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.     

Genetics of grass dry matter intake, energy balance, and digestibility in grazing irish dairy cows

The objective of this study was to estimate genetic parameters for grass dry matter intake (DMI), energy balance (EB), and cow internal digestibility (IDG) in grazing Holstein-Friesian dairy cows. Grass DMI was estimated up to 4 times per lactation on 1,588 lactations from 755 cows on 2 research farms in southern Ireland. Simultaneously measured milk production and BW records were used to calculate EB. Cow IDG, measured as the ratio of feed and fecal concentrations of the natural odd carbon-chain n-alkane pentatriacontane, was available on 583 lactations from 238 cows. Random regression and multitrait animal models were used to estimate residual, additive genetic and permanent environmental (co)variances across lactations. Results were similar for both models. Heritability for DMI, EB, and IDG across lactation varied from 0.10 [8 days in milk (DIM)] to 0.30 (169 DIM), from 0.06 (29 DIM) to 0.29 (305 DIM), and from 0.08 (50 DIM) to 0.45 (305 DIM), respectively, when estimated using the random regression model. Genetic correlations within each trait tended to decrease as the interval between periods compared increased for DMI and EB, whereas the correlations with IDG in early lactation were weakest when measured midlactation. The lowest correlation between any 2 periods was 0.10, −0.36, and −0.04 for DMI, EB, and IDG, respectively, suggesting the effect of different genes at different stages of lactations. Eigenvalues and associated eigenfunctions of the additive genetic covariance matrix revealed considerable genetic variation among animals in the shape of the lactation profiles for DMI, EB, and IDG. Genetic parameters presented are the first estimates from dairy cows fed predominantly grazed grass and imply that genetic improvement in DMI, EB, and IDG in Holstein-Friesian cows fed predominantly grazed grass is possible.     

The effect of dystocia on the dry matter intake and behavior of Holstein cows

Dairy cows that have a difficult calf delivery (dystocia) are more likely to develop health complications after calving, reducing productivity and welfare. Understanding the behavioral cues of dystocia may facilitate prompt obstetric assistance and reduce the long-term effect of the challenging delivery. The aim of this study was to describe the effects of dystocia on dairy cow behavior during the period around calving and to assess the use of these behaviors as potential indicators of dystocia. Individual dry matter intake, water intake, feeding and drinking time, meal size, standing time, and number of transitions from standing to lying positions (bouts) were recorded during the 48-h period before and after the time of calf delivery for 22 Holstein cows [11 cows with dystocia and 11 cows with unassisted delivery (eutocia)]. Cows with dystocia consumed 1.9 kg less during the 48 h before calving compared with cows with eutocia (14.3 ± 1.0 vs. 16.2 ± 1.0 kg, respectively), and this difference increased to 2.6 kg in the 24 h before calving (8.3 ± 0.7 vs. 10.9 ± 0.7 kg/d). There were no differences in drinking time between the groups, but cows with dystocia consumed less water 24 h before calving (22.4 ± 4.4 vs. 36.2 ± 4.4 kg/d, respectively) and consumed more water during the 24-h period after calving (56.9 ± 3.1 vs. 48.7 ± 3.1 kg/d) compared with cows with eutocia. Cows with dystocia transitioned from standing to lying positions more frequently than cows without dystocia beginning 24 h before calving (10.9 ± 0.7 vs. 8.3 ± 0.7 bouts/d). Dry matter intake and standing bouts in the 24 h before calving were the most accurate variables in discriminating between cows with and without dystocia, suggesting that cows with dystocia begin to alter their behavior beginning 24 h before calving.     

Genetic and genomic dissection of dry matter intake at different lactation stages in primiparous Holstein cows

Dry matter intake (DMI) and feed efficiency are economically relevant traits. Simultaneous selection for low DMI and high milk yield might improve feed efficiency, but bears the risk of aggravating the negative energy balance and related health problems in early lactation. Lactation stage-specific selection might provide a possibility to optimize the trajectory of DMI across days in milk (DIM), but requires in-depth knowledge about genetic parameters within and across lactation stages. Within the current study, daily heritabilities and genetic correlations between DMI records from different lactation stages were estimated using random regression models based on 910 primiparous Holstein cows. The heritability estimates from DIM 11 to 180 follow a slightly parabolic curve varying from 0.26 (DIM 121) to 0.37 (DIM 11 and 180). Genetic correlations estimated between DIM 11, 30, 80, 130, and 180 were all positive, ranging from 0.29 (DIM 11 and 180) to 0.97 (DIM 11 and 30; i.e., the correlations are inversely related to the length of the interval between compared DIM). Deregressed estimated breeding values for the same lactation days were used as phenotypes in sequential genome-wide association studies using 681 cows drawn from the study population and genotyped for the Illumina SNP50 BeadChip (Illumina Inc., San Diego, CA). A total of 21 SNP on 10 chromosomes exceeded the chromosome-wise significance threshold for at least 1 analyzed DIM, pointing to some interesting candidate genes directly involved in the regulation of feed intake. Association signals were restricted to certain lactation stages, thus supporting the genetic correlations. Partitioning the explained variance onto chromosomes revealed a large contribution of Bos taurus autosome 7 not harboring any associated marker in the current study. The results contribute to the knowledge about the genetic architecture of the complex phenotype DMI and might provide valuable information for future selection efforts.     

Analysis of the genetic architecture of energy balance and its major determinants dry matter intake and energy-corrected milk yield in primiparous Holstein cows

The focus of modern dairy cow breeding programs has shifted from being mainly yield based toward balanced goals that increasingly consider functional traits such as fertility, metabolic stability, and longevity. To improve these traits, a less pronounced energy deficit postpartum is considered a key challenge. On the other hand, feed efficiency and methane emissions are gaining importance, possibly leading to conflicts in the design of breeding goals. Dry matter intake (DMI) is one of the major determinants of energy balance (EB), and recently some efforts were undertaken to include DMI in genomic breeding programs. However, there is not yet a consensus on how this should be achieved as there are different goals in the course of lactation (i.e., reducing energy deficit postpartum vs. subsequently improving feed efficiency). Thus, the aim of this study was to gain more insight into the genetic architecture of energy metabolism across lactation by genetically dissecting EB and its major determinants DMI and energy-corrected milk (ECM) yield at different lactation stages applying random regression methodology and univariate and multivariate genomic analyses to data from 1,174 primiparous Holstein cows. Daily heritability estimates ranged from 0.29 to 0.49, 0.26 to 0.37, and 0.58 to 0.68 for EB, DMI, and ECM, respectively, across the first 180 d in milk (DIM). Genetic correlations between ECM and DMI were positive, ranging from 0.09 (DIM 11) to 0.36 (DIM 180). However, ECM and EB were negatively correlated (r_g = ?0.26 to ?0.59). The strongest relationship was found at the onset of lactation, indicating that selection for increased milk yield at this stage will result in a more severe energy deficit postpartum. The results also indicate that EB is more affected by DMI (r_g = 0.71 to 0.81) than by its other major determinant, ECM. Thus, breeding for a higher DMI in early lactation seems to be a promising strategy to improve the energy status of dairy cows. We found evidence that genetic regulation of energy homeostasis is complex, with trait- and lactation stage-specific quantitative trait loci suggesting that the trajectories of the analyzed traits can be optimized as mentioned above. Especially from the multivariate genomic analyses, we were able to draw some conclusions on the mechanisms involved and identified the genes encoding fumarate hydratase and adiponectin as highly promising candidates for EB, which will be further analyzed.     

Short communication: Added value of rumination time for the prediction of dry matter intake in lactating dairy cows

The objective of the current study was to quantify the change in the prediction of dry matter intake (DMI) resulting from the inclusion of rumination time (RT) in the 2001 National Research Council (NRC) DMI prediction model. Forty-one Holstein cows fed the same total mixed ration were involved in a 10-wk study. Individual DMI were measured daily. The accuracy and precision of the original NRC prediction model, based on body weight, fat-corrected milk, and week of lactation as independent variables, was compared with the accuracy and precision of the same model with RT as an additional independent variable. The RT estimate was significant in the model developed but had a low value (0.031 kg/h). Root mean square prediction errors were very similar in the 2 models (1.70 and 1.68 kg/d) as were the other indicators (R², linear bias, random error, and concordance correlation coefficient) selected to compare the models in this study. These results indicate no gain in DMI prediction precision or accuracy when RT is included in the NRC model.     

Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis

The objective of this study was to compare mid-infrared reflectance spectroscopy (MIRS) analysis of milk and near-infrared reflectance spectroscopy (NIRS) analysis of feces with regard to their ability to predict the dry matter intake (DMI) of lactating grazing dairy cows. A data set comprising 1,074 records of DMI from 457 cows was available for analysis. Linear regression and partial least squares regression were used to develop the equations using the following variables: (1) milk yield (MY), fat percentage, protein percentage, body weight (BW), stage of lactation (SOL), and parity (benchmark equation); (2) MIRS wavelengths; (3) MIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (4) NIRS wavelengths; (5) NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity; (6) MIRS and NIRS wavelengths; and (7) MIRS wavelengths, NIRS wavelengths, MY, fat percentage, protein percentage, BW, SOL, and parity. The equations were validated both within herd using animals from similar experiments and across herds using animals from independent experiments. The accuracy of equations was greater for within-herd validation compared with across-herds validation. Across-herds validation was deemed the more suitable method to assess equations for robustness and real-world application. The benchmark equation was more accurate [coefficient of determination (R²) = 0.60; root mean squared error (RMSE) = 1.68 kg] than MIRS alone (R² = 0.30; RMSE = 2.23 kg) or NIRS alone (R² = 0.16; RMSE = 2.43 kg). The combination of the benchmark equation with MIRS (R² = 0.64; RMSE = 1.59 kg) resulted in slightly superior fitting statistics compared with the benchmark equation alone. The combination of the benchmark equation with NIRS (R² = 0.58; RMSE = 1.71 kg) did not result in a more accurate prediction equation than the benchmark equation. The combination of MIRS and NIRS wavelengths resulted in superior fitting statistics compared with either method alone (R² = 0.36; RMSE = 2.15 kg). The combination of the benchmark equation and MIRS and NIRS wavelengths resulted in the most accurate equation (R² = 0.68; RMSE = 1.52 kg). A further analysis demonstrated that Holstein-Friesian cows could predict the DMI of Jersey × Holstein-Friesian crossbred cows using both MIRS and NIRS. Similarly, the Jersey × Holstein-Friesian animals could predict the DMI of Holstein-Friesian cows using both MIRS and NIRS. The equations developed in this study have the capacity to predict DMI of grazing dairy cows. From a practicality perspective, MIRS in combination with variables in the benchmark equation is the most suitable equation because MIRS is currently used on all milk-recorded milk samples from dairy cows.     

Effects of dietary energy allowance and decline in dry matter intake during the dry period on responses to glucose and insulin in transition dairy cows

We assessed whether high energy intake during the early dry period [144% of metabolizable energy (ME) requirements/d] followed by a gradual restriction of energy intake in the close-up dry period (119% of ME/d; HEI) impaired whole-body insulin sensitivity compared with a controlled energy intake (100% of ME/d; CEI) throughout the 6-wk dry period. Multiparous Ayrshire dairy cows (n = 16) were blocked by body weight, body condition score, and expected date of parturition and were used in a randomized complete block design until 10 d after parturition. Cows were fed either HEI or CEI diets based on grass silage during the first 3 wk of the dry period and grass silage supplemented with a commercial concentrate (30% of ME intake) during the final 3 wk of gestation. After calving, all cows were fed grass silage ad libitum and an increasing amount of commercial concentrate (maximum 9 kg at d 10 postpartum). Intravenous glucose tolerance tests (IVGTT) and intravenous insulin challenges were performed ?10 ± 5 d (n = 15) and +10 ± 1 d (n = 14) relative to parturition. Following glucose injection, we did not find any treatment effects on glucose and insulin responses. The prepartal nonesterified fatty acid (NEFA) response of the HEI group was blunted, basal NEFA and the decrement of NEFA were smaller, and the area under the response curve (AUC) of NEFA was less negative in HEI cows than in CEI cows. The NEFA response reversed after parturition; the NEFA AUC of the HEI group was more negative than that of the CEI group. We did not find similar responses after insulin injection. Across the treatments, NEFA AUC correlated strongly with the basal NEFA concentration during the IVGTT pre- and postpartum. Calculated and model-based indices characterizing the overall glucose tolerance and β-cell function and the insulin sensitivity were higher after parturition than during the dry period. Consistent with the lower basal insulin, the acute insulin release after the glucose infusion was smaller in postpartal IVGTT than in prepartal IVGTT. The results suggest that whole-body insulin sensitivity of the cows increased after parturition. However, the role of peripheral insulin sensitivity in the regulation of glucose partitioning seems to be minor relative to the major change in insulin secretion and clearance during the periparturient period.     

Prediction of dry matter intake throughout lactation in a dynamic model of dairy cow performance

In the dynamic modeling of dairy cow performance over a full lactation, the difference between net energy intake and net energy used for maintenance, growth, and output in milk accumulates in body reserves. A simple dynamic model of net energy balance was constructed to select, out of some common dry matter intake (DMI) prediction equations, the one that resulted in a minimum cumulative bias in body energy deposition. Dry matter intake was predicted using the Cornell Net Carbohydrate and Protein System, Agricultural Research Council, or National Research Council (NRC) DMI equations from body weight (BW) and predicted fat-corrected milk yield. The instantaneous BW of cows at progressive weeks of lactation was simulated as the numerical integral of the BW change obtained from the predicted net energy balance. Predicted DMI and BW from each DMI equation, using either of 2 equations to describe maintenance energy expenditures, were compared statistically against observed data from 21 herd average published full lactation data sets. All DMI equations underpredicted BW and DMI, but the NRC DMI equation resulted in the minimum cumulative error in predicted BW and DMI. As a general solution to prevent predicted BW from deviating substantially over time from the observed BW, a lipostatic feedback mechanism was integrated into the NRC DMI equation as a 2-parameter linear function of the relative size of simulated body reserves and week of lactation. Residual sum of squares was reduced on average by 52% for BW predictions and by 41% for DMI predictions by inclusion of the negative feedback with parameters taken from the average of all 21 least squares fits. Similarly, root mean square prediction error (%) was reduced by 30% on average for BW predictions and by 23% for DMI predictions. Inclusion of a feedback of energy reserves onto predicted DMI, simulating lipostatic regulation of BW, solved the problem of final BW deviation within a dynamic model and improved its DMI prediction to a satisfactory level.     

Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle

Feed efficiency has been widely studied in many areas of dairy science and is currently seeing renewed interest in the field of breeding and genetics. A critical part of determining how efficiently an animal utilizes feed is accurately measuring individual dry matter (DM) intake. Currently, multiple methods are used to measure feed intake or determine the DM content of that feed, resulting in different levels of accuracy of measurement. Furthermore, the scale at which data need to be collected for use in genetic analyses makes some methodologies impractical. This systematic review aims to provide an overview of the current methodologies used to measure both feed intake in ruminants and DM content of feedstuffs, current methods to predict individual DM intake, and applications of large-scale intake measurements. Overall, advances in milk spectral data analysis present a promising method of estimating individual DM intake on a herd scale with further validation of prediction models. Although measurements of individual feed intake rely on the same underlying principle, the methods selected are largely dictated by the costs of capital, labor, and necessary analyses. Finally, DM methodologies were synthesized into a comprehensive protocol for use in a variety of feedstuffs.     

Effects of prepartum roughage neutral detergent fiber levels on periparturient dry matter intake, metabolism, and lactation in heat-stressed dairy cows

Heat stress of lactating cattle results in dramatic reductions in dry matter intake (DMI). As a result, energy input cannot satisfy energy needs and thus accelerates body fat mobilization. Decreasing the level of roughage neutral detergent fiber (NDF) in prepartum diets, and thereby increasing the amount of nonfiber carbohydrates, may provide an adequate supply of energy and glucose precursors to maintain and minimize the decrease in DMI while reducing mobilization of adipose tissue. The effects of 3-wk prepartum diets containing different amounts of roughage NDF on DMI, blood metabolites, and lactation performance of dairy cows were investigated under summer conditions in Thailand. Thirty cross-bred cows (87.5% Holstein × 12.5% Sahiwal) were dried off 60 d before their expected calving date and were assigned immediately to a nonlactating cow diet containing the net energy for lactation recommended by the National Research Council (2001) model. The treatment diets contained 17.4, 19.2, and 21.0% DM as roughage NDF from bana grass (Pennisetum purpureum × Pennisetum glaucum) silage. Levels of concentrate NDF were 39.8, 40.2, and 38.6% of dietary NDF, so the levels of dietary NDF were 28.9, 32.1, and 34.2% of DM. After parturition, all cows received a lactating cow diet containing 12.7% roughage NDF and 23% dietary NDF. During the entire experiment, the minimum and maximum temperature-humidity index averaged 77.7 and 86.8, respectively, indicating conditions appropriate for the induction of extreme heat stress. As parturition approached, DMI decreased steadily, resulting in a 12.9, 25, and 32.8% decrease in DMI from d −21 until calving for nonlactating cows fed prepartum diets containing 17.4, 19.2, and 21% roughage NDF, respectively. During the 3-wk prepartum period, intakes of DM and net energy for lactation and concentrations of plasma glucose and serum insulin were higher for cows fed diets containing less roughage NDF. In cows fed the 3-wk prepartum diets containing less roughage NDF, calf birth weights, milk yield, and 4% fat-corrected milk were higher, whereas periparturient concentrations of serum nonesterified fatty acids and plasma β-hydroxybutyrate were lower. There was a carryover effect of the prepartum diet on serum nonesterified fatty acids and plasma β-hydroxybutyrate during the first 7 d in milk, and therefore on milk production. These results suggest that feeding diets containing decreased amounts of roughage NDF during the 3-wk prepartum period may minimize the decrease in DMI and lipid mobilization as parturition approaches. This strategy may thus minimize the effect of hormonal factors and heat stress on periparturient cows.     

Analysis of water intake and dry matter intake using different lactation curve models

The objective was to evaluate 6 different lactation curve models for daily water and dry matter intake. Data originated from the Futterkamp dairy research farm of the Chamber of Agriculture of Schleswig-Holstein in Germany. A data set of about 23,000 observations from 193 Holstein cows was used. Average daily water and dry matter intake were 82.3 and 19.8 kg, respectively. The basic linear mixed model included the fixed effects of parity and test-day within feeding group. Additionally, 6 different functions were tested for the fixed effect of lactation curve and the individual (random) effect of cow-lactation curve. Furthermore, the autocorrelation between repeated measures was modeled with the spatial (power) covariance structure. Model fit was evaluated by the likelihood ratio test, Akaike's and Bayesian information criteria, and the analysis of mean residual at different days in milk. The Ali and Schaeffer function was best suited for modeling the fixed lactation curve for both traits. A Legendre polynomial of order 4 delivered the best model fit for the random effect of cow-lactation. Applying the error covariance structure led to a significantly better model fit and indicated that repeated measures were autocorrelated. Generally, the best information criteria values were yielded by the most complex model using the Ali and Schaeffer function and Legendre polynomial of order 4 to model the average lactation and cow-specific lactation curves, respectively, with inclusion of the spatial (power) error covariance structure. This model is recommended for the analysis of water and dry matter intake including missing observations to obtain estimation of correct statistical inference and valid variance components.     

Defining the optimal period length and stage of growth or lactation to estimate residual feed intake in dairy cows

Residual feed intake (RFI) is an estimate of animal feed efficiency, calculated as the difference between observed and expected feed intake. Expected intake typically is derived from a multiple regression model of dry matter intake on energy sinks, including maintenance and growth in growing animals, or maintenance, gain in body reserves, and milk production in lactating animals. The best period during the production cycle of a dairy cow to estimate RFI is not clear. Here, we characterized RFI in growing Holstein heifers (RFI_Growth; ∼10 to 14 mo of age; n = 226) and cows throughout a 305-d lactation (RFI_Lac-Full; n = 118). The goals were to characterize relationships between RFI estimated at different production stages of the dairy cow; determine effects of selection for efficiency during growth on subsequent lactation and feed efficiency; and identify the most desirable testing scheme for RFI_Lac-Full. For RFI_Growth, intake was predicted from multiple linear regression of metabolizable energy (ME) intake on mid-test body weight (BW)^0.75 and average daily gain (ADG). For RFI_Lac-Full, predicted intake was based on regression of BW^0.75, ADG, and energy-corrected milk yield. Mean energy intake of the least and most efficient growing heifers (±0.5 standard deviations from mean RFI_Growth of 0) differed by 3.01 Mcal of ME/d, but the groups showed no difference in mid-test BW or ADG. Phenotypic correlation between RFI_Growth and RFI of heifers estimated in the first 100 d in milk (RFI_Lac100DIM; n = 130) was 0.37. Ranking of these heifers as least (mean + 0.5 standard deviations), middle, or most efficient (mean – 0.5 standard deviations) based on RFI_Growth resulted in 43% maintaining the same ranking by RFI_Lac100DIM. On average, the most efficient heifers ate 3.27 Mcal of ME/d less during the first 100 DIM than the least efficient heifers, but exhibited no differences in average energy-corrected milk yield, ADG, or BW. The correlation between RFI_Lac100DIM and RFI_Lac-Full was 0.72. Thus, RFI_Growth may serve as an indicator trait for RFI during lactation, and selection for heifers exhibiting low RFI_Growth should improve overall herd feed efficiency during lactation. Correlation analysis between RFI_Lac-Full (10 to 305 DIM) and subperiod estimates of RFI during lactation indicated a test period of 64 to 70 d in duration occurring between 150 to 220 DIM provided a reliable approximation (r ≥ 0.90) of RFI_Lac-Full among the test periods evaluated.     

Prediction and validation of residual feed intake and dry matter intake in Danish lactating dairy cows using mid-infrared spectroscopy of milk

The present study explored the effectiveness of Fourier transform mid-infrared (FT-IR) spectral profiles as a predictor for dry matter intake (DMI) and residual feed intake (RFI). The partial least squares regression method was used to develop the prediction models. The models were validated using different external test sets, one randomly leaving out 20% of the records (validation A), the second randomly leaving out 20% of cows (validation B), and a third (for DMI prediction models) randomly leaving out one cow (validation C). The data included 1,044 records from 140 cows; 97 were Danish Holstein and 43 Danish Jersey. Results showed better accuracies for validation A compared with other validation methods. Milk yield (MY) contributed largely to DMI prediction; MY explained 59% of the variation and the validated model error root mean square error of prediction (RMSEP) was 2.24 kg. The model was improved by adding live weight (LW) as an additional predictor trait, where the accuracy R² increased from 0.59 to 0.72 and error RMSEP decreased from 2.24 to 1.83 kg. When only the milk FT-IR spectral profile was used in DMI prediction, a lower prediction ability was obtained, with R² = 0.30 and RMSEP = 2.91 kg. However, once the spectral information was added, along with MY and LW as predictors, model accuracy improved and R² increased to 0.81 and RMSEP decreased to 1.49 kg. Prediction accuracies of RFI changed throughout lactation. The RFI prediction model for the early-lactation stage was better compared with across lactation or mid- and late-lactation stages, with R² = 0.46 and RMSEP = 1.70. The most important spectral wavenumbers that contributed to DMI and RFI prediction models included fat, protein, and lactose peaks. Comparable prediction results were obtained when using infrared-predicted fat, protein, and lactose instead of full spectra, indicating that FT-IR spectral data do not add significant new information to improve DMI and RFI prediction models. Therefore, in practice, if full FT-IR spectral data are not stored, it is possible to achieve similar DMI or RFI prediction results based on standard milk control data. For DMI, the milk fat region was responsible for the major variation in milk spectra; for RFI, the major variation in milk spectra was within the milk protein region.     

Dry matter intake and blood parameters of nonlactating Holstein and Jersey cows in late gestation

An experiment was conducted using 14 multiparous Holstein and 14 multiparous Jersey cows to determine if dry matter intake (DMI), specifically the decline in prepartum DMI and plasma parameters differed between breeds. Cows were blocked by expected calving date and received a dry cow total mixed ration (15% crude protein and 39% neutral detergent fiber) beginning 30 d before expected calving date. At calving, cows were switched to a lactation total mixed ration (17% crude protein and 33% neutral detergent fiber). Data were collected from d 23 prepartum to d 1 postpartum. Body weight was greater for Holsteins compared with Jerseys, but body condition score did not differ between breeds. Dry matter intake decreased for both Holsteins and Jerseys as parturition approached. The interaction of breed × day prepartum was significant for DMI with the magnitude of depression being greater for Holsteins compared with Jerseys. Plasma glucose and β-hydroxy-butyrate was similar between breeds. Plasma nonesterified fatty acids (NEFA) were similar for the two breeds up to d 5 prepartum, but greater for Holsteins compared with Jerseys thereafter. The decline in prepartum DMI was positively correlated to plasma NEFA for Holsteins, but not for Jerseys. These results indicate that breed differences exist for the decline in prepartum DMI and plasma NEFA. In addition, these data show an association between prepartum DMI depression and plasma NEFA but do not suggest a causal relationship.     

Association of dry matter intake and energy balance prepartum and postpartum with health disorders postpartum: Part II. Ketosis and clinical mastitis

The main objective of this study was to determine the association of dry matter intake as percentage of body weight (DMI%BW) and energy balance (EB) prepartum (−21 d relative to parturition) and postpartum (28 d) with ketosis (n = 189) and clinical mastitis (n = 79). For this, DMI%BW and EB were the independent variables and ketosis and clinical mastitis were the dependent variables. A secondary objective was to evaluate prepartum DMI%BW and EB as predictors of ketosis and clinical mastitis. For this, ketosis and clinical mastitis were the independent variables and DMI%BW and EB were the dependent variables. Data from 476 cows from 9 experiments were compiled. Clinical mastitis was diagnosed if milk from 1 or more quarters was abnormal in color, viscosity, or consistency, with or without accompanying heat, pain, redness, or swelling of the quarter or generalized illness, during the first 28 d postpartum. Ketosis was defined as the presence of acetoacetate in urine that resulted in any color change [5 mg/dL (trace) or higher] in the urine test strip (Ketostix, Bayer, Leverkusen, Germany). Cows that developed ketosis had lesser DMI%BW and lesser EB on d −5, −3, −2, and −1 than cows without ketosis. Each 0.1-percentage point decrease in the average DMI%BW and each 1-Mcal decrease in the average of EB in the last 3 d prepartum increased the odds of having ketosis by 8 and 5%, respectively. Cut-offs for DMI%BW and EB during the last 3 d prepartum to predict ketosis were established and were ≤1.5%/d and ≤1.1 Mcal/d, respectively. Cows that developed ketosis had lesser postpartum DMI%BW and EB and greater energy-corrected milk (ECM) than cows without ketosis. Cows that developed clinical mastitis had lesser DMI%BW but similar prepartum EB compared with cows without clinical mastitis. Each 0.1-percentage point decrease in the average DMI%BW and each 1-Mcal decrease in the average EB in the last 3 d prepartum increased the odds of having clinical mastitis by 10 and 8%, respectively. The average DMI%BW and EB during the last 3 d prepartum produced significant cut-offs to predict clinical mastitis postpartum, which were ≤1.2%/d and ≤1.0 Mcal/d, respectively. Cows that developed clinical mastitis had lesser postpartum DMI%BW from d 3 to 15 and on d 17; greater EB on d 18, from d 21 to 23, and on d 26; and lesser ECM. The main limitation in this study is that the time-order of disease relative to DMI%BW and ECM is inconsistent such that postpartum outcomes were measured before and after disease, which was diagnosed at variable intervals after calving. In summary, measures of prepartum DMI were associated with and were predictors of ketosis and clinical mastitis postpartum, although the effect sizes were small.     

Identification of biological traits associated with differences in residual energy intake among lactating Holstein cows

Residual feed intake, which is usually used to estimate individual variation of feed efficiency, requires frequent and accurate measurements of individual feed intake to be carried out. Developing a breeding scheme based on residual feed intake in dairy cows is therefore complicated, especially because feed intake is not measurable for a large population. Another solution could be to focus on biological determinants of feed efficiency, which could potentially be directly and broadband measurable on farm. Several phenotypes have been identified in literature as being associated with differences in feed efficiency. The present study therefore aims to identify which biological mechanisms are associated with residual energy intake (REI) differences among dairy cows. Several candidate phenotypes were recorded frequently and simultaneously throughout the first 238 d in milk for 60 Holstein cows fed on a constant diet based on maize silage. A multiple linear regression of the 238 d in milk average of net energy intake was fitted on the 238 d in milk averages for milk energy output, metabolic body weight, the sum over the 238 d in milk of both, body condition score loss and gain, and the residuals were defined as REI. A partial least square regression was fitted over all biological traits to explain REI variability. Linear multiple regression explained 93.6% of net energy intake phenotypic variation, with 65.5% associated with lactation requirement, 23.2% with maintenance, and 4.9% with body reserves change; the 6.4% residuals represented REI. Overall, measured biological traits contributed to 58.9% of REI phenotypic variability, which were mainly explained by activity (26.5%) and feeding behavior (21.3%). However, apparent confounding was observed between behavior, activity, digestibility, and rumen-temperature variables. Drawing a conclusion on biological traits that explain feed efficiency differences among dairy cows was not possible due to this apparent confounding between the measured variables. Further investigation is needed to validate these results and to characterize the causal relationship of feed efficiency with feeding behavior, digestibility, body reserves change, activity, and rumen temperature.     

Assessing feed efficiency in early and mid lactation and its associations with performance and health in Holstein cows

Objectives were to evaluate the associations between residual dry matter (DM) intake (RFI) and residual N intake (RNI) in early lactation, from 1 to 5 wk postpartum, and in mid lactation, from 9 to 15 wk postpartum, and assess production performance and risk of diseases in cows according to RFI in mid lactation. Data from 4 experiments including 399 Holsteins cows were used in this study. Intakes of DM and N, yields of milk components, body weight, and body condition were evaluated daily or weekly for the first 105 d postpartum. Milk yield by 305 d postpartum was also measured. Incidence of disease was evaluated for the first 90 d postpartum and survival up to 300 d postpartum. Residual DM and N intake were calculated in early and mid lactation as the observed minus the predicted values, which were based on linear models that accounted for major energy or N sinks, including daily milk energy or N output, metabolic body weight, and daily body energy or N changes, and adjusting for parity, season of calving, and treatment within experiment. Cows were ranked by RFI and RNI in mid lactation and categorized into quartiles (Q1 = smallest RFI, to Q4 = largest RFI). Increasing efficiency in mid lactation resulted in linear decreases in RFI (depicted from Q1 to Q4; ?0.93, ?0.05, ?0.04, and 0.98 kg/d), DMI (16.0, 16.9, 17.3, and 18.4 kg/d), net energy for lactation (NE_L) intake (26.8, 28.4, 29.0, and 30.8 Mcal/d), and NE_L balance (?9.0, ?8.1, ?8.2, and ?5.5 Mcal/d) during early lactation, but no differences were observed in body NE_L or N changes or yield of energy-corrected milk in the first 5 wk of lactation. Residual DM intake in mid lactation was associated with RFI (Pearson r = 0.43, and Spearman ρ = 0.32) and RNI (r = 0.44, ρ = 0.36) in early lactation, and with RNI in mid lactation (r = 0.91, ρ = 0.84). Similarly, RNI in mid lactation was associated with RNI in early lactation (r = 0.42, ρ = 0.35). During the first 15 wk postpartum, more efficient cows in mid lactation consumed 3.5 kg/d less DM (Q1 = 19.3 vs. Q4 = 22.8 kg/d) and were more N efficient (Q1 = 31.6 vs. Q4 = 25.8%), at the same time that yields of milk (Q1 = 39.0 vs. Q4 = 39.4 kg/d), energy-corrected milk (Q1 = 38.6 vs. Q4 = 39.3 kg/d), and milk components did not differ compared with the quartile of least efficient cows. Furthermore, RFI in mid lactation was not associated with 305-d milk yield, incidence of diseases in the first 90 d postpartum, or survival by 300 d postpartum. Collectively, rankings of RFI and RNI are associated and repeatable across lactation stages. The most feed-efficient cows were also more N efficient in early and mid lactation. Phenotypic selection of RFI based on measurements in mid lactation is associated with improved efficiency without affecting production or health in dairy cows.     

The effect of Lolium perenne L. ploidy and Trifolium repens L. inclusion on dry matter intake and production efficiencies of spring-calving grazing dairy cows

The objective of this study was to investigate the effect of perennial ryegrass (Lolium perenne L.; PRG) ploidy and white clover (Trifolium repens L.) inclusion on milk production, dry matter intake (DMI), and milk production efficiencies. Four separate grazing treatments were evaluated: tetraploid PRG only, diploid PRG only, tetraploid PRG with white clover, and diploid PRG with white clover. Individual DMI was estimated 8 times during the study (3 times in 2015, 2 times in 2016, and 3 times in 2017) using the n-alkane technique. Cows were, on average, 64, 110, and 189 d in milk during the DMI measurement period, corresponding to spring, summer, and autumn, respectively. Measures of milk production efficiency were total DMI/100 kg of body weight (BW), milk solids (kg of fat + protein; MSo)/100 kg of BW, solids-corrected milk/100 kg of BW, and MSo/kg of total DMI. Perennial ryegrass ploidy had no effect on DMI; however, a significant increase in DMI (+0.5 kg/cow per day) was observed from cows grazing PRG-white clover swards compared with PRG-only swards. Sward white clover content influenced DMI as there was no increase in DMI in spring (9% sward white cover content), whereas DMI was greater in summer and autumn for cows grazing PRG-white clover swards (+0.8 kg/cow per day) compared with PRG-only swards (14 and 23% sward white clover content, respectively). The greater DMI of cows grazing PRG-white clover swards led to increased milk (+1.3 kg/cow per day) and MSo (+0.10 kg/cow per day) yields. Cows grazing PRG-white clover swards were also more efficient for total DMI/100 kg of BW, solids-corrected milk/100 kg of BW, and MSo/100 kg of BW compared with cows grazing PRG-only swards due to their similar BW but higher milk and MSo yields. The results highlight the potential of PRG-white clover swards to increase DMI at grazing and to improve milk production efficiency in pasture-based systems.     

Addition of straw to the early-lactation diet: Effects on feed intake,milk yield,and subclinical ketosis in Holstein cows

This study evaluated feed intake, milk yield, and subclinical ketosis in dairy cows in early lactation fed 2 different diets postpartum. Cows are typically offered a high-energy ration immediately after calving. We compared a conventional high-energy total mixed ration (TMR) with a transition ration that contained chopped straw. We predicted that adding chopped straw would increase dry matter intake, milk production, and indicators of energy metabolism during the first 3 wk of lactation compared to cows fed a conventional high-energy TMR. We also predicted that carryover effects would be likely for at least 2 wk after treatment ended. A total of 68 mixed-age Holstein cows were enrolled in the study 3 wk before their expected calving. All cows were managed on a single high-forage diet during the dry period. At calving, cows were allocated to 1 of the 2 diets: half to the conventional high-energy TMR (CTMR; n = 34; net energy for lactation = 1.61 Mcal/kg; neutral detergent fiber = 31.7%), and the other half to a high-forage TMR containing chopped wheat straw, equivalent to 4.27% dry matter (STMR; n = 34; net energy for lactation = 1.59 Mcal/kg; neutral detergent fiber = 33.7%) for 3 wk after calving. Cows on STMR were then shifted to CTMR for the next 2 wk to study short-term residual effects on the performance of cows. Treatments were balanced for parity, body condition score, and body weight. Feed intake was measured daily from 2 wk before to 5 wk after calving using automatic feed bins. Blood was sampled twice weekly from 2 wk before to 5 wk after calving, and β-hydroxybutyrate and glucose were measured in serum samples. Subclinical ketosis was identified using a threshold of β-hydroxybutyrate ≥1.0 mmol/L in wk 1 after calving and ≥1.2 mmol/L in wk 2 to 5 after calving. Cows were milked twice daily, and weekly samples (composite samples of morning and afternoon milkings) were analyzed to determine total solids, fat, protein, lactose, and somatic cell count. Data were analyzed in 2 separate periods: the treatment phase (wk +1, +2, and +3) and the post-treatment phase (wk +4 and +5). The addition of straw to the TMR negatively affected the dry matter intake of STMR cows during wk 2 and 3 of lactation. Daily milk yield during the first 5 wk of lactation was lower in STMR cows than in CTMR cows. Concentrations of β-hydroxybutyrate were higher in CTMR cows than in STMR cows during wk 1, but this effect was reversed during wk 2 and 3 of lactation. By 21 d in milk, STMR cows had a greater risk of developing subclinical ketosis than CTMR cows. Adding chopped wheat straw to the TMR during the first 21 d after calving lowered dry matter intake and provided no metabolic or production benefits to lactating dairy cattle.