate of α-linoleic acid clearance from the rumen following a bolus predominantly driven by a difference in the first 30 min. Plasma insulin was decreased by HMTBa. In conclusion, HMTBa prevented the increase in trans FA in milk fat associated with MFD through a mechanism that is independent of total volatile FA concentration, but involves modification of rumen biohydrogenation. Decreased propionate and increased butyrate and ruminal protozoa may also have functional roles in the mechanism.

Improvement of breeding traits of cattle when using inbred and homozygous sires

The use of inbred and homozygous sires reduces the share of variability in the biodiversity of the population when it occurs under uncontrolled management, which leads to a decrease in the heritability of the trait. Studying the features of the consequences of inbreeding of sires helps to make their evaluation on the quality of off spring more informative, because as a result of related mating, the genetic structure of the population changes. If a selection with the genotypes of an inbred sire, heterozygous for two aabb loci of body traits, is applied to a certain group of cows, then quantitative traits in the off spring will determine milk productivity. Positive variants should be considered omozygotes, in which dominance is manifested, and heterozygotes, i. e. approximately 70 % of off spring. The probability (frequency) of their appearance is high and one can count on a favorable combination of genes in off spring from inbred and homozygous sires, if the maternal population is heterozygous in terms of physique, which are associated with the level of manifestation of milk productivity. In the breeding herd of Holstein breed, the system of intra-linear selections and crosses of homo- and heterozygous sires revealed the disparity of milk yield increases, the mass fraction of fat and protein in milk in daughters relative to mothers. The superiority in the total yield of milk protein and fat for 305 days of the fi rst lactation of the group of daughters from intraline mating and homozygous sires over mothers was 82,6 (p &lt; 0,01) and 112,9 kg (p &lt; 0,01), respectively. The highest total rank according to the complex of breeding traits was assigned to the daughters of homozygous sires and then according to the increase in the indices of the genetic value of the traits of lactation, the group B was followed by the group derived at the crosses of the lines.

Single Nucleotide Polymorphisms of ALDH18A1 and MAT2A Genes and Their Genetic Associations with Milk Production Traits of Chinese Holstein Cows.

Our preliminary work had suggested two genes, aldehyde dehydrogenase 18 family member A1 (ALDH18A1) and methionine adenosyltransferase 2A (MAT2A), related to amino acid synthesis and metabolism as candidates affecting milk traits by analyzing the liver transcriptome and proteome of dairy cows at different lactation stages. In this study, the single nucleotide polymorphisms (SNPs) of ALDH18A1 and MAT2A genes were identified and their genetic effects and underlying causative mechanisms on milk production traits in dairy cattle were analyzed, with the aim of providing effective genetic information for the molecular breeding of dairy cows. By resequencing the entire coding and partial flanking regions of ALDH18A1 and MAT2A, we found eight SNPs located in ALDH18A1 and two in MAT2A. Single-SNP association analysis showed that most of the 10 SNPs of these two genes were significantly associated with the milk yield traits, 305-day milk yield, fat yield, and protein yield in the first and second lactations (corrected p ≤ 0.0488). Using Haploview 4.2, we found that the seven SNPs of ALDH18A1 formed two haplotype blocks; subsequently, the haplotype-based association analysis showed that both haplotypes were significantly associated with 305-day milk yield, fat yield, and protein yield (corrected p ≤ 0.014). Furthermore, by Jaspar and Genomatix software, we found that 26:g.17130318 C>A and 11:g.49472723G>C, respectively, in the 5′ flanking region of ALDH18A1 and MAT2A genes changed the transcription factor binding sites (TFBSs), which might regulate the expression of corresponding genes to affect the phenotypes of milk production traits. Therefore, these two SNPs were considered as potential functional mutations, but they also require further verification. In summary, ALDH18A1 and MAT2A were proved to probably have genetic effects on milk production traits, and their valuable SNPs might be used as candidate genetic markers for dairy cattle’s genomic selection (GS).

Lactational performance, feeding behavior, ruminal fermentation and nutrient digestibility in dairy cows fed whole-plant faba bean silage-based diet with fibrolytic enzyme

Whole-plant faba bean silage has a high content in indigestible fiber. Improvement of fiber digestibility of faba bean silage would benefit animal production. However, there is no study on pretreating fibrolytic enzyme in whole-plant faba bean silage-based diet for dairy cows on animal performance. The objectives of this study were to evaluate the effects of pretreating whole-plant faba bean silage-baseddiet with fibrolytic enzyme (a mixture of xylanase and cellulase; AB Vista, UK) derived from Trichoderma reesei(FETR) on lactational performance, digestibility, ruminal fermentation characteristics, and feeding behavior of dairy cows. The animal trial was conducted using eight lactating Holstein cows (BW = 710 ± 44 kg and Days in Milk (DIM) = 121 ± 17 days) with four levels of FETR (0, 0.5, 0.75, and 1.0 mL of FETR/kg DM of silage) in a replicated Latin square design. These enzyme treatments were selected based on the previous in situ and in vitro findings that showed positive responses to the whole-plant faba bean silage. The enzyme treatments were directly applied on the silage prior to mixing process. The total mixed rations contained 31% of faba bean silage, 14% of grass hay, 3.5% of straw, 30% of barley and corn grain and 21.5% of concentrate. There was no significant difference of applying FETR on nutrient intake (P > 0.05) except for CP intake, which was reduced in FETR group compared to control (P < 0.01, 4.4 vs 4.54 kg/d). There was a linear effect found in NDF digestibility when treated with FETR, where maximum improvement was achieved with 0.5 mL of FETR application. The milk fat yield, percentage of milk fat and fat-corrected milk were linearly affected by the increasing level of enzyme. The cows fed a diet supplemented with enzymes tended to have a lower milk fat. Feed efficiency linearly responded to incremental levels of FETR. There was no enzyme effect on feeding behavior and nitrogen balance and utilization. Results from this study indicated that supplementing fibrolytic enzyme on whole-plant faba bean silage diets for dairy cows improved lactational performance, intake and digestibility with 0.5 mL of FETR application. However, adding higher enzyme level resulted in negative effects on animal performance.