Estimation of genetic parameters for feed efficiency traits using random regression models in dairy cattle

Feed efficiency has become an increasingly important research topic in recent years. As feed costs rise and the environmental impacts of agriculture become more apparent, improving the efficiency with which dairy cows convert feed to milk is increasingly important. However, feed intake is expensive to measure accurately on large populations, making the inclusion of this trait in breeding programs difficult. Understanding how the genetic parameters of feed efficiency and traits related to feed efficiency vary throughout the lactation period is valuable to gain understanding into the genetic nature of feed efficiency. This study used 121,226 dry matter intake (DMI) records, 120,500 energy-corrected milk (ECM) records, and 98,975 metabolic body weight (MBW) records, collected on 7,440 first-lactation Holstein cows from 6 countries (Canada, Denmark, Germany, Spain, Switzerland, and the United States), from January 2003 to February 2022. Genetic parameters were estimated using a multiple-trait random regression model with a fourth-order Legendre polynomial for all traits. Weekly phenotypes for DMI were re-parameterized using linear regressions of DMI on ECM and MBW, creating a measure of feed efficiency that was genetically corrected for ECM and MBW, referred to as genomic residual feed intake (gRFI). Heritability (SE) estimates varied from 0.15 (0.03) to 0.29 (0.02) for DMI, 0.24 (0.01) to 0.29 (0.03) for ECM, 0.55 (0.03) to 0.83 (0.05) for MBW, and 0.12 (0.03) to 0.22 (0.06) for gRFI. In general, heritability estimates were lower in the first stage of lactation compared with the later stages of lactation. Additive genetic correlations between weeks of lactation varied, with stronger correlations between weeks of lactation that were close together. The results of this study contribute to a better understanding of the change in genetic parameters across the first lactation, providing insight into potential selection strategies to include feed efficiency in breeding programs.

Energy balance of dairy cows predicted by mid-infrared spectra data of milk using Bayesian approaches

Information on dry matter intake (DMI) and energy balance (EB) at the animal and herd level is important for management and breeding decisions. However, routine recording of these traits at commercial farms can be challenging and costly. Fourier-transform mid-infrared (FT-MIR) spectroscopy is a noninvasive technique applicable to a large cohort of animals that is routinely used to analyze milk components and is convenient for predicting complex phenotypes that are typically difficult and expensive to obtain on a large scale. We aimed to develop prediction models for EB and use the predicted phenotypes for genetic analysis. First, we assessed prediction equations using 4,485 phenotypic records from 167 Holstein cows from an experimental station. The phenotypes available were body weight (BW), milk yield (MY) and milk components, weekly-averaged DMI, and FT-MIR data from all milk samples available. We implemented mixed models with Bayesian approaches and assessed them through 50 randomized replicates of a 5-fold cross-validation. Second, we used the best prediction models to obtain predicted phenotypes of EB (EBp) and DMI (DMIp) on 5 commercial farms with 2,365 phenotypic records of MY, milk components and FT-MIR data, and BW from 1,441 Holstein cows. Third, we performed a GWAS and estimated heritability and genetic correlations for energy content in milk (EnM), BW, DMIp, and EBp using the genomic information available on the cows from commercial farms. The highest correlation between the predicted and observed phenotype (ry,y^) was obtained with DMI (0.88) and EB (0.86), while predicting BW was, as anticipated, more challenging (0.69). In our study, models that included FT-MIR information performed better than models without spectra information in the 3 traits analyzed, with increments in prediction correlation ranging from 5% to 10%. For the predicted phenotypes calculated by the prediction equations and data from the commercial farms the heritability ranged between 0.11 and 0.16 for EnM, DMIp and EBp, and 0.42 for BW. The genetic correlation between EnM and BW was -0.17, with DMIp was 0.40 and with EBp was -0.39. From the GWAS, we detected one significant QTL region for EnM, and 3 for BW, but none for DMIp and EBp. The results obtained in our study support previous evidence that FT-MIR information from milk samples contribute to improve the prediction equations for DMI, BW, and EB, and these predicted phenotypes may be used for herd management and contribute to the breeding strategy for improving cow performance.

The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

Consistency of dry matter intake in Holstein cows: Heritability estimates and associations with feed efficiency

Resilience can be defined as the capacity to maintain performance or bounce back to normal functioning after a perturbation, and studying fluctuations in daily feed intake may be an effective way to identify resilient dairy cows. Our goal was to develop new phenotypes based on daily dry matter intake (DMI) consistency in Holstein cows, estimate genetic parameters and genetic correlations with feed efficiency and milk yield consistency, and evaluate their relationships with production, longevity, health, and reproduction traits. Data consisted of 397,334 daily DMI records of 6,238 lactating Holstein cows collected from 2007 to 2022 at 6 research stations across the United States. Consistency phenotypes were calculated based on the deviations from expected daily DMI for individual cows during their respective feeding trials, which ranged from 27 to 151 d in duration. Expected values were derived from different models, including simple average, quadratic and cubic quantile regression with a 0.5 quantile, and locally estimated scatterplot smoothing (LOESS) regression with span parameters 0.5 and 0.7. We then calculated the log of variance (log-Var-DMI) of daily deviations for each model as the consistency phenotype. Consistency of milk yield was also calculated, as a reference, using the same methods (log-Var-Milk). Genetic parameters were estimated using an animal model, including lactation, days in milk and cohort as fixed effects, and animal as random effect. Relationships between log-Var-DMI and traits currently considered in the US national genetic evaluation were evaluated using Spearman's rank correlations between sires' breeding values. Heritability estimates for log-Var-DMI ranged from 0.11 ± 0.02 to 0.14 ± 0.02 across models. Different methods (simple average, quantile regressions, and LOESS regressions) used to calculate log-Var-DMI yielded very similar results, with genetic correlations ranging from 0.94 to 0.99. Estimated genetic correlations between log-Var-DMI and log-Var-Milk ranged from 0.51 to 0.62. Estimated genetic correlations between log-Var-DMI and feed efficiency ranged from 0.55 to 0.60 with secreted milk energy, from 0.59 to 0.63 with metabolic body weight, and from 0.26 to 0.31 with residual feed intake (RFI). Relationships between log-Var-DMI and the traits in the national genetic evaluation were moderate and positive correlations with milk yield (0.20 to 0.21), moderate and negative correlations with female fertility (-0.07 to -0.20), no significant correlations with health and longevity, and favorable correlations with feed efficiency (-0.23 to -0.25 with feed saved and 0.21 to 0.26 with RFI). We concluded that DMI consistency is heritable and may be an indicator of resilience. Cows with lower variation in the difference between actual and expected daily DMI (more consistency) may be more effective in maintaining performance in the face of challenges or perturbations, whereas cows with greater variation in observed versus expected daily DMI (less consistency) are less feed efficient and may be less resilient.

Predicting feed intake in confined beef cows

Six existing equations (three for nonlactating and three for lactating; NRC, 1987, Predicting feed intake of food-producing animals. Washington, DC: The National Academies Press, National Academy of Science; doi: 10.17226/950; NRC, 1996, Nutrient requirements of beef cattle, 7th Revised Edition: Update 1996. Washington, DC: The National Academies Press; doi: 10.17226/9791; Hibberd and Thrift, 1992. Supplementation of forage-based diets. J. Anim. Sci. 70:181. [Abstr]) were evaluated for predicting feed intake in beef cows. Each of the previously published equations are sensitive to cow-shrunk BW and feed energy concentration. Adjustments in feed intake prediction are provided for level of milk yield in NRC (1987. Predicting feed intake of food-producing animals. Washington, DC: The National Academies Press, National Academy of Science; doi: 10.17226/950) and NRC (1996 Nutrient requirements of beef cattle, 7th Revised Edition: Update 1996. Washington, DC: The National Academies Press; doi: 10.17226/9791) equations. The equation published in 1996 used data generated between 1979 and 1993. Our objectives were to validate the accuracy of the published equations using more recent data and to propose alternative prediction models. Criteria for inclusion in the evaluation dataset included projects conducted or published since 2002, direct measurement of feed intake, adequate protein supply, and pen feeding (no metabolism crate data). After removing outliers, the dataset included 53 treatment means for nonlactating cows and 32 treatment means for lactating cows. Means for the nonlactating dataset were dry matter intake (DMI) = 13.2 ± 2.9 kg/d, shrunk body weight (SBW) = 578 ± 83.9 kg, body condition score = 5.7 ± 0.73, and Mcal net energy for maintenance (NEm)/kg of feed = 1.27 ± 0.15 Mcal/kg. Means for the lactating dataset were DMI = 14.6 ± 2.24 kg/d, SBW = 503 ± 73.4 kg, body condition score = 4.7 ± 0.58, and Mcal NEm/kg feed = 1.22 ± 0.16. Simple linear regression was used to determine slope, intercept, and bias when observed DMI (y) was regressed against predicted DMI (x). The NRC (1996. Nutrient requirements of beef cattle, 7th Revised Edition: Update 1996. Washington, DC: The National Academies Press; doi: 10.17226/9791) nonlactating equation underestimated feed intake in diets moderate to high in energy density with intercept differing from 0 and slope differing from one (P ≤ 0.01). Average deviation from observed values was 2.4 kg/d. Similarly, when the NRC (1996. Nutrient requirements of beef cattle, 7th Revised Edition: Update 1996. Washington, DC: The National Academies Press; doi: 10.17226/9791) equation was used to predict DMI in lactating cows, the slope differed from one (P < 0.01) with average deviation from observed values of 3.0 kg/d. New models were developed by pooling the two datasets and including a categorical variable for stage of production (0 = nonlactating and 1 = lactating). Continuous variables included study-average SBW0.75 and diet NEm, Mcal/kg. The best-fit empirical model accounted for 68% of the variation in daily feed intake with standard error of the estimate Sy root mean squared error = 1.31. The proposed equation needs to be validated with independent data.

Dose response to postruminal urea in lactating dairy cattle

Inclusion of urea in dairy cattle diets is often limited by negative effects of high levels of feed urea on dry matter intake (DMI) and efficiency of rumen N utilization. We hypothesized that supplying urea postruminally would mitigate these limitations and allow greater inclusion of urea in dairy cattle diets. Four rumen-fistulated Holstein-Friesian dairy cows (7 ± 2.1 lactations, 110 ± 30.8 d in milk; mean ± standard deviation) were randomly assigned to a 4 × 4 Latin square design to examine DMI, milk production and composition, digestibility, rumen fermentation, N balance, and plasma constituents in response to 4 levels of urea continuously infused into the abomasum (0, 163, 325, and 488 g/d). Urea doses were targeted to linearly increase the crude protein (CP) content of total DMI (diet plus infusion) by 0%, 2%, 4%, and 6% and equated to 0%, 0.7%, 1.4%, and 2.1% of expected DMI, respectively. Each 28-d infusion period consisted of a 7-d dose step-up period, 14 d of adaptation, and a 7-d measurement period. The diet was fed ad libitum as a total mixed ration [10.9% CP, 42.5% corn silage, 3.5% grass hay, 3.5% wheat straw, and 50.5% concentrate (dry matter basis)] and was formulated to meet 100%, 82%, and 53% of net energy, metabolizable protein, and rumen-degradable protein requirements, respectively. Linear, quadratic, and cubic effects of urea dose were assessed using polynomial regression assuming the fixed effect of treatment and random effects of period and cow. Dry matter intake and energy-corrected milk yield responded quadratically to urea dose, and milk urea content increased linearly with increasing urea dose. Apparent total-tract digestibility of CP increased linearly with increasing urea dose and ruminal NH3-N concentration responded quadratically to urea dose. Mean total VFA concentration was not affected by urea dose. The proportion of N intake excreted in feces decreased linearly and that excreted in urine increased linearly in response to increasing urea dose. The proportion of N intake excreted in milk increased linearly with increasing urea dose. Urinary urea excretion increased linearly with increasing urea dose. Microbial N flow responded cubically to urea dose, but the efficiency of microbial protein synthesis was not affected. Plasma urea concentration increased linearly with increasing urea dose. Regression analysis estimated that when supplemented on top of a low-CP diet, 179 g/d of postruminal urea would maximize DMI at 23.4 kg/d, corresponding to a dietary urea inclusion level of 0.8% of DMI, which is in line with the current recommendations for urea inclusion in dairy cattle diets. Overall, these results indicate that postruminal delivery of urea does not mitigate DMI depression as urea dose increases.

Genetic parameters for feed intake and body weight in dairy cattle using high-throughput 3-dimensional cameras in Danish commercial farms

Recording complex phenotypes on a large scale is becoming possible with the incorporation of recently developed new technologies. One of these new technologies is the use of 3-dimensional (3D) cameras on commercial farms to measure feed intake and body weight (BW) daily. Residual feed intake (RFI) has been proposed as a proxy for feed efficiency in several species, including cattle, pigs, and poultry. Dry matter intake (DMI) and BW records are required to calculate RFI, and the use of this new technology will help increase the number of individual records more efficiently. The aim of this study was to estimate genetic parameters (including genetic correlations) for DMI and BW obtained by 3D cameras from 6,000 cows in commercial farms from the breeds Danish Holstein, Jersey, and Nordic Red. Additionally, heritabilities per parity and genetic correlations among parities were estimated for DMI and BW in the 3 breeds. Data included 158,000 weekly records of DMI and BW obtained between 2019 and 2022 on 17 commercial farms. Estimated heritability for DMI ranged from 0.17 to 0.25, whereas for BW they ranged from 0.44 to 0.58. The genetic correlations between DMI and BW were moderately positive (0.58-0.65). Genetic correlations among parities in both traits were highly correlated in the 3 breeds, except for DMI between first parity and late parities in Holstein where they were down to 0.62. Based on these results, we conclude that DMI and BW phenotypes measured by 3D cameras are heritable for the 3 dairy breeds and their heritabilities are comparable to those obtained by traditional methods (scales and feed bins). The high heritabilities and correlations of 3D measurements with the true trait in previous studies demonstrate the potential of this new technology for measuring feed intake and BW in real time. In conclusion, 3D camera technology has the potential to become a valuable tool for automatic and continuous recording of feed intake and BW on commercial farms.

A three-year comparison of once-a-day and twice-a-day milking in seasonal-calving pasture-based systems

Globally, the majority of dairy cows are milked twice a day (TAD); however, in pasture-based production systems, such as in Ireland, the idea of milking once a day (OAD) is being considered for reasons such as improved work-life balance. The immediate effects within a lactation, as well as the multilactation consequences of OAD, compared with TAD milking, require understanding. The objective of this randomized experiment was to compare OAD and TAD milking, over a 3-yr period, by examining the differences in milk production and composition, body weight (BW), body condition score (BCS), dry matter intake (DMI), udder characteristics, locomotion score, and milking time. Over the 3-yr period, 83 cows were enrolled in the experiment; 32, 44, and 48 cows in yr 1, 2, and 3 of the experiment, respectively. Each year, 23% of the herds were primiparous animals, while the remainder were second lactation or greater in parity. All cows were milked in the morning at 0700 h; only cows milked TAD were milked a second time each day at 1600 h. Cows rotationally grazed pastures for the duration of the lactating period and were housed during the nonlactating period. Milking cows OAD reduced cumulative milk yield by 26%, and milk solids yield (kg of fat + kg of protein) by 21%, across the 3 yr of the experiment when compared with cows milked TAD which produced 4,126 and 365 kg/cow, respectively. A contributory factor to the reduced production was a shorter lactation length (9.7 d) of the cows milked OAD compared with TAD (294 d). Milk fat percent of cows milked TAD was similar for all 3 yr of the study (5.05%), whereas milk fat percent of the cows milked OAD increased year on year, with each year being greater than the previous year (5.02%, 5.32%, and 5.70% for yr 1, 2, and 3; respectively). Milk protein percent was greater (+0.19%) for cows milked OAD compared with TAD which was 3.78%. Compared with cows milked TAD, total DMI for cows milked OAD was 22% less at the start of lactation (<167 d), but as the lactation progressed (>167 d) we observed no difference in DMI between treatments. Similar to the literature, milking cows OAD significantly increased average somatic cell score, both during (+16%) and at the end of lactation (+19%), compared with milking cows TAD which were 4.69 and 4.79, respectively. We detected positive aspects associated with OAD milking such as greater BW, BCS, and fertility performance. Milking OAD reduced both milking time per cow per day (reductions ranged from 34% in the first 4 mo of lactation to 43% during mo 5-9 of lactation) and milking time per liter of milk (-3.5 s/L) throughout lactation, leading to less labor inputs on-farm which can have positive implications for farmer work-life balance. The significant time saving and potential savings in costs (e.g., electricity) need to be considered in conjunction with the milk production reduction when considering OAD milking for the entire lactation.

Effect of forage type on swallowed bolus mass and a method for counting swallows in dairy cattle

Dry matter intake (DMI) is a primary determinant of milk production in grazing dairy cows and an ability to measure the DMI of individual cows would allow herd managers to formulate supplementary rations that consider the amount of nutrients ingested from grass. The 2 related aims of this experiment were to define the mean number of swallowed boli and mass of the swallowed boli in Holstein-Friesian dairy cattle offered a variety of forages commonly fed in the dairy industry of southeastern Australia, and to evaluate 2 indirect methods for counting the number of swallows. Twelve ruminally-fistulated, lactating Holstein-Friesian cows were randomly assigned to 3 replicated 4 × 4 Latin square designs and offered 4 forages: fresh chicory (FC), fresh perennial ryegrass (RP), alfalfa hay (AH), and perennial ryegrass silage (RS). The experiment was conducted over 28 d with each of 4 periods consisting of 7 d with 3 d of measurement. Forage diets were offered to individual cows following the partial evacuation of the rumen. The first 20 min after forage was offered constituted the measurement period, during which all swallowed boli were manually captured by samplers who placed their hand through the ruminal fistula and over the cardia entrance of the rumen of each cow. Concurrently, microphones and video cameras were used for the indirect measurement of swallows. The average swallowed bolus mass overall was 17.4 g dry matter (DM) per bolus with the lowest mass observed in cows offered FC (8.9 g DM/bolus), followed by RP (14.9 g DM/bolus), compared with cows offered AH (23.6 g DM/bolus) and RS (22.3 g DM/bolus). The swallowing rate was greater in cows offered FC (78 swallows/20 min) than in cows offered RP, AH, and RS (62.3 swallows/20 min). The audio recording method showed greater concordance (Lin's concordance correlation coefficient = 0.90) with the physical capturing of the boli through the rumen, than the video recording method did (Lin's concordance correlation coefficient = 0.54). It is concluded that the mass of the swallowed boli is related to forage type and that using a microphone attached to the cow's forehead can provide an accurate measure of the number of swallows when verified against the actual number of swallows counted by manual interception of the boli at the rumen cardia.

Association of dry matter intake, milk yield, and days to first ovulation with cytological endometritis in Holstein cows

Dry matter intake (DMI, kg/d) is closely related to the magnitude of negative energy and protein balance during the transition period, and the metabolic adaptations to support lactation in dairy cows. Thus, DMI might affect the development of cytological endometritis in the early postpartum period. Difficulty to adapt to these metabolic changes is related to impaired immune function and increased occurrence of reproductive disorders. We aimed to examine the association of pre- and postpartum DMI, body weight (BW), body condition score, milk yield and milk composition, and days to first ovulation with cytological endometritis at 15 (CYT15) and 30 DIM (CYT30). A second objective was to understand the association of vaginal discharge with CYT15 and CYT30 and performance. We conducted a pooled statistical analysis of 5 studies, including data from 280 multiparous Holstein cows. Based on the cutoffs for the percentage of uterine polymorphonuclear cells (PMN), determined by taking the median value of the data set for 15 and 30 DIM, cows were categorized as follows: LOW15 (PMN % at 15 DIM ≤24%; n = 125), HIGH15 (PMN % at 15 DIM >24%; n = 125), LOW30 (PMN % at 30DIM ≤7%; n = 141); and HIGH30 (PMN % at 30DIM >7%; n = 139). Cows in HIGH15 consumed an average of 1.97 ± 0.5 kg/d less DM than cows in LOW15 during prepartum, and 3.01 ± 0.5 kg/d less DM during postpartum. Dry matter intake (as a percentage of BW) was higher for cows in LOW15 during pre- and postpartum than for cows in HIGH15. Moreover, cows in HIGH15 tended to have lower milk yield than cows in LOW15 from the third until the fifth week postpartum. Although DMI was not associated with CYT30, DMI (as a percentage of BW) was lower for cows in LOW30 pre- and postpartum than for cows in HIGH30. There was no association between CYT30 and milk yield. Cows in LOW15 had greater days to first ovulation than cows in HIGH15, while cows in LOW30 also had greater days to first ovulation than cows in HIGH30. Simple regression analyses demonstrated linear associations of increased DMI, particularly postpartum, with decreased uterine PMN percentage and lower vaginal discharge score. Additionally, increased units of vaginal discharge score and increased percentage units of uterine PMN were linearly associated with decreased milk yield. Corroborating with the notion of the ovarian function being associated with uterine inflammatory status, cows in HIGH15 and HIGH30 ovulated on average 3 d before than cows in LOW15 and LOW30, respectively. Cytological endometritis at 15 DIM was associated with lower DMI from 4 wk before calving until 4 wk postpartum and was associated with lower milk yield. The association of vaginal discharge with cytological endometritis was variable and dependent on the day of evaluation.

Effect of diets enriched in n-6 or n-3 fatty acid on dry matter intake, energy balance, oxidative stress, and milk fat profile of transition cows

The objective of this study was to determine the effect of dietary supplementation of n-3 polyunsaturated fatty acids (PUFA) and n-6 PUFA on dry matter intake (DMI), energy balance, oxidative stress, and performance of transition cows. Forty-five multiparous Holstein dairy cows with similar parity, body weight (BW), body condition score (BCS), and milk yield were used in a completely randomized design during a 56-d experimental period including 28 d prepartum and 28 d postpartum. At 240 d of pregnancy, cows were randomly assigned to one of the 3 isoenergetic and isoprotein dietary treatments, including a control ration containing 1% hydrogenated fatty acid (CON), a ration with 8% extruded soybean (HN6, high n-6 PUFA source), and a ration with 3.5% extruded flaxseed (HN3; high n-3 PUFA source). The HN6 and HN3 diets had an n-6/n-3 ratio of 3.05:1 and 0.64:1 in prepartum cows and 8.16:1 and 1.59:1 in postpartum cows, respectively. During the prepartum period (3, 2, and 1 wk before calving), DMI, DMI per unit of BW, total net energy intake, and net energy balance were higher in the HN3 than in the CON and NH6 groups. During the postpartum period (2, 3, and 4 wk after calving), cows fed HN3 and HN6 diets both showed increasing DMI, DMI as a percentage of BW, and total net energy intake compared with those fed the CON diet. The BW of calves in the HN3 group was 12.91% higher than those in the CON group. Yield and nutrient composition of colostrum (first milking after calving) were not affected by HN6 or HN3 but milk yield from 1 to 4 wk of milking was significantly improved compared with CON. During the transition period, BW, BCS, and BCS changes were not affected. Cows fed the HN6 diet had a higher plasma NEFA concentration compared with the CON cows during the prepartum period. Feeding HN3 reduced the proportion of de novo fatty acids and increased the proportion of preformed long-chain fatty acids in regular milk. In addition, the n-3 PUFA-enriched diet reduced the n-6/n-3 PUFA ratio in milk. In conclusion, increasing the n-3 fatty acids concentration in the diet increased both DMI during the transition period and milk production after calving, and supplementing n-3 fatty acids was more effective in mitigating the net energy balance after calving.

Feed Efficiency and Physiological Parameters of Holstein and Crossbred Holstein × Simmental Cows

This study aimed to compare the feed efficiency (FE) and physiological parameters of Holstein and crossbred Holstein × Simmental cows in a confinement system during winter and summer. The study was conducted in a dairy farm in southern Brazil by including a total of 48 multiparous cows. The cows were studied for 21 days in two periods, summer and winter, and their daily dry matter intake (DMI), milk yield (MY), rectal temperature (RT), respiratory rate (RR), body weight, and body condition score were recorded. An analysis of variance was conducted using the SAS statistical package. The results showed that crossbred Holstein × Simmental cows have a similar FE as Holstein cows in a high-production system (1.83 × 1.81 kg DMI/kg MY, respectively), and they can achieve the same production levels as purebred Holstein cows (43.8 vs. 44.5 milk/cow/day). Our findings indicated a difference for the period as both genetic groups achieved higher FE in winter than in summer (1.98 vs. 1.67 DMI/kg MY, respectively). In addition, we found evidence that crossbred cows are better at dissipating body heat during heat-stress situations, as they have higher RR in summer compared to purebred cows, while Holstein cows have higher RT in summer afternoons than crossbred cows. Therefore, using crossbred Holstein × Simmental cows is an alternative for high-production systems.

Enteric Methane Emissions Prediction in Dairy Cattle and Effects of Monensin on Methane Emissions: A Meta-Analysis

Greenhouse gas emissions, such as enteric methane (CH₄) from ruminant livestock, have been linked to global warming. Thus, easily applicable CH₄ management strategies, including the inclusion of dietary additives, should be in place. The objectives of the current study were to: (i) compile a database of animal records that supplemented monensin and investigate the effect of monensin on CH₄ emissions; (ii) identify the principal dietary, animal, and lactation performance input variables that predict enteric CH₄ production (g/d) and yield (g/kg of dry matter intake DMI); (iii) develop empirical models that predict CH₄ production and yield in dairy cattle; and (iv) evaluate the newly developed models and published models in the literature. A significant reduction in CH₄ production and yield of 5.4% and 4.0%, respectively, was found with a monensin supplementation of ≤24 mg/kg DM. However, no robust models were developed from the monensin database because of inadequate observations under the current paper's inclusion/exclusion criteria. Thus, further long-term in vivo studies of monensin supplementation at ≤24 mg/kg DMI in dairy cattle on CH₄ emissions specifically beyond 21 days of feeding are reported to ensure the monensin effects on the enteric CH₄ are needed. In order to explore CH₄ predictions independent of monensin, additional studies were added to the database. Subsequently, dairy cattle CH₄ production prediction models were developed using a database generated from 18 in vivo studies, which included 61 treatment means from the combined data of lactating and non-lactating cows (COM) with a subset of 48 treatment means for lactating cows (LAC database). A leave-one-out cross-validation of the derived models showed that a DMI-only predictor model had a similar root mean square prediction error as a percentage of the mean observed value (RMSPE, %) on the COM and LAC database of 14.7 and 14.1%, respectively, and it was the key predictor of CH₄ production. All databases observed an improvement in prediction abilities in CH₄ production with DMI in the models along with dietary forage proportion inclusion and the quadratic term of dietary forage proportion. For the COM database, the CH₄ yield was best predicted by the dietary forage proportion only, while the LAC database was for dietary forage proportion, milk fat, and protein yields. The best newly developed models showed improved predictions of CH₄ emission compared to other published equations. Our results indicate that the inclusion of dietary composition along with DMI can provide an improved CH₄ production prediction in dairy cattle.

Effects of dietary chromium supplementation on dry matter intake and milk production and composition in lactating dairy cows: A meta-analysis

Introduction

Chromium (Cr) is an essential mineral that has been demonstrated to enhance milk production in dairy cows. This study aims to evaluate the effects of dietary Cr supplementation on dry matter intake (DMI), milk production and composition using a meta-analysis based on existing literature.

Methods

A random effects meta-analysis was performed to investigate the effects of dietary Cr supplementation on DMI, milk production and composition. The heterogeneity was assessed using the I 2 statistic and Q test, while Egger's test was used to evaluate publication bias.

Results

The meta-analysis discovered that Cr-supplemented cows had a significantly higher DMI compared to those not supplemented, with an increase of 0.72 kg/day [95% confidence interval (CI), 0.46-0.97]. The regression model indicated that DMI significantly increased by 0.9 g/kg of body weight (BW) and by 80.5 g for an increase of 1 mg of Cr supplement. The supplementation phase was associated with an increase in DMI, with an increase of 0.4582 kg/day for BFP (before parturition) and 0.853 kg/day for AFP (after parturition). The methionine and yeast forms of Cr increased DMI by 0.714 and 1.137 kg/day, respectively. The DMI was increased by 2.137 and 0.620 kg/day for multiparous (MP)+ primiparous (PP) cows and MP cows, respectively. Milk production was also increased by Cr supplementation, with an increase of 1.20 kg/day (95% CI, 0.65-1.76). The regression model indicated that milk production increased by 2.3 g/day for an increase of 1 kg of BW and by 122.4 g/day for an increase of 1 mg of Cr supplement. Milk production also increased with the duration of the experiment and days in milk. The amino acid and methionine forms of Cr complexes increased milk production by 1.645 and 1.448 kg/day, respectively. Milk production increased by 1.087 and 1.920 kg/day for MP and PP cows, respectively. Milk composition was not significantly affected by Cr supplementation. Egger's test for publication biases was not significant for all responses of interest.

Discussion

The meta-analysis showed that Cr supplementation improves DMI and milk production in dairy cows. The results suggest that the supplementation phase, form of Cr, and parity should be considered when supplementing dairy cows with Cr. The results have important implications for the dairy industry and can contribute to the development of more effective feeding strategies for dairy cows.

Enteric Methane Emissions in Dairy Cows with Different Genetic Groups in the Humid Tropics of Costa Rica

Enteric methane (CH₄) is one of the main greenhouse gases emitted in livestock production systems with ruminants. Among the options to reduce such emissions, animal genetics is one of the factors that is taking relevance in recent years. The aim of the present study was to assess the emission of enteric CH₄ in dairy cows with different genetic backgrounds. Sixteen cows belonging to the following three genetic groups were selected for this study: seven F1 (50% Jersey × 50% Gyr), five Triple cross (50% Jersey × 31% Holstein × 19% Sahiwal) and four Jersey. Enteric CH₄ emissions were measured in all cows for 15 months, at the middle of each month, using the SF₆ technique. Enteric CH₄ emissions did not differ (p > 0.05) among genetic groups, although it varied with the stage of lactation, due to differences in milk yield and dry matter intake (DMI). Pasture DMI and the intensity of CH₄ emissions (g kg^-1 DMI) differed (p < 0.05) between dry and lactating cows, with higher DMI in the lactation period, while CH₄ emission intensity was higher for dry cows. Cows with the highest proportion of Bos taurus genes presented a higher annual mean methane conversion factor (Y_m), with 7.22, 7.05 and 5.90% for the Triple cross, purebred Jersey and F1, respectively. In conclusion, non-significant differences in enteric CH₄ emissions and Y_m were detected among dairy cows with different genetic backgrounds. However, F1 cows tended to show lower enteric CH₄ emission and Y_m, compared to those with more Bos taurus genes.

Understanding the relationship between weather variables and intake in beef steers

The relationship between weather variables and dry matter intake (DMI) in beef steers was examined using daily intake data from 790 beef steers collected through a computer-controlled feeding system in nonsummer months. Daily data were condensed into weekly averages (N = 13,895 steer-weeks). The variables considered to predict DMI (2.50 to 23.60 kg/d) were body weight (197 to 796 kg), dietary net energy for maintenance (NEm; 0.79 to 2.97 Mcal/kg), ambient temperature (-23.73 °C to 21.40 °C), range of temperature (2.79 °C to 19.43 °C), dew point (-27.84 °C to 14.34 °C), wind speed (2.08 to 6.49 m/s), solar radiation (30.8 to 297.1 W/m2), and 2-wk lag (average of previous 2 wk's values) and monthly lag (average of previous 4 wk's values) of each weather variable. Toeplitz variance-covariance structure for repeated measures was used to determine the model to predict DMI, while accounting for the effects of body weight, dietary NEm, and other variables in the model. Two-week lag of ambient temperature interacted (P ≤ 0.005) with 2-wk lag of range of temperature, monthly lag of wind speed, 2-wk lag of solar radiation, and dew point to predict DMI. Interactions (P = 0.0001) between 2-wk lag of range of temperature vs. dew point and monthly lag of wind speed vs. 2-wk lag of solar radiation were also detected. This study reports important weather variables associated with differences in DMI of growing and finishing steers and will help improve the accuracy of DMI prediction equations for beef cattle. Improvements in the accuracy of predicting DMI should give producers better tools to plan and execute efficient feeding management programs. The R2 of the overall model was 0.8891.

Predicting dry matter intake in beef cattle

Technology that facilitates estimations of individual animal dry matter intake (DMI) rates in group-housed settings will improve production and management efficiencies. Estimating DMI in pasture settings or facilities where feed intake cannot be monitored may benefit from predictive algorithms that use other variables as proxies. This study examined the relationships between DMI, animal performance, and environmental variables. Here we determined whether a machine learning approach can predict DMI from measured water intake variables, age, sex, full body weight, and average daily gain (ADG). Two hundred and five animals were studied in a drylot setting (152 bulls for 88 d and 53 steers for 50 d). Collected data included daily DMI, water intake, daily predicted full body weights, and ADG using In-Pen-Weighing Positions and Feed Intake Nodes. After exclusion of 26 bulls of low-frequency breeds and one severe (>3 standard deviations) outlier, the final number of animals used for modeling was 178 (125 bulls, 53 steers). Climate data were recorded at 30-min intervals throughout the study period. Random Forest Regression (RFR) and Repeated Measures Random Forest (RMRF) were used as machine learning approaches to develop a predictive algorithm. Repeated Measures ANOVA (RMANOVA) was used as the traditional approach. Using the RMRF method, an algorithm was constructed that predicts an animal's DMI within 0.75 kg. Evaluation and refining of algorithms used to predict DMI in drylot by adding more representative data will allow for future extrapolation to controlled small plot grazing and, ultimately, more extensive group field settings.

Effects of diet on feed intake, weight change, and gas emissions in beef cows

The objective of this study was to examine the effects of diet energy density on ranking for dry matter intake (DMI), residual feed intake (RFI), and greenhouse gas emissions. Forty-two mature, gestating Angus cows (600 ± 69 kg body weight [BW]; body condition score [BCS] 5.3 ± 1.1) with a wide range in DMI expected progeny difference (-1.38 to 2.91) were randomly assigned to two diet sequences; forage then concentrate (FC) or concentrate then forage (CF). The forage diet consisted of long-stem native grass hay plus protein supplement (HAY; 1.96 Mcal ME/kg DM). The concentrate diet consisted of 35% chopped grass hay and 65% concentrate feeds on a dry matter basis (MIX; 2.5 Mcal ME/kg DM). The GreenFeed Emission Monitoring system was used to determine carbon dioxide (CO2), oxygen (O2), and methane (CH4) flux. Cow performance traits, ultrasound back fat and rump fat, feed DMI, and gas flux data were analyzed in a crossover design using a mixed model including diet, period, and sequence as fixed effects and pen and cow within sequence as random effects. For all measured traits excluding DMI, there was a diet × sequence interaction (P < 0.05). The correlation between MIX and HAY DMI was 0.41 (P = 0.067) and 0.47 (P = 0.03) for FC and CF sequences, respectively. There was no relationship (P > 0.66) between HAY and MIX average daily gain (ADG), regardless of sequence. Fifty-seven percent of the variation in DMI was explained by metabolic BW, ADG, and BCS for both diets during the first period. During the second period, the same three explanatory variables accounted for 38% and 37% of the variation in DMI for MIX and HAY diets, respectively. The negative relationship between BCS and DMI was more pronounced when cows consumed the MIX diet. There was no relationship between MIX and HAY RFI, regardless of sequence (P > 0.18). During the first period, correlations for CO2, CH4, and O2 with MIX DMI were 0.69, 0.81, and 0.56 (P ≤ 0.015), respectively, and 0.76, 0.74, and 0.64 (P < 0.01) with HAY DMI. During the second period, correlations for CO2, CH4, and O2 with MIX DMI were 0.62, 0.47, and 0.56 (P ≤ 0.11), respectively. However, HAY DMI during the second period was not related to gas flux (P > 0.47). Results from this experiment indicate that feed intake of two energy-diverse diets is moderately correlated while ADG while consuming the two diets is not related. Further experimentation is necessary to determine if gas flux data can be used to predict feed intake in beef cows.

Effects of calcareous marine algae on milk production, feed intake, energy balance, mineral status, and inflammatory markers in transition dairy cows

The objective of this experiment was to compare the effects of calcareous marine algae (CMA; Acid Buf, Celtic Sea Minerals) with a limestone-based control on feed intake, milk production, energy balance, serum mineral metabolites, and inflammatory markers in transition dairy cows. Twenty-two multiparous and 10 primiparous cows were assigned to 2 treatments from 25 d before expected parturition until 42 d postpartum. Cows were assigned to treatment according to a randomized complete block design based on parity, pre-experimental body condition score, previous 305-d milk yield, and either fat + protein yield (for multiparous cows) or predicted transmitting ability for milk yield and fat + protein yield (for primiparous cows). Cows were fed a negative dietary cation-anion difference [-50 mEq/kg] total mixed ration (TMR) based on corn silage, grass silage, and straw during the prepartum period and a 50:50 forage:concentrate TMR based on grass silage, corn silage, and concentrate during the postpartum period. The 2 dietary treatments consisted of a control (CON), which contained limestone as the primary calcium source, and CMA, in which limestone was replaced by CMA at 0.42% and 0.47% of dry matter for the pre- and postpartum periods, respectively. The dietary treatments were fed as 2 different concentrate pellets added to the TMR. Cows fed the CMA diet had higher dry matter intake in both the prepartum (+1.08 kg) and postpartum (+0.94 kg) periods compared with cows fed the CON diet. Fat yield (+0.11 kg), fat concentration (+0.43%), and 4% fat-corrected milk (+1.56 kg) were higher in cows fed CMA than in cows fed CON. The concentration of plasma serum amyloid A was reduced and that of serum P was increased on the CMA treatment compared with the CON treatment. These findings demonstrate the benefits of supplementing CMA to dairy cows during the transition period compared with a CON treatment containing limestone as the primary Ca source.

Effects of rumen-protected glutamate supplementation during the periparturient period on digestibility, inflammation, metabolic responses, and performance in dairy cows

The objective of this study was to evaluate the effects of feeding rumen-protected glutamate during the periparturient period (d -21 ± 3 to d 21 ± 3 relative to calving) on apparent total-tract digestibility (ATTD), inflammation, metabolic responses, and production performance of dairy cows. Fifty-two multiparous Holstein cows were blocked by parity, body condition score, and expected calving date, and randomly assigned to one of the experimental diets with rumen-protected monosodium glutamate (RP-Glu; intestinally available Glu = 8.8%) or without RP-Glu (control) at d -21 ± 3 relative to expected calving date. The RP-Glu was fed at 4% and 3% of dietary dry matter, before and after calving, respectively. Prepartum diets contained 17.1% and 16.5% crude protein, and 13.1% and 13.3% starch, and postpartum diets contained 18.8% and 18.3% crude protein, and 22.5% and 22.7% starch on a dry matter basis, respectively for RP-Glu and control treatments. A subset of 19 cows was used to measure ATTD. Cows fed the RP-Glu had greater ATTD of dry matter (70.6 vs. 69.1%), crude protein (75.1 vs. 72.6%), and ether extract (66.0 vs 61.2%) on d 5 ± 1 after calving. Cows fed the RP-Glu also had greater dry matter intake (15.7 vs. 13.7 kg/d) on d 1 after calving. Cows fed the RP-Glu had greater plasma concentrations of Glu (4.60 vs. 3.89 µmol/dL) and insulin-like growth factor-1 (44.2 vs. 30.1 mg/mL), lower serum concentrations of free fatty acids (670 vs. 981 μEq/L) and total bilirubin (0.22 vs. 0.34 mg/dL), and lower plasma 3-methylhistidine concentration (1.28 vs. 1.50 μmol/dL) on d 4 after calving. However, these treatment effects observed between d 1 and d 5 ± 1 immediately after calving did not continue until d 21 after calving. Concentrations of serum amyloid A, serum haptoglobin, and plasma lipopolysaccharide binding protein were not affected by the treatment. In addition, no differences were observed for serum β-hydroxybutyrate concentration and milk yield during the postpartum period between the 2 groups, and cows fed the RP-Glu had a decreased lactose yield. These findings suggest that feeding RP-Glu during the periparturient period can increase digestive capacity and feed intake, and decrease mobilization of body fat and protein immediately after calving without increasing milk production.

Intake and apparent digestibility of dry matter, milk production, and composition of cows fed with diets containing oilseed cakes: A meta-analysis

Oilseed cakes can partially replace corn or soy used in the diet without losing animal performance. The objective was to carry out a meta-analysis and principal component analysis to evaluate the effects of cakes on the intake and apparent digestibility coefficient (ADC) of dry matter (DM) and milk production and composition in lactating dairy cows. The data set used in the meta-analysis came from 51 studies published between 2009 and 2019, which resulted in 119 studies with 18 types of cakes evaluated in 1350 cows. Cows fed with cakes increased dry matter intake (DMI) by 0.366 kg d^-1 (P < 0.001) and DMI as a function of the animal's body weight by 0.103% (P < 0.0001) compared with the diet without cake. The milk protein content decreased by 0.050% (P < 0.010). The contents of neutral detergent fiber (NDF) (26%-%) and ether extract (EE) (3%-7%) of the cake diets did not affect ADCDM. Cakes with contents between 10% and 30% can replace corn or soy in the diet without affecting milk production, components (fat, protein, and lactose), and contents (fat and lactose), but it can reduce the milk protein content of milk.

Inter- and Intra-Individual Variation in the Behavior of Feed Intake on Nutrient Availability in Early Lactating Dairy Cows

Simple Summary

The problem of nutrient and energy deficiency and the associated risk of disease in fresh dairy cows has been known for many years. Previous approaches to reducing the risk have been almost exclusively on a herd basis approach but have so far not been sufficiently effective. The present study revealed large variation between individual animals during the first weeks after calving, particularly with respect to dry matter intake (DMI). In addition to the large variation in intake behavior, feed intake and nutrient digestibility, interactions between parameters refute the traditional feeding regimes, based on the mean requirement values at herd level. Inter-individual variation indicates that each animal follows an individual strategy in optimizing DMI. Only if constant access to the feed bunk and balanced diets are made possible, all animals can follow their individual strategy, maximize individual DMI and come closer to the goal of an adequate supply. As there is only a low risk for excessive DMI during early lactation, feeding regimes should not be oriented towards the assumed average level of feed intake but towards the animals with a low level of dry matter intake. Otherwise, it will not be possible to improve the nutrient supply for all animals.

Abstract

Since energetic deficits in dairy cows can only be reduced at an animal level, the objective of the present study was to determine the extent of variation in intake behavior within and between animals during early lactation, to explore the magnitude of interactions between feed intake, intake behavior and nutrient digestibility, and to identify levers for maximizing feed intake at the individual animal level. Feeding behavior, intake and nutrient digestibility of 28 German Holstein dairy cows, fed TMR with 7.0 MJ NEL, were studied between the 2nd and 15th week after calving. Dry matter intake was assessed daily and nutrient digestibility weekly, with iNDF₂₄₀ as an intrinsic marker. Results showed high intra- and inter-individual variation in intake behavior parameters with coefficients of variation (CV) up to 0.58 in meal frequency. Nutrient digestibility varied only slightly with CV values up to 0.10 in crude protein. Milk yield, meal frequency, feeding time, feeding rate and meal size had significant positive effects on DMI (p < 0.01). To achieve long-term improvements in feed intake, it is important to optimize feed intake and feeding behavior of individual animals by improving feeding conditions and develop technical tools to identify animals with insufficient feed intake.

Are subjectively scored linear type traits suitable predictors of the genetic merit for feed intake in grazing Holstein-Friesian dairy cows?

Measuring dry matter intake (DMI) in grazing dairy cows using currently available techniques is invasive, time consuming, and expensive. An alternative to directly measuring DMI for use in genetic evaluations is to identify a set of readily available animal features that can be used in a multitrait genetic evaluation for DMI. The objectives of the present study were thus to estimate the genetic correlations between readily available body-related linear type traits and DMI in grazing lactating Holstein-Friesian cows, but importantly also estimate the partial genetic correlations between these linear traits and DMI, after adjusting for differences in genetic merit for body weight. Also of interest was whether the predictive ability derived from the estimated genetic correlations materialized upon validation. After edits, a total of 8,055 test-day records of DMI, body weight, and milk yield from 1,331 Holstein-Friesian cows were available, as were chest width, body depth, and stature from 47,141 first lactation Holstein-Friesian cows. In addition to considering the routinely recorded linear type traits individually, novel composite traits were defined as the product of the linear type traits as an approximation of rumen volume. All linear type traits were moderately heritable, with heritability estimates ranging from 0.27 (standard error = 0.14) to 0.49 (standard error = 0.15); furthermore, all linear type traits were genetically correlated (0.29 to 0.63, standard error 0.14 to 0.12) with DMI. The genetic correlations between the individual linear type traits and DMI, when adjusted for genetic differences in body weight, varied from -0.51 (stature) to 0.48 (chest width). These genetic correlations between DMI and linear type traits suggest linear type traits may be useful predictors of DMI, even when body weight information is available. Nonetheless, estimated genetic merit of DMI derived from a multitrait genetic evaluation of linear type traits did not correlate strongly with actual DMI in a set of validation animals; the benefit was even less if body weight data were also available.

Feed Intake of Growing Dairy Heifers Raised under Tropical Conditions: A Model Evaluation Using Meta-Analysis

Several models for predicting dry matter intake (DMI) of replacement dairy heifers have been developed; however, only a few have been evaluated using data from heifers of different breeds raised under tropical conditions. Thus, the objective of this study was to evaluate the DMI equations for dairy heifers managed under tropical conditions. A total of 230 treatment means from 61 studies using dairy heifers (n = 1513 heifers, average body weight = 246 kg) were used. The animals were grouped into two groups based on their genetics: (1) Bos taurus (Holstein, Jersey, Brown Swiss, and Holstein × Jersey) and (2) crossbred (Bos taurus × Bos indicus). Seven previously published DMI equations (HH, HHJ, QUI, STA, 2001 NRC, OFLin, and OFNLin) for heifers were evaluated using mean bias, slope bias, mean squared prediction errors (MSPE) and its decomposition, and other model evaluation statistics. For Bos taurus heifers, our results indicated that OFNLin and HHJ had lower mean bias (0.13 and 0.16 kg/d, respectively) than other models. There was no significant slope or mean bias for HHJ and OFNLin (p > 0.05), indicating agreement between the observed and predicted DMI values. All other models had a significant mean bias (p < 0.05), whereas the QUI model also presented a significant slope bias (p < 0.02). For crossbred heifers, the STA equation was the only one that did not present mean and slope bias significance (p > 0.05). All other DMI models had significant mean bias when evaluated using crossbred data (p < 0.04), and QUI, OFLin, and OFNLin also presented significant slope bias (p < 0.01). Based on our results, predictions from OFNLin and HHJ best represented the observed DMI of Bos taurus heifers (MSPE ≤ 1.25 kg²/d², mean bias ≤ 0.16 kg/d), whereas STA was the best model for crossbred heifers (MSPE = 1.25 kg²/d², mean bias = 0.09 kg/d). These findings indicate that not all available models are adequate for estimating the DMI of dairy heifers managed under a tropical climate, with HHJ and OFNLin for Bos taurus and STA for crossbreds being the most suitable models for DMI prediction. There is evidence that models from Bos taurus heifers could be used to estimate the DMI of heifers under tropical conditions. For heifer ration formulation is necessary to consider that DMI is influenced by breed, diet, management, and climate. Future work should also include animal genetic and environmental variables for the prediction of DMI in dairy heifers.

Effects of Replacing Grass with Foliage on Growth Rate and Feed Intake in Goats-A Systematic Review and Meta-Analysis

Simple Summary

Goats are important as food sources and livelihood in several areas of the world, mainly in low-income countries. Free-range browsing is common, but to increase productivity and improve health, supplemental or complete feeding is increasing. Ruminant feeding has often been using grasses, but as goats are browsers, they may benefit from including foliage in the diet. This systematic review and meta-analysis focuses on the effect of including foliage in goat diets. The results show that foliage was often more nutrient-rich and increased dry matter intake as well as average daily weight gain in goats.

Abstract

Small ruminants such as goats have a higher preference for browse species than cattle and sheep. In a meta-analysis of 42 papers describing 117 experimental treatments found by a search performed in June 2021 in PubMed and Web of Knowledge, we examined the general effect of including foliage in the diet of goats, replacing grasses, on dry matter intake and average daily weight gain. The inclusion requirement for a paper was that it described a controlled trial with a control diet of grass and with grass replaced by foliage in the experimental diet. Publication bias was estimated by calculating the Fail-safe n. Random effects analyses were conducted, using effect size calculated as Hedges’ d. The results showed that inclusion of foliage increased feed intake (Hedges’ d = 1.350, SE = 0.388) and average daily weight gain (Hedges’ d = 1.417, SE = 0.444) compared with a grass-based control. The positive effect of foliage inclusion on dry matter intake was associated with lower neutral detergent fiber (NDF) and higher crude protein (CP) in the foliage than in the grass it replaced. The positive effect on average daily weight gain was associated with higher CP concentration in the foliage than in grass. Foliage inclusion level showed a quadratic relationship with dry matter intake, with maximum dry matter intake achieved at a level of 50–60%. There was wide variation between the studies reviewed, and this variation was not reduced by subgroup analysis based on different kinds of foliage. In conclusion, the addition of foliage to goat diets can increase feed intake and daily weight gain, as an effect of the dietary preferences of goats and of generally higher nutritional value in foliage species compared with natural/semi-natural grass species.

The effect of Holstein-Friesian, Jersey × Holstein-Friesian, and Norwegian Red × (Jersey × Holstein-Friesian) cows on dry matter intake and production efficiencies in pasture-based systems

The objective of this study was to investigate the effect of cow genotype and parity on dry matter intake (DMI) and production efficiencies in pasture-based systems. Three dairy cow genotypes were evaluated over 3 yr; 40 Holstein-Friesian (HF), 40 Jersey × HF (JEX), and 40 Norwegian Red × JEX (3WAY) each year, with each genotype grazed in equal numbers on 1 of 4 grazing treatments in a 2 × 2 factorial arrangement of treatments [diploid or tetraploid perennial ryegrass (Lolium perenne L.) with or without white clover (Trifolium repens L.)]. A total of 208 individual cows were used during the experiment. The effect of parity (lactation 1, 2, and 3+) was also evaluated. Individual DMI was estimated 8 times during the study, 3 times in 2015 and in 2017, and twice in 2016, using the n-alkane technique. Days in milk at each DMI measurement period were 64, 110, and 189, corresponding to spring, summer, and autumn. Measures of milk production efficiency calculated were total DMI/100 kg of body weight (BW), milk solids (kg fat + protein; MSo)/100 kg of BW, solids-corrected milk (SCM)/100 kg of BW, and unité fourragère lait (net energy requirements for lactation equivalent of 1 kg of standard air-dry barley; UFL) available for standard (4.0% fat and 3.1% protein content) milk production after accounting for maintenance. During the DMI measurement periods HF had a greater milk yield (23.2 kg/cow per d) compared with JEX and 3WAY (22.0 and 21.9 kg/cow per d, respectively) but there was no difference in MSo yield. Holstein-Friesian and JEX, and JEX and 3WAY had similar DMI, but HF had greater total DMI than 3WAY (DMI was 17.2, 17.0, and 16.7 kg/cow per d for HF, JEX, and 3WAY, respectively). Jersey × Holstein-Friesian cows were the most efficient for total DMI/100 kg of BW, SCM/100 kg of BW, and MSo/100 kg of BW (3.63, 4.96, and 0.39 kg/kg of BW) compared with HF (3.36, 4.51, and 0.35 kg/kg of BW) and 3WAY (3.45, 4.63, and 0.37 kg/kg of BW), respectively. Unité fourragère lait available for standard milk production after accounting for maintenance was not different among genotypes. As expected, DMI differed significantly among parities with greater parity cows having higher DMI and subsequently higher milk and MSo yield. Although all 3 genotypes achieved high levels of DMI and production efficiency, JEX achieved the highest production efficiency. Some of the efficiency gains (SCM/100 kg of BW, MSo/100 kg of BW, and total DMI/100 kg of BW) achieved with JEX decreased when the third breed (Norwegian Red) was introduced.

Investigating the Use of Dry Matter Intake and Energy Balance Prepartum as Predictors of Digestive Disorders Postpartum

One objective was to evaluate the association of dry matter intake as a percentage of body weight (DMI%BW) and energy balance (EB) prepartum and postpartum, and energy-corrected milk (ECM) postpatum with digestive disorders postpartum. For this, ANOVA was used, and DMI%BW, EB, and ECM were the outcome variables, and left displaced abomasum (LDA), indigestion, and other digestive disorders (ODDZ) were the explanatory variables. The main objective was to evaluate prepartum DMI%BW and EB as predictors of digestive disorders. For this, logistic regression was used, and LDA, indigestion, and ODDZ were the outcome variables and DMI%BW and EB were the explanatory variables. Data from 689 cows from 11 experiments were compiled. Left displaced abomasum was not associated with prepartum DMI%BW or EB. Postpartum data were normalized to the day of the event (day 0). Cows that developed LDA had lesser postpartum DMI%BW on days −24, −23, −12, −7 to 0 and from days 1 to 8, 10 to 12, and 14 and 16, lesser postpartum EB from days −7 to −5, −3 to 0, and 12, and lesser postpartum energy-corrected milk on days −19, −2, −1, 0, 7, 9, 10, 15, and 17 relative to diagnosis than cows without LDA. Cows that developed indigestion had lesser prepartum DMI%BW and EB than cows without indigestion, and lesser postpartum DMI%BW on days −24, −1, 0, 1, and 2, and greater DMI%BW on day 26, lesser ECM on days −24, −2, −1, 0, 1, and 2 relative to diagnosis. Postpartum EB was not associated with indigestion postpartum. Cows that developed ODDZ had lesser prepartum DMI%BW on day −8 and from days −5 to −2, lesser prepartum EB on day −8 and from days −5 to −2, and lesser postpartum DMI%BW than cows without ODDZ. Each 0.1 percentage point decrease in the average DMI%BW and each Mcal decrease in the average EB in the last 3 days prepartum increased the odds of having indigestion by 9% each. Cutoffs for DMI%BW and EB during the last 3 days prepartum to predict indigestion were established and were ≤1.3%/day and ≤0.68 Mcal/day, respectively. In summary, measures of prepartum DMI%BW and EB were associated with indigestion and ODDZ postpartum and were predictors of indigestion postpartum, although the effect sizes were small.

A Basic Model to Predict Enteric Methane Emission from Dairy Cows and Its Application to Update Operational Models for the National Inventory in Norway

The aim of this study was to develop a basic model to predict enteric methane emission from dairy cows and to update operational calculations for the national inventory in Norway. Development of basic models utilized information that is available only from feeding experiments. Basic models were developed using a database with 63 treatment means from 19 studies and were evaluated against an external database (n = 36, from 10 studies) along with other extant models. In total, the basic model database included 99 treatment means from 29 studies with records for enteric CH₄ production (MJ/day), dry matter intake (DMI) and dietary nutrient composition. When evaluated by low root mean square prediction errors and high concordance correlation coefficients, the developed basic models that included DMI, dietary concentrations of fatty acids and neutral detergent fiber performed slightly better in predicting CH₄ emissions than extant models. In order to propose country-specific values for the CH₄ conversion factor Y_m (% of gross energy intake partitioned into CH₄) and thus to be able to carry out the national inventory for Norway, the existing operational model was updated for the prediction of Y_m over a wide range of feeding situations. A simulated operational database containing CH₄ production (predicted by the basic model), feed intake and composition, Y_m and gross energy intake (GEI), in addition to the predictor variables energy corrected milk yield and dietary concentrate share were used to develop an operational model. Input values of Y_m were updated based on the results from the basic models. The predicted Y_m ranged from 6.22 to 6.72%. In conclusion, the prediction accuracy of CH₄ production from dairy cows was improved with the help of newly published data, which enabled an update of the operational model for calculating the national inventory of CH₄ in Norway.

Influence of Residual Feed Intake and Cow Age on Dry Matter Intake Post-Weaning and Peak Lactation of Black Angus Cows

Simple Summary

Supplemental nutrition for cattle is the greatest operating cost for cow-calf producers, accounting for 65% of the annual expenses. In addition, residual feed intake (RFI) is being used as a selection tool for purchasing and retaining heifers, as well as selecting bulls with the goal of improving feed efficiency and/or reducing supplemental inputs. However, the use and relevance of RFI as a selection tool for the cow-calf industry needs additional research. In our studies, heifer post-weaning RFI did not influence mature cow dry matter intake and intake behavior for both lactating and non-lactating beef cows. In contrast, cow age did correspond to increases of intake and intake rates of mature cows. However, when intake was expressed as g/kg body weight⁻¹, no differences were observed with respect to cow age for lactating and non-lactating cows. Milk production was influenced by heifer post-weaning RFI in 5–6- and 8–9-year-old cows, however, did not influence 9–10-year-old cows. Therefore, our research suggests that cow age has greater impacts on dry matter intake than RFI, however, the relationship between RFI of heifers and subsequent mature cow milk production warrants further investigation.

Abstract

We evaluated heifer post-weaning residual feed intake (RFI) classification and cow age on dry matter intake (DMI) at two stages of production. Fifty-nine non-lactating, pregnant, (Study 1) and fifty-four lactating, non-pregnant (Study 2) commercial black Angus beef cows were grouped by age and RFI. Free-choice, hay pellets were fed in a GrowSafe feeding system. In Study 1, cow DMI (kg/d) and intake rate (g/min) displayed a cow age effect (p < 0.01) with an increase in DMI and intake rate with increasing cow age. In Study 2, cow DMI (kg/d) and intake rate (g/min) displayed a cow age effect (p < 0.02) with an increase in DMI and intake rate with increasing cow age. Milk production displayed a cow age × RFI interaction (p < 0.01) where both 5–6-year-old and 8–9-year-old low RFI cows produced more milk than high RFI cows. For both studies, intake and intake behavior were not influenced by RFI (p ≥ 0.16) or cow age × RFI interaction (p ≥ 0.21). In summary, heifer’s post-weaning RFI had minimal effects on beef cattle DMI or intake behavior, however, some differences were observed in milk production.

Effects of dietary energy and protein levels on nutrient intake, digestibility, and body weight change in Hararghe highland and Afar sheep breeds of Ethiopia

OBJECTIVES

The experiment was conducted to determine the effect of dietary energy and protein level growth performances of selected indigenous Ethiopian sheep breeds.

MATERIALS AND METHODS

Fifty intact ram lambs, 25 from each breed with 12 months of age and a mean initial body weight (IBW) of 19.31 ± 1.7 kg, were employed for this experiment. Animals were distributed randomly into five dietary treatments, i.e., minimum Energy and Protein (mEmP), medium energy and protein (MEMP), medium Energy and high Protein (MEHP), high energy and medium protein (HEMP), and high Energy and high Protein (HEHP) diets in randomized complete block design with 2 * 5 factorial arrangements. The minimum, medium, and high energy diets were 2.388, 2.866, and 3.344 Mcal/kg dry matter (DM) with the corresponding 10%, 16%, and 20% crude protein (CP) diets, respectively. The diets were formulated in a total mixed ration from wheat bran (WB), maize grain, peanut cake, and pasture hay feed ingredients. Diet offer was at the rate of 3% of lambs' live weight and revised biweekly as per the attained body weight changes. Digestibility trial was conducted for 7 days of actual fecal data collection, followed by 90 days of feeding trial.

RESULTS

The animals fed on the MEHP diet had a maximum DM and nutrient intakes (CP and organic matter) and the best final body weight (FBW), total gain, gain rate, average daily gains, and feed conversion efficiency (31.3, 12.9 kg, 41.2%, 143.3 gm, and 23.13, respectively), followed by HEMP, HEHP, MEMP, and mEmP diets. Digestibility of DM and nutrients linearly followed similar trends (p < 0.01). Hararghe sheep was heavier (p < 0.01) by 4.3 and 3.1 kg in its FBW and total gain and more efficient in nutrients utilization (22.57 vs. 18.18) as compared to Afar sheep (AS).

CONCLUSION

It is concluded that MEHP and MEMP are superior and optimum diets for sheep breeds, and Hararghe sheep is carried out better than AS in most growth performance parameters.

Multiple Country Approach to Improve the Test-Day Prediction of Dairy Cows' Dry Matter Intake

Simple Summary

Dry matter intake, related to the number of nutrients available to an animal to meet its production and health needs, is crucial for the economic, environmental, and welfare management of dairy herds. Because the equipment required to weigh the ingested food at an individual level is not broadly available, we propose some new ways to approach the actual dry matter consumed by a dairy cow for a given day. To do so, we used regression models using parity (number of lactations), week of lactation, milk yield, milk mid-infrared spectrum, and prediction of bodyweight, fat, protein, lactose, and fatty acids content in milk. We chose these elements to predict individual dry matter intake because they are either easily accessible or routinely provided by regional dairy organizations (often called “dairy herd improvement” associations). We succeeded in producing a model whose dry matter intake predictions were moderately related to the actual values.

Abstract

We predicted dry matter intake of dairy cows using parity, week of lactation, milk yield, milk mid-infrared (MIR) spectrum, and MIR-based predictions of bodyweight, fat, protein, lactose, and fatty acids content in milk. The dataset comprised 10,711 samples of 534 dairy cows with a geographical diversity (Australia, Canada, Denmark, and Ireland). We set up partial least square (PLS) regressions with different constructs and a one-hidden-layer artificial neural network (ANN) using the highest contribution variables. In the ANN, we replaced the spectra with their projections to the 25 first PLS factors explaining 99% of the spectral variability to reduce the model complexity. Cow-independent 10 × 10-fold cross-validation (CV) achieved the best performance with root mean square errors (RMSE_CV) of 3.27 ± 0.08 kg for the PLS regression and 3.25 ± 0.13 kg for ANN. Although the available data were significantly different, we also performed a country-independent validation (CIV) to measure the models’ performance fairly. We found RMSE_CIV varying from 3.73 to 6.03 kg for PLS and 3.69 to 5.08 kg for ANN. Ultimately, based on the country-independent validation, we discussed the developed models’ performance with those achieved by the National Research Council’s equation.

Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model

Simple Summary

Moisture content is an important parameter for monitoring the quality of feed and feed materials as its established ranges serve as markers for safe storage, mixing, and feeding animals. The moisture content of feed materials changes very rapidly and necessitates rapid measurement. Current moisture content measurement methods are time-consuming, destructive, and require specialized skills. This often causes reduced and/or delayed testing, which results in the spoilage of feed and feed materials. Additionally, the improper balance of dry matter intake which is inversely proportional to moisture content often causes metabolic diseases for animals consuming the diet. To solve these, we have developed a rapid and non-destructive global hyperspectral model that could quantify moisture content in feed materials. Our results show that the developed model is robust, could provide a method to measure the distribution of moisture in feed, and has potential for implementation in a commercial setting.

Abstract

The dry matter (DM) content of feed is vital in cattle nutrition and is inversely correlated with moisture content. The established ranges of moisture content serve as a marker for factors such as safe storage limit and DM intake. Rapid changes in moisture content necessitate rapid measurements. A rapid and non-destructive global model for the measurement of moisture content in total mixed ration feed and feed materials was developed. To achieve this, we varied and measured the moisture content in the feed and feed materials using standard methods and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 1000–2500 nm. The spectral data from the samples were extracted and preprocessed using seven techniques and were used to develop a global model using partial least squares regression (PLSR) analysis. The range preprocessing technique had the best prediction accuracy (R² = 0.98) and standard error of prediction (2.59%). Furthermore, the visual assessment of distribution in moisture content made possible by the generated PLSR-based moisture content mapped images could facilitate precise formulation. These applications of HSI, when used in commercial feed production, could help prevent feed spoilage and resultant health complications as well as underperformance of the animals from improper DM intake.

The effects of organic grass and grass-birdsfoot trefoil pastures on Jersey heifer development: Herbage characteristics affecting intake

Low dietary energy and decreased intake of herbage have been attributed to the reduced performance of grazing dairy cattle. We hypothesized that grasses with inherently greater energy would interact in a complementary way with condensed tannins (CT) in birdsfoot trefoil to increase herbage intake by grazing dairy heifers. Eight pasture treatments comprising high-sugar perennial ryegrass (Lolium perenne L.), orchardgrass (Dactylis glomerata L.), meadow bromegrass (Bromus riparius Rehmann), and tall fescue [Schendonorus arundinaceus (Schreb.) Dumort] were established in Lewiston, Utah as monocultures and binary mixtures with birdsfoot trefoil (Lotus corniculatus L.; BFT). Pasture treatments were rotationally stocked by Jersey heifers for 105 d in 2017 and 2018, and herbage samples were collected pre- and postgrazing for each 7-d grazing period and analyzed for herbage mass, nutritive value, and apparent herbage intake. We observed differences among pasture treatments in herbage quantity and nutritive value, as well as differences in herbage intake by grazing Jersey heifers. On average, grass-BFT mixtures had greater herbage intake than grass monocultures, and every grass-BFT treatment individually had greater herbage intake than their respective grass monocultures. Using multivariate analyses, we determined that approximately 50% of the variation in herbage intake was due to nutritive and physical herbage characteristics, with the most explanatory being characteristics related to fiber and energy, followed by those related to the percent of BFT in the herbage. Grass monocultures exhibited a range of inherent dietary energy, but there was indication that an imbalance of energy to crude protein (e.g., protein deficient) reduced intake of grass monocultures. Moreover, there was some evidence of a complementary effect between increased dietary energy and CT; however, low CT levels made it impossible to determine the effect of CT on herbage intake per se. This study confirmed that chemical and physical characteristics inherent to different pasture species have a large effect on herbage intake by grazing cattle. Pastures planted to binary mixtures of nutritious grasses and birdsfoot trefoil increase herbage intake of temperate pastures by grazing Jersey heifers.

Dietary soluble non-starch polysaccharide level and composition influences grower and finisher phase performance, excreta moisture content and total tract nutrient digestibility in broilers

1. The aim of this study was to examine the impact of dietary soluble non-starch polysaccharide (sNSP) level and composition on grower and finisher phase performance, total tract nutrient digestibility and excreta moisture content in broiler chickens.2. Cobb 500 broilers (n = 1080) were fed 12 dietary treatments; four diets with differing primary grain sources (barley, corn, sorghum and wheat) and three different sNSP levels (low, medium and high). Diets were formulated to have similar protein and energy levels but differing sNSP levels, induced by manipulating the quantity of the ingredients in the diet. The diets were fed in three phases, starter (d 0-12), grower (d 12-23) and finisher (d 23-31).3. For birds aged d 23 and 31, total pen body weight and feed intake were determined, and fresh excreta and litter samples were collected per pen. Dry matter (DM) content was measured in the excreta and litter samples. Total tract DM digestibility, apparent metabolisable energy corrected to nitrogen (AMEn), and soluble and insoluble NSP and free oligosaccharide degradability were evaluated.4. In birds fed the sorghum- and corn-based diets, feeding high sNSP resulted in a lower cFCR at d 0-23 compared to low sNSP (P = 0.004 and P = 0.044, respectively). In birds fed the corn-based diet, feeding low sNSP resulted in the lowest litter DM but highest DM digestibility at d 23 (P = 0.045 and P < 0.001) and d 31 (P = 0.022 and P = 0.008). For all diets, degradability of sNSP was higher and insoluble NSP was lower when feeding low compared to high sNSP (P < 0.001). In birds fed the barley- and sorghum-based diets, AMEn was lower when feeding the low compared to high sNSP level (P < 0.001 and P = 0.016, respectively).6. Results from this study showed that level of dietary sNSP impacts broiler productive performance and nutrient utilisation.

Comparison of methods to predict feed intake and residual feed intake using behavioral and metabolite data in addition to classical performance variables

Predicting dry matter intake (DMI) and feed efficiency by leveraging the use of data streams available on farm could aid efforts to improve the feed efficiency of dairy cattle. Residual feed intake (RFI) is the difference between predicted and observed feed intake after accounting for body size, body weight change, and milk production, making it a valuable metric for feed efficiency research. Our objective was to develop and evaluate DMI and RFI prediction models using multiple linear regression (MLR), partial least squares regression, artificial neural networks, and stacked ensembles using different combinations of cow descriptive, performance, sensor-derived behavioral (SMARTBOW; Zoetis), and blood metabolite data. Data were collected from mid-lactation Holstein cows (n = 124; 102 multiparous, 22 primiparous) split equally between 2 replicates of 45-d duration with ad libitum access to feed. Within each predictive approach, 4 data streams were added in sequence: dataset M (week of lactation, parity, milk yield, and milk components), dataset MB (dataset M plus body condition score and metabolic body weight), dataset MBS (dataset MB plus sensor-derived behavioral variables), and dataset MBSP (dataset MBS plus physiological blood metabolites). The combination of 4 datasets and 4 analytical approaches resulted in 16 analyses of DMI and RFI, using variables averaged within cow across the study period. Additional models using weekly averaged data within cow and study were built using all predictive approaches for datasets M, MB, and MBS. Model performance was assessed using the coefficient of determination, concordance correlation coefficient, and root mean square error of prediction. Predictive models of DMI performed similarly across all approaches, and models using dataset MBS had the greatest model performance. The best approach-dataset combination was MLR-dataset MBS, although several models performed similarly. Weekly DMI models had the greatest performance with MLR and partial least squares regression approaches. Dataset MBS models had incrementally better performance than datasets MB and M. Within each approach-dataset combination, models with DMI averaged over the study period had slightly greater model performance than DMI averaged weekly. Predictive performance of all RFI models was poor, but slight improvements when using MLR applied to dataset MBS suggest that rumination and activity behaviors may explain some of the variation in RFI. Overall, similar performance of MLR, compared with machine learning techniques, indicates MLR may be sufficient to predict DMI. The improvement in model performance with each additional data stream supports the idea of integrating data streams to improve model predictions and farm management decisions.

Effects of corn grain endosperm type and fineness of grind on feed intake, feeding behavior, and productive performance of lactating dairy cows

Our objective was to evaluate effects of corn grain endosperm type and fineness of grind on feed intake, feeding behavior, ruminal fermentation, and productive performance of lactating cows. Eight ruminally and duodenally cannulated Holstein cows in mid lactation (130 ± 42 d in milk; mean ± standard deviation) were used in a duplicated 4 × 4 Latin square design with 21-d periods. A 2 × 2 factorial arrangement of treatments was used with main effects of corn grain endosperm type (floury or vitreous) and fineness of grind of corn grain (fine or medium). Rations were formulated to contain 29% starch, 27% neutral detergent fiber, 18.2% forage neutral detergent fiber, and 18% crude protein. Corn grain treatments supplied 86.2% of dietary starch. Endosperm was 25% vitreous for floury corn and 66% vitreous for vitreous corn. Fineness of grind did not affect dry matter intake (DMI), but floury corn tended to reduce DMI (23.8 vs. 25.1 kg/d) compared with vitreous corn. Floury corn increased meal frequency more for fine grind size (9.57 vs. 9.41 meals/d) than medium grind size (9.78 vs. 9.75 meals/d). However, there were no effects of treatment on any other measure of feeding behavior. Endosperm type did not affect yields of milk or milk components or milk composition except that vitreous corn tended to decrease milk lactose concentration compared with floury corn. Finely ground corn decreased yields of milk (31.1 vs. 33.1 kg/d), 3.5% fat-corrected milk (33.1 vs. 35.1 kg/d), milk fat (1.22 vs. 1.32 kg/d), milk lactose (1.48 vs. 1.59 kg/d), and solids not fat (2.46 vs. 2.63 kg/d) compared with medium grind size. However, fineness of grind did not affect milk composition. Treatments had no effect on change in body weight or body condition score or efficiency of milk production (kg of 3.5% fat-corrected milk/kg of DMI). Mean ruminal pH was not affected by treatment, but pH variance was decreased by vitreous compared with floury corn. Total volatile fatty acids and propionate concentrations in the rumen were increased by floury compared with vitreous corn but were not affected by fineness of grind. Effects of fineness of grind on yield of milk and milk components were greater than the effects of corn grain vitreousness.

Models to predict dry feed intake in Holstein calves to 4 months of age

Voluntary daily dry feed intake (DFI) in Holstein calves was predicted using 60,761 individual daily observations collected from 1,235 Holstein calves in 30 experiments from 4 research stations in the United States and Europe. Consumption of dry feed (calf starter and hay, kg/d or percent of body weight) was measured from 3 to 114 d of age. Linear models and 2- and 3-parameter nonlinear models were evaluated to predict DFI using age of calf, intake of milk replacer, ambient temperature, percent forage, and neutral detergent fiber concentration in ration dry matter (DM) as independent variables. The initial data set was randomly divided within study location into development (80% of all observations) and validation data sets, and initial screening was conducted using the development data set. Five nonlinear models and 3 linear models (candidate models) were identified and used in further model evaluation. Cross-validation studies (n = 20) with the validation data set were conducted by linear regression of DFI with predicted DFI as independent variable. Candidate models were subsequently evaluated with data from 12 published studies in 2 analyses. The exponential model that best predicted daily DFI in Holstein calves in original and external data sets was DFI (kg/d) = 1.3207 × e^{[(-5.3892 + 0.6376 × MEgap) × EXP(-0.0392 × Age)]} - 0.0013 × Temp + 0.0032 × NDFDM + 0.0026 × Age × MEgap - 0.3646 × PctForage [coefficient of determination (R²) = 0.92, concordance correlation coefficient (CCC) = 0.96, and mean square error of prediction (MSEP) = 0.10 kg]; where MEgap (Mcal/d) = difference of daily metabolizable energy (ME) requirement and ME intake from milk replacer; Age = age of calf (d) from 3 to 114, Temp = mean daily ambient temperature (°C), NDFDM = ration neutral detergent fiber (% DM); PctForage = percent forage in ration DM. The linear model that best predicted DFI was DFI (kg/d = -0.1349 + 0.0106 × Age + 0.1808 × MEgap + 0.0013 × Age × MEgap + 0.0001 × Temp + 0.00002 × Age × Temp (R² = 0.93, CCC = 0.96, and MSEP = 0.10 kg). When Temp and ration characteristics were not included, optimal models were 1.4362 × e^{[(-4.6646 + 0.5234 × MEgap) × EXP(-0.0361 × Age)]} + 0.0025 × Age × MEgap (R² = 0.92, CCC = 0.96, and MSEP = 0.11 kg) and -0.1344 + 0.0102 × Age + 0.1810 × MEgap + 0.0013 × Age × MEgap [R² = 0.93, CCC = 0.96, and MSEP = 0.10 kg]. Models of daily DFI may improve prediction of nutrient supply to young Holstein calves to approximately 4 mo of age, thereby increasing prediction of growth performance.

Effect of protein level and methionine supplementation on dairy cows during the transition period

Cows experience a significant negative protein balance during the first 30 d of lactation. Given the functional effects of AA on health, especially in challenging periods such as calving, higher levels of protein and specific AA in the diet may act to improve health and feed intake. The response of dairy cows to 3 protein supplementation strategies during the transition period and through the first 45 d in milk was evaluated. The final data set had 39 Holstein cows blocked based on parity (primiparous vs. multiparous) and expected calving and randomly assigned within each block to one of 3 dietary treatments: low protein (LP), high protein (HP), or high protein plus rumen-protected methionine (HPM). Treatments were offered from d -18 ± 5 to 45 d relative to parturition. Pre- and postpartum diets were formulated for high metabolizable protein (MP) supply from soybean meal, and HP and HPM provided higher MP balance than LP. Preplanned contrasts were LP versus HP+HPM and HP versus HPM. Significance was declared at P ≤ 0.05 and trends at 0.05 <P ≤ 0.10. Cows fed HP and HPM had greater fry matter intake (DMI) prepartum than LP (+2 kg/d), and there was a trend for greater DMI with HPM than with HP (+1.6 kg/d). Body weight and condition score before and after calving did not differ among treatments. High protein (HP and HPM) tended to increase milk yield during the first 45 d of lactation (+1.75 kg/d), increased milk lactose content and urea-N in milk and plasma, tended to increase blood BHB 14 d postpartum, and tended to reduce milk/DMI compared with LP. Blood concentrations of calcium at calving and of glucose, and nonesterified fatty acids pre- and postpartum did not differ. High protein induced lower concentration of plasma IL-1 at calving and lowered blood lymphocytes 21 d postpartum, suggestive of a reduced inflammatory status compared with LP. The concentrations of IL-10, tumor necrosis factor alpha, and other hemogram variables did not differ among treatments. Addition of rumen-protected methionine to the HP diet did not alter milk yield but increased fat and total solids concentrations. The rumen-protected methionine had no effect on blood metabolites and immunity markers, with the exception of increased pre-partum insulin concentrations. The data indicate that dairy cows around calving respond positively to an increase in the supply of MP and to rumen-protected methionine supplementation of the HP diet by increasing intake and improving immune status.

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.

The Rumen Bacterial Community in Dairy Cows Is Correlated to Production Traits During Freshening Period

The rumen microbiome plays a vital role in providing nutrition to the host animal, thereby influencing ruminant production. Despite its importance, it is not fully understood how variation in the ruminal bacteria community composition influences dry matter intake (DMI), milk yield and ruminal fermentative parameters in dairy cows, especially during freshening period. Here, we hypothesized that during early lactation, high DMI cows having a different ruminal microbiota than low DMI cows, and that this difference persists over time. To test this, we enrolled 65 fresh and determinzed their DMI using an auto-feed intake recording system. Fourteen days after calving, the 10 animals with the lowest (LFI) and the 10 animals with the highest (HFI)-average DMI were selected for further analysis. Rumen fluid was collected from these two cohorts at 1 (Fresh1d) and 14 days (Fresh14d) after calving and their ruminal microbiota were assessed using 16S rRNA sequencing. Volatile fatty acid (VFA) concentrations were also quantified. Comparison of the ruminal microbiotas between Fresh1d and Fresh14d showed that Fresh14d cows had a significantly higher relative abundance of VFA—producing microbes (P < 0.05), such as Prevotella_7 and Succinivibrionaceae_UCG-001. This was commensurate with the concentrations of acetate, propionate, butyrate, valerate and total VFAs, were also significantly (P < 0.05) increased in Fresh14d cows. We also found that the differences in the ruminal microbiota between LFI and HFI cows was limited, but DMI significantly altered (P < 0.05) the relative proportion of bacteria in the families Coriobacteriaceae, and Succinivibrionaceae. Furthermore, specific operational taxonomic units belonging to the Anaeroplasma was significantly (P < 0.05) correlated with DMI and milk yield. Taking together, our findings provide a framework for future studies of freshening period cow that seek to better understand the role of the ruminal microbiota during this critical period in the lactation cycle.

Changes in hematological, biochemical, and blood gases parameters in response to progressive inclusion of nitrate in the diet of Holstein calves

Background and Aim:

Nitrate (NO₃^-) reduces enteric methane emissions and could be a source of non-protein nitrogen in ruminant feeds. Nonetheless, it has a potential toxic effect that could compromise animal health and production. The purpose of this study was to determine the effects of progressive inclusion of NO₃^- in the diet on the hematological, biochemical, and blood gases parameters, in turn, the effects on feed intake and live weight gain (LWG) in Holstein calves.

Materials and Methods:

Eighteen Holstein heifers and steers (nine animals/treatment) were maintained in individual pens for 45 days. Animals were randomly allocated to either a control or nitrate diet (ND) (containing 15 g of NO₃^-/kg of dry matter [DM]). The biochemical parameters and blood gases were analyzed only in the NO₃^- group on days: -1, 1, 7, 13, 19, and 25 corresponding to 0, 20, 40, 60, 80, and 100% of the total inclusion of NO₃^- in the diet, respectively. In addition, DM intake (DMI) and LWG were evaluated among dietary treatments.

Results:

Feeding the ND did not influence DMI or LWG (p>0.05). Methemoglobin (MetHb) and deoxyhemoglobin increased according to the NO₃^- concentrations in the diet (p<0.05), while an opposite effect was observed for oxyhemoglobin and carboxyhemoglobin (p<0.05). Hematocrit levels decreased (p<0.05), while albumin, alanine aminotransferase, and gamma-glutamyl transpeptidase concentrations were not modified (p>0.05). However, glucose, urea, aspartate aminotransferase (AST), and retinol concentrations increased (p<0.05) according to the NO₃^- concentrations in the diet.

Conclusion:

This study confirmed that the progressive inclusion of 123 g of NO₃^-/animal/day in the diet could be safe without affecting DMI and LWG of Holstein calves. In turn, a dose-response effect of the MetHb, glucose, urea, AST, and retinol was observed, but these values did not exceed reference values. These results highlighted the importance of using a scheme of progressive inclusion of NO₃^- in the diet of calves to reduce the risks of NO₃^- toxicity.

Effects of Rumen-Protected Niacin on Dry Matter Intake, Milk Production, Apparent Total Tract Digestibility, and Faecal Bacterial Community in Multiparous Holstein Dairy Cow during the Postpartum Period

Extensive studies about rumen-protected niacin (RPN) supplementation on dairy cows in early-lactation have been done, but the effects of RPN on changes in dry matter intake (DMI), milk production, feed digestibility, and fecal bacterial community were conflicting. The aim of this study was to investigate them affected by RPN in postpartum cows. Multiparous Holstein dairy cows (n = 12, parity = 3.5 ± 0.5, body weights = 740 ± 28 kg) were divided into two groups supplemented with either 0 (CON) or 20 g/d RPN (RPN). Our results showed that RPN supplementation increased DMI and milk production of cows during the first three weeks after calving (p < 0.05). The concentrations of neuropeptide Y and orexin A were significantly higher in RPN group than that in the CON group during postpartum period (p < 0.05). The apparent total-tract digestibility of nutrients was similar between the CON and RPN groups at 2 weeks after calving (p > 0.05). The 16S rRNA gene sequencing analysis showed that RPN had no impact on the alpha and beta diversity, although 4 genera were changed in cow feces at 14 days after calving. Overall, 20 g/d RPN added to the diet could improve DMI and milk yield up to two weeks after calving with little influence on feed digestibility.

Association of subclinical hypocalcemia dynamics with dry matter intake, milk yield, and blood minerals during the periparturient period

Subclinical hypocalcemia (SCH) affects many high-producing dairy cows in the postpartum period. Recent work has shown that cows experiencing prolonged or delayed SCH are at increased risk for disease and produce less milk than cows experiencing a transient reduction in or normal concentrations of plasma Ca following parturition. Our objective was to determine the association between different postpartum SCH dynamics with pre- and postpartum dry matter intake (DMI), milk yield, and blood mineral concentrations. Data were retrospectively collected from multiparous Holstein cows (n = 78), and cows were classified into 1 of 4 SCH groups based on mean blood total Ca (tCa) concentrations at 1 and 4 d in milk (DIM): normocalcemic (NC; [tCa] >1.95 mmol/L at 1 DIM and >2.2 mmol/L at 4 DIM, n = 28); transient SCH (tSCH; [tCa] ≤1.95 mmol/L at 1 DIM and >2.2 mmol/L at 4 DIM, n = 27); delayed SCH (dSCH; [tCa] >1.95 mmol/L at 1 DIM and ≤2.2 mmol/L at 4 DIM, n = 6); and persistent SCH (pSCH; [tCa] ≤1.95 mmol at 1 DIM and ≤2.2 mmol/L at 4 DIM, n = 17). Linear mixed models were created to analyze the change in pre- and postpartum DMI, milk yield, and blood mineral concentrations over time as well as differences between SCH groups. Prepartum intake was similar between groups, but the NC and tSCH cows consumed more feed than the pSCH or dSCH cows during the first 3 wk of lactation. The tSCH cows produced more milk than the other 3 groups during the first 6 wk of lactation. Postpartum blood tCa and Mg were different between SCH groups and were highest in the NC cows and lowest in the pSCH cows. Our results suggest that the high level of DMI consumed by the NC and tSCH cows in the postpartum period supported an appropriate homeostatic response to the increased Ca demands of lactation, allowing for higher milk yield compared with their counterparts experiencing delayed or prolonged episodes of SCH.

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.

Selenium supplementation improves nutrient intake and digestibility, and mitigates CH4 emissions from sheep grazed on the mixed pasture of alfalfa and tall fescue

Low selenium (Se) in soil and forage can adversely affect on the quality of animal-derived foods, and hence on human health. Lambs grazed on mixed pastures of alfalfa (Medicago sativa) and tall fescue (Festuca arundinacea) were supplemented with five levels of Se [0, 3, 6, 9 and 12 µg/kg body weight (BW)]. The intake of dry matter (DM) and organic matter (OM) varied with the level of Se supplementation, with a peak at 6 µg Se per kg BW (p ≤ 0.05). Gross energy (GE) intake, digestive energy (DE) intake and metabolic energy (ME) intake were higher at 6 µg Se per kg BW than at other Se levels (p < 0.01); in addition, methane energy (CH₄ -E) output was lower at 6 µg Se per kg BW. Supplementation with Se significantly increased nitrogen (N) intake, faecal N and urine N, for which the peak values were 20.2 g N/, 5.62 g N/day and 7.92 g N/day, respectively, at 6 µg Se per kg BW. Se intake, blood Se, faecal Se, urine Se and retained Se were negatively correlated with forage crude protein (CP) content (p < 0.001) but were positively correlated with the content of neutral detergent fibre (NDF) (p < 0.001) and acid detergent fibre (ADF) (p < 0.001). Thus, we recommend the addition of 6 µg Se per kg BW to sheep grazed on pastures in regions with low soil Se.

Predicting Daily Dry Matter Intake Using Feed Intake of First Two Hours after Feeding in Mid and Late Lactation Dairy Cows with Fed Ration Three Times per Day

Simple Summary

It is difficult to obtain feed intake of dairy cows in experiments since all cows are raised in a free-stall barn in commercial dairy farms nowadays. Therefore, it is necessary to develop a simple, accurate, and reliable feed intake prediction model to replace direct measurement. In this study, we generated a forecasting model to predict daily dry matter intake (DMI) of dairy cows in mid and late lactation based on the feed intake of first 2 h after feeding (DMI-2h). The proposed prediction equation was: DMI (kg/day) = 8.499 + 0.2725 × DMI-2h (kg/day) + 0.2132 × Milk yield (kg/day) + 0.0095 × Body weight (kg/day) (R² = 0.46). Compared with NRC model (2001), our model shows higher accuracy and precision on predicting daily DMI of dairy cows with fed ration three times per day in mid and late lactation period. This prediction model could be used as an alternative approach for researchers who have difficulty in measuring DMI in dairy cows’ experiments.

Abstract

The objective of this study was to evaluate the feasibility of using the dry matter intake of first 2 h after feeding (DMI-2h), body weight (BW), and milk yield to estimate daily DMI in mid and late lactating dairy cows with fed ration three times per day. Our dataset included 2840 individual observations from 76 cows enrolled in two studies, of which 2259 observations served as development dataset (DDS) from 54 cows and 581 observations acted as the validation dataset (VDS) from 22 cows. The descriptive statistics of these variables were 26.0 ± 2.77 kg/day (mean ± standard deviation) of DMI, 14.9 ± 3.68 kg/day of DMI-2h, 35.0 ± 5.48 kg/day of milk yield, and 636 ± 82.6 kg/day of BW in DDS and 23.2 ± 4.72 kg/day of DMI, 12.6 ± 4.08 kg/day of DMI-2h, 30.4 ± 5.85 kg/day of milk yield, and 597 ± 63.7 kg/day of BW in VDS, respectively. A multiple regression analysis was conducted using the REG procedure of SAS to develop the forecasting models for DMI. The proposed prediction equation was: DMI (kg/day) = 8.499 + 0.2725 × DMI-2h (kg/day) + 0.2132 × Milk yield (kg/day) + 0.0095 × BW (kg/day) (R² = 0.46, mean bias = 0 kg/day, RMSPE = 1.26 kg/day). Moreover, when compared with the prediction equation for DMI in Nutrient Requirements of Dairy Cattle (2001) using the independent dataset (VDS), our proposed model shows higher R² (0.22 vs. 0.07) and smaller mean bias (−0.10 vs. 1.52 kg/day) and RMSPE (1.77 vs. 2.34 kg/day). Overall, we constructed a feasible forecasting model with better precision and accuracy in predicting daily DMI of dairy cows in mid and late lactation when fed ration three times per day.

Forage quality and beef cow preference is affected by wrap type of conventional and reduced-lignin alfalfa round bales stored outdoors

Storing hay outdoors can result in detrimental changes in forage quality. Additionally, alfalfa (Medicago sativa L.) cultivar may influence dry matter intake (DMI) and hay waste when feeding livestock. The objectives were to determine the effects of conventional or reduced-lignin alfalfa round bales stored outdoors and wrapped with plastic twine, net wrap, or B-Wrap on forage quality, beef cow preference, and hay waste. Round bales made from reduced-lignin (n = 12) or conventional (n = 12) alfalfa cultivars were baled and stored outdoors for 16 mo. Within each cultivar, four bale replicates were bound with plastic twine, net wrap, or B-Wrap. After storage, bales were fed in a switchback design with period confounded with alfalfa cultivar to 18 lactating Angus cows (Bos Taurus L.). The pairs had ad libitum access to three round-bale feeders where bales of each wrap type were placed for eight 48 h periods. Position of round bale wrap type was rotated according to a Latin Square arrangement. Bales were weighed and waste surrounding each feeder was collected at 24 and 48 h to calculate DMI and hay waste. Statistical significance was set at P < 0.05. Alfalfa cultivar did not impact any of the response variables (P > 0.05). At feeding, round bales wrapped in net wrap had greater (P < 0.015) moisture content (16.4%) compared with those wrapped with B-Wrap (12.8%). Neutral detergent fiber was lower (P = 0.03) in bales wrapped in B-Wrap (46%) compared with twine-tied bales (49%) while net wrapped bales were not different. Total digestible nutrients (P = 0.02), and relative feed value (P = 0.04) were lower in twine-tied bales compared with B-Wrap while net wrapped bales were not different. Twine (7.1 × 10⁶ colony forming units [CFU]/g) and net wrap (4.7 × 10⁶ CFU/g) bales had greater (P < 0.0001) mold counts than B-Wrap bales (4.8 × 10⁴ CFU/g), while concentrations of other forage components and yeast counts were not different among wrap types (P > 0.05). Total DMI, and DMI during the first 24 h, were greater (P ≤ 0.032) for B-Wrap bales compared to twine-tied bales indicating preference for hay wrapped in B-Wrap; net wrapped bales were not different. Dry matter intake in the first 24 h was negatively associated with the mold count (r = -0.52; P = 0.02), and hay waste was not affected by wrap type (P > 0.05). These results confirm that wrap type affected forage quality and mold counts, which in turn influenced beef cattle preference of round bales stored outdoors.

Liability to diseases and their relation to dry matter intake and energy balance in German Holstein and Fleckvieh dairy cows

Dairy cow efficiency is increasingly important for future breeding decisions. The efficiency is determined mostly by dry matter intake (DMI). Reducing DMI seems to increase efficiency if milk yield remains the same, but resulting negative energy balance (EB) may cause health problems, especially in early lactation. Objectives of this study were to examine relationships between DMI and liability to diseases. Therefore, cow effects for DMI and EB were correlated with cow effects for 4 disease categories throughout lactation. Disease categories were mastitis, claw and leg diseases, metabolic diseases, and all diseases. In addition, this study presents relative percentages of diseased cows per days in milk (DIM), repeatability, and cow effect correlations for disease categories across DIM. A total of 1,370 German Holstein (GH) and 287 Fleckvieh (FV) primiparous and multiparous dairy cows from 12 dairy research farms in Germany were observed over a period of 2 yr. Farm staff and veterinarians recorded health data. We modeled health and production data with threshold random regression models and linear random regression models. From DIM 2 to 305 average daily DMI was 22.1 kg/d in GH and 20.2 kg/d in FV. Average weekly EB was 2.8 MJ of NE_L/d in GH and 0.6 MJ of NE_L/d in FV. Most diseases occurred in the first 20 DIM. Multiparous cows were more susceptible to diseases than primiparous cows. Relative percentages of diseased cows were highest for claw and leg diseases, followed by metabolic diseases and mastitis. Repeatability of disease categories and production traits was moderate to high. Cow effect correlations for disease categories were higher for adjacent lactation stages than for more distant lactation stages. Pearson correlation coefficients between cow effects for DMI, as well as EB, and disease categories were estimated from DIM 2 to 305. Almost all correlations were negative in GH, especially in early lactation. In FV, the course of correlations was similar to GH, but correlations were mostly more negative in early lactation. For the first 20 DIM, correlations ranged from -0.31 to 0.00 in GH and from -0.42 to -0.01 in FV. The results illustrate that future breeding for dairy cow efficiency should focus on DMI and EB in early lactation to avoid health problems.

Effects of source and concentration of neutral detergent fiber from roughage in beef cattle diets on feed intake, ingestive behavior, and ruminal kinetics

The objectives of this research were to evaluate the effects of source and concentration of α-amylase-treated neutral detergent fiber (aNDF) from roughage on feed intake, ingestive behavior, and ruminal kinetics in beef cattle receiving high-concentrate diets. Six ruminally cannulated Nellore steers (408 ± 12 kg of body weight) were randomly assigned to a 6 × 6 Latin square design with six diets: 10% aNDF from corn silage (10CS); 20% aNDF from corn silage (20CS); or four diets containing 10% aNDF from corn silage and 10% aNDF from one of the following sources: sugarcane (SC), sugarcane bagasse (SCB), soybean hulls (SH), or low oil cottonseed hulls (LOCH). The parameters of passage and degradation kinetics were estimated based on a two-compartmental model with gamma- and exponential-distributed residence times. The nonlinear models were fitted by nonlinear least squares, and a linear mixed-effects model was fitted to all variables measured from the Latin square design that were related to intake, digestibility, digestion kinetic parameters, and residence times. Mean particle size (MPS) between roughage sources (CS, SCB, and SC) and coproducts (SH and LOCH) was affected (P < 0.05). Dry matter intake (DMI) was not affected (P > 0.05) by 20CS, SC, SH, or LOCH. Steers fed 20CS or LOCH diets had 16% and 20% greater DMI, respectively, (P < 0.05) than steers fed 10CS diet. Steers fed SCB consumed the least dry matter (DM). The SH and LOCH diets had lower MPS values (about 8.77 mm) in comparison to 20CS, SCB, and SC diets (about 13.08 mm) and, consequently, affected (P < 0.05) rumen content, ruminal in situ disappearance, nutrient digestibility, and solid fractional passage rate. Chewing time was affected (P < 0.05) by roughage sources and concentration. Lower values of distance travel inside the rumen (min/cm) were observed (P < 0.05) for the SCB and SC diets in comparison with any other diet. Except for SCB, there was no difference (P > 0.05) in rumen fill, among other treatments. Mean daily ruminal pH was not affected (P > 0.05) by 20CS, SCB, SC, and LOCH diets, and it ranged from 6.1 to 6.23. Total short-chain fatty acids concentration was affected (P < 0.05) by roughage source and concentration. Based on our results, we recommend that under Brazilian finishing diets, replacing roughage sources, except for SCB, based on aNDF concentration of the roughage in high-concentrate diets containing finely ground flint corn does not affect DMI.

Cistanche deserticola Addition Improves Growth, Digestibility, and Metabolism of Sheep Fed on Fresh Forage from Alfalfa/Tall Fescue Pasture

Simple Summary

Cistanche deserticola is a functional plant which mainly grows in desert and is parasitic on roots of the host species Haloxylon ammodendron. It has advantages in improving bodily intestinal peristalsis, immunity, anti-aging, anti-oxidation, and liver health and was supplied for sheep in this experiment to study the effects of C. deserticola addition on nutrients digestion, nitrogen balance, energy utilization, and methane production. The results revealed that C. deserticola has good utilization value in animal nutrition. The data are useful for further research on this natural plant additive to improve the health and productivity of the sheep fed on fresh forage from alfalfa/tall fescue pastures.

Abstract

This study is targeted at evaluating whether C. deserticola addition promotes digestion, nitrogen and energy use, and methane production of sheep fed on fresh forage from alfalfa/tall fescue pastures. The sheep feeding trial was conducted with four addition levels with C. deserticola powder, and a basal diet of fresh alfalfa (Medicago sativa) and tall fescue (Festuca arundinacea). Addition levels of 4% and 6% improved average body weight gain (BWG) by 215.71 and 142.86 g/d, and feed conversion ratio (FCR) by 0.20 and 0.14, respectively. Digestibility of dry matter (DM), organic matter (OM), neutral detergent fiber (NDF), and ether extract (EE) was 62.25%, 65.18%, 58.75%, and 47.25% under the addition level of 2%, which is greater than that in the control group. C. deserticola addition improved energy utilization efficiency, while addition levels of 2% and 4% increased nitrogen intake and deposited nitrogen. Overall, C. deserticola has the potential to improve growth performance, digestion of sheep, so it has suitability to be used as a feed additive.