Mastitis and the shape of the lactation curve in Norwegian dairy cows

An investigation of the shape of the lactation curve and the mastitis incidence was conducted to identify whether management interventions of the lactation curve constitute a potential for reducing incidence of mastitis at herd level. Lactation curves were estimated to describe the variation of daily milk yield during the 305-d lactation period in Norwegian Red cows. Associations between mastitis incidence at herd level and lactation curve characteristics such as production level at onset of lactation, magnitude and time of peak milk yield, and increase and decrease of milk yield rates were studied. Data from 250,303 lactations occurring during 2005 and 2006 from 14,766 herds were obtained from the Norwegian Dairy Herd Recording System. Besides veterinary treatments, the records included information on monthly test-day milk yields. The shapes of the lactation curves at herd level were parameterized using a modified Wilmink model in two separate mixed model analyses. In the first analysis a subset of lactations with no records of veterinary treatments was used. Lactation curves from herds with high (>0·31 cases/305-d lactation) and low (<0·07 cases/305-d lactation) herd mastitis incidence rate were parameterized and compared for three separate strata of parity. The result showed that high herd mastitis incidence rate was associated with a low intercept (P<0·05), a steep slope before peak milk yield (P<0·01) and a rapid decline after peak milk yield (P<0·01). In the second analysis a subset of high-yielding lactations with veterinary treatments of mastitis only and lactations with no records of veterinary treatment were compared. This was done to investigate whether the findings at herd level were also reflected at cow level. These results showed that lactation curves from lactations with mastitis cases were associated with a steep slope before peak milk yield (P<0·05) in second and later parities and a rapid decline after peak milk yield (P<0·01) in all three parity groups.     

Comparative evaluation of a new lactation curve model for pasture-based Holstein-Friesian dairy cows

Fourteen lactation models were fitted to average and individual cow lactation data from pasture-based dairy systems in the Australian states of Victoria and Tasmania. The models included a new "log-quadratic" model, and a major objective was to evaluate and compare the performance of this model with the other models. Nine empirical and 5 mechanistic models were first fitted to average test-day milk yield of Holstein-Friesian dairy cows using the nonlinear procedure in SAS. Two additional semiparametric models were fitted using a linear model in ASReml. To investigate the influence of days to first test-day and the number of test-days, 5 of the best-fitting models were then fitted to individual cow lactation data. Model goodness of fit was evaluated using criteria such as the residual mean square, the distribution of residuals, the correlation between actual and predicted values, and the Wald-Wolfowitz runs test. Goodness of fit was similar in all but one of the models in terms of fitting average lactation but they differed in their ability to predict individual lactations. In particular, the widely used incomplete gamma model most displayed this failing. The new log-quadratic model was robust in fitting average and individual lactations, and was less affected by sampled data and more parsimonious in having only 3 parameters, each of which lends itself to biological interpretation.     

A reaction norm sire model to study the effect of metabolic challenge in early lactation on the functional longevity of dairy cows

Due to the discrepancy of the high energy demand for rapidly increasing milk production and limited feed intake in the transition period around parturition, dairy cows require considerable metabolic adaptations. We hypothesize that some cows are genetically less suited to cope with these metabolic needs than others, leading to adverse follow-up effects on longevity. To test this, we designed a reaction norm model in which functional lifetime was linked to the metabolic challenge in the beginning of the first lactation. As challenge variables, we used either the sum of milk yield or the accumulated fat-to-protein ratio of the first 3 test-days (<120 d in milk), pre-adjusted for herd-test-day variance. We defined a random regression sire model, in which a random slope was estimated for each sire to assess whether a bull had robust (neutral or positive slopes) or non-robust (negative slopes) daughters. We fitted the model to data of ～580,000 daughters of ～5,000 Brown Swiss bulls with suitable observations available (≥10 daughters per bull). To validate our proposed model and assess the reliability of the estimated (co)variance components, we conducted an extensive bootstrap approach. For both challenge variables, we found the sire variance for the slope of the random regression to be significantly different from zero, suggesting a genetic component for metabolic adaptability. The results of the study show that the ability to cope with metabolic stress in the transition period has a genetic component, which can be used to breed metabolically robust dairy cows.     

Influence of lactation on metabolic characteristics and embryo development in postpartum Holstein dairy cows

The aim of this study was to examine the direct effect of lactation on the ability of the reproductive tract of postpartum dairy cows to support early embryo development. Twenty-one primiparous Holstein heifers were used. Immediately after calving, half of the cows were dried off (i.e., never milked), and the other half entered the milking herd and were milked twice daily. Jugular blood samples were taken twice per week from 15 d before calving to approximately 100 d postpartum to measure nonesterified fatty acids, β-hydroxybutyrate, glucose, insulin, and insulin-like growth factor-I. At the same time, body weight and body condition score were recorded for each cow. At approximately 60 d postpartum (experiment 1), approximately 65 two- to four-cell embryos, produced by in vitro maturation and fertilization, were endoscopically transferred to the oviduct ipsilateral to the corpus luteum of all cows on d 2 of the estrous cycle. Five days later (d 7), the oviduct and uterus were flushed nonsurgically and the number of embryos developing to the blastocyst stage was recorded. At approximately 90 d postpartum (experiment 2), the estrous cycles of the same cows were resynchronized and 15 to 20 in vitro-produced blastocysts were transferred to the uterus of each recipient on d 7. All cows were slaughtered on d 14 to assess embryo survival and dimensions. Body weight and body condition score were significantly different between groups for the entire postpartum period of the study. Concentrations of nonesterified fatty acids and β-hydroxybutyrate were higher and concentrations of glucose, insulin, and insulin-like growth factor-I were lower in lactating compared with nonlactating cows. Embryo recovery rates from lactating and dry cows were similar. In experiment 1, fewer embryos developed to the blastocyst stage in the lactating cows compared with the nonlactating cows. In experiment 2, embryo survival and conceptus dimensions were not different between lactating and nonlactating cows. In conclusion, the data indicate that the reproductive tract of the lactating dairy cow is compromised in its ability to support early embryo development compared with that of matched dry cows and this may contribute to early embryo mortality observed in such animals.     

Identifying poor metabolic adaptation during early lactation in dairy cows using cluster analysis

Currently, cows with poor metabolic adaptation during early lactation, or poor metabolic adaptation syndrome (PMAS), are often identified based on detection of hyperketonemia. Unfortunately, elevated blood ketones do not manifest consistently with indications of PMAS. Expected indicators of PMAS include elevated liver enzymes and bilirubin, decreased rumen fill, reduced rumen contractions, and a decrease in milk production. Cows with PMAS typically are higher producing, older cows that are earlier in lactation and have greater body condition score at the start of lactation. It was our aim to evaluate commonly used measures of metabolic health (input variables) that were available [i.e., blood β-hydroxybutyrate acid, milk fat:protein ratio, blood nonesterified fatty acids (NEFA)] to characterize PMAS. Bavarian farms (n = 26) with robotic milking systems were enrolled for weekly visits for an average of 6.7 wk. Physical examinations of the cows (5–50 d in milk) were performed by veterinarians during each visit, and blood and milk samples were collected. Resulting data included 790 observations from 312 cows (309 Simmental, 1 Red Holstein, 2 Holstein). Principal component analysis was conducted on the 3 input variables, followed by K-means cluster analysis of the first 2 orthogonal components. The 5 resulting clusters were then ascribed to low, intermediate, or high PMAS classes based on their degree of agreement with expected PMAS indicators and characteristics in comparison with other clusters. Results revealed that PMAS classes were most significantly associated with blood NEFA levels. Next, we evaluated NEFA values that classify observations into appropriate PMAS classes in this data set, which we called separation values. Our resulting NEFA separation values [<0.39 mmol/L (95% confidence limits = 0.360–0.410) to identify low PMAS observations and ≥0.7 mmol/L (95% confidence limits = 0.650–0.775) to identify high PMAS observations] were similar to values determined for Holsteins in conventional milking settings diagnosed with hyperketonemia and clinical symptoms such as anorexia and a reduction in milk yield, as reported in the literature. Future studies evaluating additional clinical and laboratory data, breeds, and milking systems are needed to validate these finding. The aim of future studies would be to build a PMAS prediction model to alert producers of cows needing attention and help evaluate on-farm metabolic health management at the herd level.     

Characterization of metabolic changes during a protocol for inducing lactation ketosis in dairy cows

During the 5 wk immediately after parturition, five high producing cows that were overfed prepartum completed a protocol for inducement of ketosis. By 12 d postpartum, hepatic glycogen decreased by 75% and hepatic triglyceride, beta-hydroxybutyrate, and acetoacetate increased by 6, 4, and 2.5 times. The protocol, initiated at 2 wk postpartum, consisted of a 15 to 20% decrease from ad libitum feed intake plus dietary supplementation with 1,3-butanediol, a ketogenic substrate. Severity of the ketotic state increased gradually, and four cows developed clinical signs of ketosis at an average of 36 d postpartum. Glycogen was 90% depleted, and triglycerides, beta-hydroxybutyrate, and acetoacetate concentrations in liver were increased to 10, 10, and 15 times above average prepartum concentrations. In plasma, beta-hydroxybutyrate increased and glucose decreased. Plasma insulin exhibited an initial postpartal decrease (40%) but then was stable at that concentration through 36 d. After treatment for ketosis, glucose and insulin concentrations of plasma were greater than prepartal concentrations. Results indicate that a relatively simple protocol of prolonged energy deficit combined with an influx of ketone body precursors can induce experimental lactation ketosis in overfed cows. The protocol should be a valuable tool for ketosis research.     

Dietary energy source in dairy cows in early lactation: metabolites and metabolic hormones

Negative energy balance-related metabolic disorders suggest that the balance between available lipogenic and glucogenic nutrients is important. The objectives of this study were to compare the effects of a glucogenic or a lipogenic diet on liver triacylglycerides (TAG), metabolites, and metabolic hormones in dairy cows in early lactation and to relate metabolite concentrations to the determined energy retention in body mass (ER). Sixteen dairy cows were fed either a lipogenic or glucogenic diet from wk 3 prepartum to wk 9 postpartum (pp) and were housed in climate respiration chambers from wk 2 to 9 pp. Diets were isocaloric (net energy basis). Postpartum, cows fed a lipogenic diet tended to have higher nonesterified fatty acid concentration (NEFA; 0.46 ± 0.04 vs. 0.37 ± 0.04 mmol/L) and lower insulin concentration (4.0 ± 0.5 vs. 5.5 ± 0.6 μIU/mL). No difference was found in plasma glucose, β-hydroxybutyrate, insulin-like growth factor-I, and thyroid hormones. Liver TAG was equal between both diets in wk −2 and 2 pp. In wk 4 pp cows fed the glucogenic diet had numerically lower TAG levels, although there was no significant dietary effect. Negative relationships were detected between ER and milk fat and between ER and NEFA. A positive relationship was detected between ER and insulin concentration. Overall, results suggest that insulin plays a regulating role in altering energy partitioning between milk and body tissue. Feeding lactating dairy cows a glucogenic diet decreased mobilization of body fat compared with a lipogenic diet. The relative abundance of lipogenic nutrients, when feeding a more lipogenic diet, is related to more secretion of lipogenic nutrients in milk, lower plasma insulin, and higher plasma NEFA concentration.     

The effect of early-lactation feeding strategy on the lactation performance of spring-calving dairy cows

The objective of this study was to establish the influence of daily herbage allowance (DHA) and supplementation level offered to spring-calving dairy cows in early lactation on animal performance throughout lactation. Sixty-six Holstein-Friesian dairy cows were randomly assigned to a 6-treatment grazing study. The treatments comprised 3 DHA levels (13, 16, and 19 kg of DM/cow; >4 cm) and 2 concentrate supplementation levels (0 and 4 kg of DM/cow per day). Treatments were imposed from February 21 to May 8 (period 1; P1). During the subsequent 4-wk (period 2; P2), animals were offered a DHA of 20 kg of DM/cow and no concentrate. Subsequently, all animals grazed as a single herd to the end of lactation. Sward quality was homogeneous throughout lactation. A low DHA increased sward utilization (+14%) but reduced milk, solids-corrected milk, protein, and lactose yields compared with a high DHA during P1. Concentrate supplementation significantly increased milk, solids-corrected milk, fat, protein, and lactose yields during P1. The positive effect of concentrate supplementation remained throughout P2. A total concentrate input of 380 kg of DM/cow increased total lactation milk (+432 kg), solids-corrected milk (+416 kg), fat (+18 kg), protein (+15 kg), and lactose (+23 kg) yields. Greater P1 body weights were recorded when a high DHA and concentrate were offered. The P1 treatment had no effect on body condition score throughout lactation. The results indicate that offering a low DHA in early spring does not adversely affect total milk production, body weight, or body condition score, and offering concentrate results in a greater total lactation milk production performance.     

Splanchnic metabolism of dairy cows during the transition from late gestation through early lactation

Blood flow and net nutrient fluxes for portal-drained viscera (PDV) and liver (total splanchnic tissues) were measured at 19 and 9 d prepartum and at 11, 21, 33, and 83 d in milk (DIM) in 5 multiparous Holstein-Friesian cows. Cows were fed a grass silage-based gestation ration initially and a corn silage-based lactation ration peripartum and postpartum. Meals were fed at 8-h intervals and hourly (n = 8) measures of splanchnic metabolism were started before (0730 h and 0830 h) feeding at 0830 h. Dry matter intakes (DMI) at 19 and 9 d prepartum were not different. Metabolism changes measured from 19 to 9 d prepartum were lower arterial insulin and acetate, higher arterial nonesterified fatty acids and increased net liver removal of glycerol. After calving, PDV and liver blood flow and oxygen consumption more than doubled as DMI and milk yield increased, but 85 and 93% of the respective increases in PDV and liver blood flow at 83 DIM had occurred by 11 DIM. Therefore, factors additional to DMI must also contribute to increased blood flow in early lactation. Most postpartum changes in net PDV and liver metabolism could be attributed to increases in DMI and digestion or increased milk yield and tissue energy loss. Glucose release was increasingly greater than calculated requirements as DIM increased, presumably as tissue energy balance increased. Potential contributions of lactate, alanine, and glycerol to liver glucose synthesis were greatest at 11 DIM but decreased by 83 DIM. Excluding alanine, there was no evidence of an increased contribution of amino acids to liver glucose synthesis is required in early lactation. Increased net liver removal of propionate (69%), lactate (20%), alanine (8%), and glycerol (4%) can account for increased liver glucose release in transition cows from 9 d before to 11 d after calving.     

On-farm management decisions to improve beef quality of market dairy cows

A 3-phase study was conducted to assess on-farm management decisions to reduce antibiotic residue violations and improve carcass characteristics in market (cull) dairy cows. In Phase 1, questionnaires were mailed to dairy producers (n = 142) to determine current on-farm management strategies for reducing antibiotic residues in market dairy cattle. In Phase 2, Holstein market cows (n = 77) were assigned randomly to each of the 3 feeding treatments (0, 30, or 60 d). Average daily gain (ADG), body condition score (BCS), and carcass characteristics were assessed. Phase 3 determined the meat withdrawal time of Holstein cows (n = 62) administered procaine penicillin G. Eighty-six percent of dairy farms responding to the questionnaire had at least one cow condemned annually, and no producer had a designated feeding protocol for market cows prior to selling. In Phase 2, ADG was greater in cows fed for 30 d (1.4+/-0.6 kg/d) than in cows fed for 60 d (0.9+/-0.4 kg/d). Additional feeding did not influence the carcass characteristics studied with the exception of kidney, pelvic and heart fat, which was higher in cows fed for 60 d compared with those fed for 0 and 30 d. In Phase 3, 31% of cows treated with procaine penicillin G exceeded the 10-d label withdrawal recommendation by an average of 3.1+/-1.9 d. Feeding market cows may not influence carcass characteristics, but can increase ADG and may ensure that recommended meat withdrawal times for antibiotics are exceeded.     

The effect of subclinical ketosis in early lactation on reproductive performance of postpartum dairy cows

Data generated from 796 Holstein cows enrolled in a clinical trial to investigate the health effect of a monensin controlled release capsule were analyzed to investigate the association between circulating serum β-hydroxybutyrate (BHBA) concentration in the peri-parturient period and subsequent reproductive performance. Overall, accounting for both repeated measures within cow and clustering at the herd level, non-pregnant cows after first insemination tended to have increased circulating BHBA concentrations from 3 wk before calving to 9 wk after calving relative to pregnant cows. Including the interaction between the week of sample collection and pregnancy outcome, non-pregnant cows had higher circulating BHBA concentrations in the second week after calving than cows diagnosed pregnant after first artificial insemination. Within individual weeks, cows with circulating BHBA concentrations ≥1,000 μmol/L in the first week postpartum were less likely to be diagnosed pregnant after first insemination. In the second week postpartum, the cows with circulating BHBA concentrations ≥1,400 μmol/L were significantly less likely to be pregnant after first artificial insemination. A dose response relationship was found when a comparison of the probability of pregnancy after first insemination and duration of elevated circulating ketone bodies was investigated. The probability of pregnancy was reduced by 20% in cows diagnosed subclinically ketotic in either the first or second week postpartum. Nevertheless, cows above the subclinical ketosis threshold in both the first and second week postpartum were 50% less likely to be pregnant after first insemination. Similarly, the median time to pregnancy increased in cows experiencing elevated BHBA concentrations in either (124 d) or both (130 d) the first and second week postpartum relative to cows never experiencing elevated BHBA concentrations (108 d). To further investigate this, the effect of elevated circulating BHBA was permitted to vary with time. The effect decreased with time, such that the daily probability of pregnancy increased similar to nonsubclinically ketotic cows by approximately 160 d in milk. From this analysis, both the relative circulating concentration of BHBA and the duration of elevated circulating BHBA were negatively associated with the probability of pregnancy at first service.     

Forage pH effects on intake in early lactation dairy cows

In Experiment 1, 18 mature Holstein cows were used in a single reversal design with 6-wk periods from wk 5 to 16 postpartum. Cows were fed for ad libitum consumption corn silage and grain separately in a 40:60 ratio where treatments consisted of a corn silage (pH = 3.64) or corn silage partially neutralized with sodium bicarbonate prior to feeding (pH = 5.44). Neutralization of corn silage increased forage DM intake 1.0 kg/d and total DM 1.3 kg/d. Milk fat percent was increased from 3.79 to 4.15. In Experiment 2, 17 mature Holstein cows were used in an identical design except that alfalfa haylage was used as the forage. Increasing alfalfa haylage pH from 4.62 to 5.45 had no effect on intake or milk production. Literature data means and data summarized from the present experiments in multiple regression analysis indicated that intake as a percentage of body weight = .96 + .88 pH - .077 pH2 (R2 = .65, n = 49). Optimal pH for maximum intake was 5.7. Intake responses to pH above 4.5 are relatively small and explain the differences in responses seen between corn silage and alfalfa haylage in Experiments 1 and 2.     

Digestive and metabolic efficiency of energy and nitrogen during lactation and the dry period in dairy cows

The objective of this study was to characterize total-tract nutrient digestibility, energy balance, and N balance in the critical dietary and metabolic transitions of the lactation cycle. Twelve dairy cows were housed in tiestalls from 10 wk before to 16 wk after parturition. After 2 wk of adaptation to the facility and diet, digestibility of organic matter (OM), neutral detergent fiber (NDF), starch, and N were measured, and energy and N balances determined at weekly intervals by total collection of feces, urine, and milk over 48 h. Cows were individually fed ad libitum a grass silage- and corn silage-based total mixed ration during lactation and a corn silage- and barley straw-based total mixed ration during the dry period. Effects of stage of lactation were evaluated by clustering week in 5 groups: late lactation (wk ?8 to ?7), dry period (wk ?6 to ?1), and 3 early lactation periods (wk 1 to 5, wk 6 to 10, and wk 11 to 16). In lactation, apparent total-tract digestibility of OM, NDF, and starch was lowest in the first 5 wk of lactation. From wk 2 to 16 after parturition, apparent nutrient digestibility of all nutrients increased linearly, but with a negative quadratic component for dry matter, OM, and NDF, to levels comparable to those reported in last 2 wk of the previous lactation. However, differences in digestibility across lactation stage were moderate, illustrated by the difference between OM digestibility in late lactation (last 2 wk, 74.8%) and early lactation (first 5 wk, 72.5%). Cows were in negative energy balance for the first 8 wk after calving, and in negative N balance for the first 4 wk after calving. Based on energy and N balance, we predicted that 36.5 kg of body fat and 3.5 kg of body protein were gained in the last 8 wk before calving, and that 47.5 kg of body fat and 7.6 kg of body protein were mobilized in the first weeks of lactation. These predicted changes in body mass, both the gain before calving and loss after calving, were greater by 37% and 10%, respectively, than fluctuations in measured body weight (corrected for predicted gut fill and fetus weights). At wk 1 and 2 postpartum, body N loss corresponded to 25 and 29%, respectively, of total N excretion in milk, and body energy loss corresponded to 64% and 44%, respectively, of the energy exported to milk, illustrating the important contribution of N and energy from body stores to milk production in early lactation. Metabolic N efficiency, measured as total N output (milk and body) over digestible N input (from diet and body), averaged 54.4% in the last 2 wk of lactation, increased to 65.9% 2 wk after calving, and decreased linearly as lactation advanced to 61.9% by wk 16. Short (48 h) but weekly repetition of total collection of feces and urine appears to be a suitable approach to evaluate temporal changes in nutrient digestibility, energy balance, and N balance across lactation and the dry period.     

Characterization of ketolactia in dairy cows during early lactation

Fourier transform infrared spectroscopy (FTIR) allows for the determination of milk acetone (mACE) and β-hydroxybutyrate (mBHB) concentrations, providing a potential herd monitoring tool for hyperketolactia, defined as elevated milk ketone bodies. The study aim was to characterize mACE and mBHB concentration dynamics during early lactation in Polish Holstein-Friesian cows. Milk samples (n = 3,867,390) were collected within 6 to 60 days in milk (DIM) over a 4-yr period (April 1, 2013 to March 31, 2017) from approximately 21,300 dairy herds (average 38.7 cows/herd). Fixed effects of parity, DIM, and their interaction on mACE and mBHB concentrations were determined using a mixed model with a herd-year-season fixed effect and random cow effect. Published hyperketolactic mACE (≥0.15 mmol/L) and mBHB (≥0.10 mmol/L) threshold concentrations were used to classify study milk samples into ketolactia groups of normal (mACE <0.15 mmol/L and mBHB <0.10 mmol/L) and hyperketolactic (HYKL; either mACE ≥0.15 mmol/L or mBHB ≥0.10 mmol/L). Additionally, HYKL samples were categorized into subpopulations as having elevated mBHB and mACE (HYKL_ACEBHB, mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L), only elevated mBHB (HYKL_BHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), or only elevated mACE (HYKL_ACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L). Effects of parity, DIM, ketolactia group or subpopulation, and their interactions on mACE and mBHB concentrations were also determined using the mixed model that included ketolactia group or subpopulation as an independent variable. Across all data, mACE and mBHB concentrations were influenced by effects of parity, DIM, and their interaction as well as parity, DIM, ketolactia group or subpopulation, and their interactions. For all samples, mACE and mBHB concentrations decreased with increasing DIM, with mACE concentration declining more rapidly compared with mBHB. In the data set, 68% and 32% of all samples were defined as normal or HYKL, respectively. Among HYKL samples, mACE was elevated soon after calving and declined over time. In contrast, mBHB started lower after calving and increased reaching peak concentrations around 30 DIM, and then decreased. Within HYKL samples, 50.8, 41.3, and 7.9% were categorized as HYKL_ACEBHB, HYKL_BHB, and HYKL_ACE respectively. Between 6 and 21 DIM, 11.3% of HYKL were classified as HYKL_ACE. Primiparous cows had greater (14.8%) HYKL_ACE samples in this time period. In conclusion, this study has characterized mACE and mBHB concentrations during early lactation and determined effects of parity, DIM, and their interaction. Using published criteria interpreting mACE and mBHB concentrations, it was intriguing to identify a unique population of samples having elevated mACE without mBHB in early lactation, especially in primiparous cows. Further research is needed to determine if this sample population represents an unhealthy metabolic status that adversely affects cow health and performance.     

Development and evaluation of models to predict the feed intake of dairy cows in early lactation

Inaccurate prediction of dry matter intake (DMI) limits the ability of current models to anticipate the technical and economic consequences of adopting different strategies for production management on individual dairy farms. The objective of the present study was to develop an accurate, robust, and broadly applicable prediction model and to compare it with the current NRC model for dairy cows in early lactation. Among various functions, an exponential model was selected for its best fit to DMI data of dairy cows in early lactation. Daily DMI data (n = 8,547) for 3 groups of Holstein cows (at Illinois, New Hampshire, and Pennsylvania) were used in this study. Cows at Illinois and New Hampshire were fed totally mixed diets for the first 70 d of lactation. At Pennsylvania, data were for the first 63 d postpartum. Data from Illinois cows were used as the developmental dataset, and the other 2 datasets were used for model evaluation and validation. Data for BW, milk yield, and milk composition were only available for Illinois and New Hampshire cows; therefore, only these 2 datasets were used for model comparisons. The exponential model, fitted to the individual cow daily DMI data, explained an average of 74% of the total variation in daily DMI for Illinois data, 49% of the variation for New Hampshire data, 67% of the variation for Pennsylvania data, and 64% of the variation overall. Based on all model selection criteria used in this study, the exponential model for prediction of weekly DMI of individual cows was superior to the current NRC equation. The exponential model explained 85% of the variation in weekly mean DMI compared with 42% for the NRC equation. Compared with the relative prediction error of 6% for the exponential model, that associated with prediction using the NRC equation was 14%. The overall mean square prediction error value for individual cows was 5-fold higher for the NRC equation than for the exponential model (10.4 vs. 2.0 kg²/d²). The consistently accurate and robust prediction of DMI by the exponential model for all data-sets suggested that it could safely be used for predicting DMI in many circumstances.     

Comparative evaluation of alternative forages to grass silage in the diet of early lactation dairy cows

Fifty-six autumn-calving Holstein-Friesian cows, blocked on the basis of days in milk (27.6 ± 10.65 d), lactation number (3.1 ± 2.21), and preexperimental milk yield (28.4 ± 6.69 kg) were used to examine the effects of replacing 330 g/kg of dry matter (DM) of first-cut perennial ryegrass silage with either fermented whole-crop wheat (WCW), urea-treated processed WCW, or corn silage on subsequent feed intake, milk production, and efficiency of nitrogen utilization. The DM (g/kg), crude protein (CP, g/kg of DM) and in vitro DM digestibility (g/kg) of the forages were 204, 179, and 762 for grass silage; 389, 90, and 711 for fermented WCW; 795, 141, and 768 for urea-treated processed WCW; and 346, 93, and 783 for corn silage, respectively. Four forage treatments were evaluated as follows: 1) grass silage as the sole forage (GS); 2) a mixture of grass silage and fermented WCW silage, (F-WCW); 3) a mixture of grass silage and urea-treated processed WCW, (UP-WCW); and 4) a mixture of grass silage and corn silage (CS). In all cases, the alternative forages comprised 67% of the forage mix on a DM basis. Isonitrogenous diets were formulated by offering all cows 8 kg of concentrate as fed, formulated to different CP concentrations. Cows were offered these diets from 28 to 104 d in milk. Total DM intake and milk yield were greater on UP-WCW (20.0 and 30.2 kg/d) and CS (18.3 and 33.2 kg/d) than on GS (13.5 and 26.5 kg/d). Although DM intake was greater on F-WCW (17.1 kg/d) than on GS, milk yield was not significantly greater (+2.7 kg/d). Milk protein concentration was greater on F-WCW (30.5 g/kg), UP-WCW (31.3 g/kg), and CS (30.7 g/kg) than on GS (28.5 g/kg). However, there was no difference between treatments in milk fat or lactose concentrations. Body weight change was greater for cows offered GS (−0.27 kg/d) than for those offered UP-WCW (−0.01 kg/d) and CS (+0.05 kg/d) but not compared with those offered F-WCW (−0.06 kg/d). There was no effect of treatment on plasma glucose, nonesterified fatty acids, β-hydroxybutyrate, urea, or total protein at d 64 ± 17.4 and d 92 ± 17.4 postpartum. Efficiency of N utilization was greatest for CS with 0.36 of N intake being recovered in milk compared with 0.28, 0.32, and 0.26 for GS, F-WCW, and UP-WCW, respectively. There was no effect of treatment on milk urea N concentration or the urinary allantoin N to creatinine N ratio. The results of this experiment indicate that corn silage is a more suitable supplementary forage to grass silage than fermented or urea-treated processed WCW, with advantages realized in milk production and more efficient N utilization.     

On-farm detection of claw lesions in dairy cows based on acoustic analyses and machine learning

Claw lesions are a serious problem on dairy farms, affecting both the health and welfare of the cow. Automated detection of lameness with a practical, on-farm application would support the early detection and treatment of lame cows, potentially reducing the number and severity of claw lesions. Therefore, in this study, a method was proposed for the detection of claw lesions based on the acoustic analysis of a cow's gait. A panel was constructed to measure the impact sound of animals walking over it. The recorded impact sound was edited, and 640 sound files from 64 cows were analyzed. The classification of animal-lameness status was performed using a machine-learning process with a random forest algorithm. The gold standard was a 2-point scale of hoof-trimming results (healthy vs. affected), and 38 properties of the recorded sound files were used as influencing factors. A prediction model for classifying the cow lameness was built using a random forest algorithm. This was validated by comparing the reference output from hoof-trimming with the model output concerning the impact sound. Altering the likelihood settings and changing the cutoff value to predict lame animals improved the prediction model. At a cutoff at 0.4, a decreased false-negative rate was generated, and the false-positive rate only increased slightly. This model obtained a sensitivity of 0.81 and a specificity of 0.97. With this procedure, Cohen's Kappa value of 0.80 showed good agreement between model classification and diagnoses from hoof-trimming. In summary, the prediction model enabled the detection of cows with claw lesions. This study shows that lameness can be detected by machine learning from the impact sound of hoofs in dairy cows.     

Study of the lactation curve in dairy cattle on farms in central Mexico

Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines (exponential decay), Wood (gamma equation), Rook (Michaelis-Menten ×exponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.     

Prediction of metabolic status of dairy cows in early lactation using milk fatty acids and test-day variables

Early lactation metabolic imbalance is an important physiological change affecting the health, production, and reproduction of dairy cows. The aims of this study were (1) to evaluate the potential of test-day (TD) variables with or without milk fatty acids (FA) content to classify metabolically imbalanced cows and (2) to evaluate the robustness of the metabolic classification with external data. A data set was compiled from 3 experiments containing plasma β-hydroxybutyrate, nonesterified FA, glucose, insulin-like growth factor-I, FA proportions in milk fat, and TD variables collected from 244 lactations in wk 2 after calving. Based on the plasma metabolites, 3 metabolic clusters were identified using fuzzy c-means clustering and the probabilistic membership value of each cow to the 3 clusters was determined. Comparing the mean concentration of the plasma metabolites, the clusters were differentiated into metabolically imbalanced, moderately impacted, and balanced. Following this, the 2 metabolic status groups identified were imbalanced cows (n = 42), which were separated from what we refer to as “others” (n = 202) based on the membership value of each cow for the imbalanced cluster using a threshold of 0.5. The following 2 FA data sets were composed: (1) FA (groups) having high prediction accuracy by Fourier-transform infrared spectroscopy and, thus, have practical significance, and (2) FA (groups) formerly identified as associated with metabolic changes in early lactation. Metabolic status prediction models were built using FA alone or combined with TD variables as predictors of metabolic groups. Comparison was made among models and external evaluations were performed using an independent data set of 115 lactations. The area under the receiver operating characteristics curve of the models was between 75 and 91%, indicating their moderate to high accuracy as a diagnostic test for metabolic imbalance. The addition of FA groups to the TD models enhanced the accuracy of the models. Models with FA and TD variables showed high sensitivities (80–88%). Specificities of these models (73–79%) were also moderate and acceptable. The accuracy of the FA models on the external data set was high (area under the receiver operating characteristics curve between 76 and 84). The persistently good performance of models with Fourier-transform infrared spectroscopy-quantifiable FA on the external data set showed their robustness and potential for routine screening of metabolically imbalanced cows in early lactation.