Genetic parameters for dry matter intake, energy balance, residual energy intake, and liability to diseases in German Holstein and Fleckvieh dairy cows.

Selection for feed efficiency (FE) is a hot topic in dairy cow breeding. Dry matter intake (DMI) and residual energy intake (REI) are mostly discussed as new selection traits. Selection for lower DMI or REI seems to increase FE if other traits, such as milk yield or health, are not affected negatively. However, genetic relationships with other traits have not been adequately investigated because of the difficulties in recording sufficient feed intake data for genetic evaluations. The aim of this study was to examine the genetic relationships between FE-related traits and liability to diseases throughout lactation. First, heritabilities for all traits are presented. Subsequently, genetic correlations between DMI, energy-corrected milk yield, energy balance (EB), and REI on the one hand and 3 disease categories (mastitis, claw and leg diseases, and all diseases) on the other throughout lactation in German Holstein (GH) dairy cows are illustrated. Production and health data from the projects optiKuh and eMissionCow were used. Data consisted of weekly observations recorded over a 325-wk period in 2,387 GH and over a 300-wk period in 632 Fleckvieh (FV) primiparous and multiparous dairy cows from 13 dairy research farms in Germany. Variance and covariance components were estimated univariately or bivariately with linear random regression models for production data and threshold random regression models for health data. Heritabilities for DMI, EB, and REI were on average 0.17 and 0.15, 0.14 and 0.15, as well as 0.11 and 0.14 in GH and FV, respectively. Heritabilities on the underlying scale for mastitis, claw and leg diseases, and all diseases were on average 0.17 and 0.16, 0.18 and 0.12, as well as 0.15 and 0.11 in GH and FV, respectively. In GH, almost all genetic correlations were negative, especially in early lactation. Within the first 50 d in milk, genetic correlations between DMI and REI on the one hand and disease categories on the other ranged from -0.25 to -0.14 for mastitis, from -0.31 to -0.13 for claw and leg diseases, and from -0.58 to -0.30 for all diseases. Consequently, selection for lower DMI or REI could lead to a higher liability to diseases, especially in early lactation. A possibility to mitigate these undesirable side effects could be lactation stage-specific selection for FE. For FV, further studies with more data are needed to assess genetic relationships.

Residual energy intake, energy balance, and liability to diseases: Genetic parameters and relationships in German Holstein dairy cows.

Residual energy intake (REI) is an often-suggested trait for direct selection of dairy cows for feed efficiency. Cows with lower REI seem to be more efficient but are also in a more severe negative energy balance (EB), especially in early lactation. A negative EB leads to a higher liability to diseases. Due to this fact, this study aims to investigate the genetic relationship between REI and liability to diseases. Health and production data were recorded from 1,370 German Holstein dairy cows from 8 research farms over a period of 2 yr. We calculated 2 phenotypes for REI that considered the following energy sinks: milk energy content, metabolic body weight, body weight change, body condition score, and body condition score change. Genetic parameters were estimated with threshold or linear random regression models from days in milk (DIM) 1 to 305. Heritabilities for REI, EB, and all diseases ranged from 0.12 to 0.39, 0.15 to 0.31, and 0.09 to 0.20, respectively. Genetic correlations between selected DIM for REI and EB were higher for adjacent DIM than for more distant DIM. Pearson correlation coefficients between estimated breeding values (EBV) for REI and EB varied between 0.47 and 0.81; they were highest in mid lactation. Correlations between EBV for all diseases and REI as well as EB were negative, with lowest values in early lactation. Within the first 50 DIM, proportions of diseased days for cows with lowest EBV for REI were almost twice as high as for cows with highest EBV for REI. In conclusion, selecting dairy cows for lower REI should be treated with caution because of an unfavorable relationship with liability to diseases, especially in early lactation.

Relationship between milk constituents from milk testing and health, feeding, and metabolic data of dairy cows.

A new evaluation scheme to assess the nutritional status of dairy cows on the basis of milk constituents was derived from 7.37 million German records of milk testing. The aim of this work was to validate this new scheme. Two data sets with fertility and health information (data set A) and with measured energy and nutrient intake and metabolic characteristics (data set B) were analyzed. Data set A included 32 commercial dairy farms in northeast Germany, with 72,982 records of 43,863 German Holstein cows; data set B included 12 German experimental farms, with 49,275 records of 1,650 German Holstein, Simmental, and Brown Swiss cows. Milk traits were linked to health disorders and metabolic and feeding characteristics. Frequently used limits of milk constituents were compared with ranges of the new "Dummerstorf feeding evaluation." To distinguish an optimal from a deficient energy supply, a milk protein content ≥3.20% (previously used) and a milk fat:protein ratio (FPR) ≤1.4 (new scheme) were chosen and compared with feed energy intake in relation to demand. Energy status was more often correctly assigned by FPR than by milk protein content (80.7 and 68.7%, respectively). Over all data, the new optimum range of milk urea between 150 and 250 mg/L was better suited to dietary crude protein intake in relation to demand than the previously used range of 150 to 300 mg/L (42.4 and 38.0%, respectively). Ketosis or blood values associated with ketosis such as ß-hydroxybutyrate >1.2 mmol/L or nonesterified fatty acids >1,000 µmol/L, as well as strong mobilization of body weight ≥1.5 kg/d, loss of back fat thickness ≥10 mm, and loss of body condition score ≥1 unit in first 60 days in milk were compared with different milk trait thresholds. For the updated scheme FPR >1.4 was used in combination with either milk protein content below the individual statistical lower limit of milk protein content, or milk fat content greater than the individual statistical upper limit of milk fat content; FPR >1.5 was taken as a frequently used threshold. For these ketosis indicators, the new scheme had higher sensitivities. Energy oversupply or the risk of overconditioning could not be identified by milk constituents alone. Urinary acid-base content was not related to milk content. Similarly, milk testing data did not allow a clear distinction to be made between the diagnoses of acidosis and, for example, ketosis. Essential requirements for good herd management are the continuous observation of milk testing data in combination with other established instruments of feeding and animal monitoring.

Lactation curves and model evaluation for feed intake and energy balance in dairy cows.

A good health status of high-performing dairy cows is essential for successful production. Feed intake affects the metabolic stability of dairy cows and can be used as a measurement for energy balance. By implementing feed intake and energy balance into the breeding goal, these traits provide great potential for an improvement in the health of dairy cows by breeders. In this study, fixed and random regression models were tested to establish appropriate models for a further analysis of this approach. A total of 1,374 Holstein-Friesian cows and 327 Simmental cows (SI) from 12 German research farms participating in a collaboration called optiKuh were phenotyped. Feed intake data recording was standardized across farms, and energy balance was calculated using phenotypic information on milk yield, milk ingredients, live weight, gestation stage, and feed intake. The phenotypic data set consisted of a total of 40,012 Holstein-Friesian and 16,996 SI with average weekly dry matter intakes of 21.8 ± 4.3 and 20.2 ± 3.6 kg/d, respectively. Observations of days in milk 1 to 350 were used to evaluate the best-fitting models and to estimate the repeatability and correlations between cow effects at different stages for feed intake and energy balance. Four parametric functions (Ali and Schaeffer and Legendre polynomials of second, third, and fourth degree) were compared to model the lactation curves. Based on the corrected Akaike information criterion and the Bayesian information criterion, the goodness of fit was evaluated to choose the best-fitting model for the finest description of lactation curves for the traits energy balance and feed intake. Legendre polynomial fourth degree was the best-fitting model for random regression models. In contrast, Ali and Schaeffer was the best choice for fixed regression models. Feed intake and energy balance acted as expected: the feed intake increased slowly at the beginning of lactation and the negative energy balance switched to a positive range around 40 to 80 d of lactation. The repeatabilities of both traits were quite similar and the repeatabilities for SI were the highest for both traits. Additionally, correlations between cow effects were closest between early days in milk. These results emphasize the possibility that the unique optiKuh data set can be used for further genetic analyses to enable genomic selection for feed intake or energy balance.

Short communication: Pro- and antioxidative indicators in serum of dairy cows during late pregnancy and early lactation: Testing the effects of parity, different dietary energy levels, and farm.

Dairy cows face metabolic challenges in the transition from late pregnancy to early lactation. The energy demands for the growing fetus and the onset of milk production are increasing but voluntary feed intake often decreases around parturition and cannot meet these demands. This energy balance, among others, can change the oxidative status. Oxidative stress occurs when antioxidant defense mechanisms are not sufficient to cope with the increasing generation of reactive oxygen species. Our objectives were to investigate (1) the effect of parity on the oxidative status of dairy cows (n = 247) in late pregnancy and early lactation; and (2) the effect of different inclusion rates of concentrate feeding (150 vs. 250 g/kg of energy-corrected milk) during early lactation on 2 farms including 87 cows in total. In addition, we aimed to compare the oxidative status across the 2 farms using equal portions of concentrate feeding. For these purposes, we measured concentrations of the derivatives of reactive oxygen metabolites (dROM) and the ferric reducing ability (FRAP) in serum on d -50, -14, +8, +28, and +100 relative to calving. Furthermore, we calculated the oxidative status index (OSi) as dROM/FRAP × 100. Data were analyzed using a linear mixed model. Cows in the first and second lactations had greater dROM, FRAP, and OSi than cows in their third and greater lactations. Hence, supporting the antioxidative side of the balance might be of particular importance in the first and second lactations. Feeding different amounts of concentrates did not affect dROM, FRAP, or OSi under our experimental conditions, suggesting that the relatively small differences in energy intake were not affecting the oxidative status. Comparing farms, cows from one farm were notable for having greater dROM and lower FRAP, resulting in a greater OSi compared with cows on the other farm. Milk yield showed a time by farm interaction with 7% less milk on d 100 on the farm with the greater OSi. Moreover, cows on that farm had 1.4-fold greater ß-hydroxybutyrate concentrations. Our results emphasize the value of assessing oxidative status with regard to both the pro- and antioxidative sides, and support the association between oxidative and metabolic status. Further investigations are needed to determine the applicability of OSi as a prognostic tool during early lactation and to determine which factors have the greatest influence on oxidative status.

Association between Fatty Acid Composition in Hair and Energy Availability during Early Lactation in Simmental and German Holstein Cows.

This study examined (1) if fatty acids in bovine hair are influenced by dietary energy levels and (2) if the relationship between energy availability and fatty acids in hair persists across breeds and farms. Sixty-two and 59 Fleckvieh (Simmental), and 55 German Holstein cows from three farms, respectively, were fed two levels of energy concentration of roughage (6.1 and 6.5 MJ net energy for lactation/kg dry matter) and two levels of concentrate supply (150 and 250 g/kg energy-corrected milk). The average body weight was 727 kg (Simmental) and 668 kg (Holstein). The average lactation number was 3.1. Hair samples were taken in lactation weeks 4 and 8. In Simmental cows, a lower energy deficit due to a relatively higher energy intake from high energy concentration of the roughage was associated with higher C18:2n-6 and C18:3n-3 contents in hair at week 8. In cows from all three farms, higher energy intake between lactation weeks 2 and 6 correlated with higher content of C18:2n-6 in hair samples taken in lactation weeks 4 and 8. No correlation was found for C12:0. These results provide the first evidence that increased energy intake increases the contents of C18:2n-6 in hair.

Circulating adiponectin concentrations during the transition from pregnancy to lactation in high-yielding dairy cows: testing the effects of farm, parity, and dietary energy level in large animal numbers.

Dairy cows experience a negative energy balance due to increasing energy demands and insufficient voluntary feed intake in the transition from late pregnancy to early lactation. For supplying sufficient energy toward the conceptus and the mammary gland, insulin sensitivity in peripheral tissues is reduced leading to adipose tissue mobilization. Adiponectin, an insulin-sensitizing adipokine, is presumably related to energy metabolism and could play an important role in these metabolic adaptations. We hypothesize (1) that primiparous cows would differ from pluriparous cows in their circulating adiponectin concentrations during the transition from late pregnancy to early lactation and (2) that feeding different energy levels would affect the adiponectin concentrations during early lactation in dairy cows. For the first hypothesis, we examined 201 primiparous and 456 pluriparous Holstein dairy cows on three experimental farms. Ante partum, primiparous cows had lower adiponectin and greater NEFA concentrations than pluriparous cows, but vice versa post partum. Hence, adiponectin might be involved in the energy partitioning in primiparous cows (conceptus and lactation vs other still growing body tissues) with changing priorities from pregnancy to lactation. For the second hypothesis, 110 primiparous and 558 pluriparous Holstein and Simmental dairy cows in six experimental farms received either roughage with 6.1 or 6.5 MJ NEl/kg dry matter (adjusted with different amounts of wheat straw) ad libitum, combined with either 150 or 250 g concentrates/kg energy corrected milk. Greater amounts of concentrate lead to greater milk yield, but did not affect the blood variables. The higher energy level in the roughage led to greater glucose and IGF-1 but lower adiponectin in pluriparous cows. Further studies are needed to elucidate the mechanisms behind the roughage effect and its metabolic consequences.