Impact of dietary forage proportion and crossbreeding on feed efficiency and methane emissions in lactating dairy cows

Increasing forage proportion (FP) in the diets of dairy cows would reduce competition for human edible foods and reduce feed costs, particularly in low-input systems. However, increasing FP reduces productivity and may increases methane (CH4) emission parameters. This work aimed to investigate the impact of FP and breed on feed efficiency and CH4 emission parameters. Data from 32 individual experiments conducted at the Agri-Food and Biosciences Institute between 1992 and 2010 were utilised in this study resulting in data from 796 Holstein-Friesian (HF), 50 Norwegian Red (NR), 46 Jersey × HF (J × HF) and 16 NR × HF cows. Diets consisted of varying proportions of forage and concentrate dependent on the experimental protocols of each experiment. A linear mixed model was used to investigate the effect of low (LFP; 10% to 30%), medium (MFP; 30% to 59%), high (HFP; 60% to 87%) and pure (FOR; 100%) FP (dry matter [DM] basis) and breed on feed efficiency, and CH4 emission parameters and multivariate redundancy analysis identified associations between animal and dietary drivers on the same variables. Total dry matter intake (DMI) was higher for cows offered LFP (17.3 kg/d) and MFP (17.9 kg/d) compared to HFP (15.3 kg/d) and FOR (13.8 kg/d) (P < 0.001). Milk yield (P < 0.001), milk yield/DMI (P < 0.001), energy corrected milk (ECM)/DMI (P < 0.001) and milk energy/DMI (P < 0.001) were higher for LFP and MFP compared to HFP and FOR. Methane/DMI was higher for HFP (24.3 g/kg) compared to MFP (22.4 g/kg) (P < 0.001). Methane/milk yield (P < 0.001) or CH4/ECM (P < 0.001) was higher for HFP (22.5 or 21.6 g/kg) and FOR (27.0 or 25.8 g/kg) compared to MFP (19.1 or 17.9 g/kg). There were no differences between LFP and MFP or between HFP and FOR for milk yield, milk yield/DMI, ECM/DMI, milk energy/DMI, CH4/milk yield and CH4/ECM (P > 0.05). Differences existed between breeds for residual feed intake (P = 0.040), milk yield/DMI (P = 0.041) and CH4/DMI (P = 0.048) with multivariate redundancy analysis demonstrating negative correlations with efficiency and positive correlations with CH4/DMI and CH4/milk yield. Feeding concentrates at 70% to 90% of DMI (LFP group) would not result in any further benefits for productivity, feed efficiency or CH4 yield and intensity when compared to feeding 41% to 70% concentrates of DMI (MFP group). There may be opportunity to improve profitability for lower intensity farms with less concentrate input.

Efficiency of feed and energy use in primiparous and multiparous dairy cows fed contrasting dietary protein concentrations across lactation

Reducing dietary CP concentration can reduce feeding costs and N excretion in dairy production but may negatively impact productivity and efficiency. This study investigated the impact of reduced dietary CP concentration, across early, mid- and late-lactation stages in primiparous and multiparous lactating cows, on productivity, feed and energy use efficiency and CH4 emission parameters. Twenty-four Holstein-Friesian (12 primiparous, 12 multiparous) cows were allocated to three experimental total mixed rations containing 12.2, 15.1 or 18.1% CP (LCP, MCP and HCP, respectively; DM basis), in a continuous study across lactation (days 1-305). Digestibility and gas exchanges were measured in metabolism units and indirect open-circuit respiration calorimeter chambers during early, mid- and late-lactation. Data were analysed using a linear mixed model, with repeated measures, with CP concentration, stage of lactation, parity and their interactions as fixed effects, and a random effect of cow fitted as the subject and stage of lactation as the repeated measure. When compared with LCP treatment, MCP and HCP had higher DM intake (DMI) (+1.9 and +3.0 kg/d), milk yield (+5.5 and +7.7 kg/d), energy corrected milk yield (ECMY) (+5.0 and +7.1 kg/d), and feed efficiency (ECMY/DMI, +0.13 and +0.15 kg/kg; milk solids/DMI, +16 and +20 g/kg; milk energy output (EL)/DMI, +0.40 and 0.46 MJ/kg). Digestible energy intake (DEI)/gross energy intake (GEI), metabolisable energy intake (MEI)/GEI, MEI/DEI and milk energy output adjusted for zero energy balance (EL(0))/MEI were higher in HCP (+0.02, +0.03, +0.02, and +0.06 MJ/MJ) than LCP while there were no differences between LCP and MCP for DEI/GEI, or between MCP and HCP for MEI/DEI and EL(0)/MEI. Methane production per digestible DMI and ECMY were lower for MCP (-3.2 and -3.1 g/kg) and HCP (-3.8 and -3.4 g/kg), when compared with LCP. Methane energy per GEI, DEI and MEI were lower for the MCP (-0.007, -0.011 and -0.014 MJ/MJ) and HCP (-0.007, -0.014 and -0.017 MJ/MJ) than LCP. The significant interaction between CP concentration and stage of lactation on milk yield and ECMY showed that treatment differences (increased values in MCP or HCP vs LCP diets) reduced as lactation progressed. A diet containing 15.1% CP (DM basis) may be sufficient to maintain milk production and feed efficiency while reducing CH4 yield and intensity. However, regression analysis suggests that productivity may increase further between 15 and 18% CP (DM basis) but the response to dietary CP may depend on the stage of lactation.

Review: Improving residual feed intake modelling in the context of nutritional- and genetic studies for dairy cattle

The residual feed intake (RFI) model has recently gained popularity for ranking dairy cows for feed efficiency. The RFI model ranks the cows based on their expected feed intake compared to the observed feed intake, where a negative phenotype (eating less than expected) is favourable. Yet interpreting the biological implications of the regression coefficients derived from RFI models has proven challenging. In addition, multitrait modelling of RFI has been proposed as an alternative to the least square RFI in nutrition and genetic studies. To solve the challenge with the biological interpretation of RFI regression coefficients and suggest ways to improve the modelling of RFI, an interdisciplinary effort was required between nutritionists and geneticists. Therefore, this paper aimed to explore the challenges with the traditional least square RFI model and propose solutions to improve the modelling of RFI. In the traditional least square RFI model, one set of fixed effects is used to solve systematic effects (e.g., seasonal effects and age at calving) for traits with different means and variances. Thereby, measurement and model fitting errors can accumulate in the phenotype, resulting in undesirable effects. A multivariate RFI model will likely reduce this problem, as trait-specific fixed effects are used. In addition, regression coefficients for DM intake on milk energy tend to have more biologically meaningful estimates in multitrait RFI models, which indicates a confounding effect between the fixed effects and regression coefficients in the least square RFI model. However, defining precise expectations for regression coefficients from RFI models or sourcing for accurate feed norm coefficients seems difficult, especially if the coefficients are applied to a wide cattle population with varying diets or management systems, for example. To improve multitrait modelling of RFI, we suggest improving the modelling of changes in energy status. Furthermore, a novel method to derive the energy density of the diet and individual digestive efficiency is proposed. Digestive efficiency is defined as the part of the efficiency associated with digestive processes, which primarily reflects the conversion from gross energy to metabolisable energy. We show the model was insensitive to prior values of energy density in feed and that there was individual variation in digestive efficiency. The proposed method needs further development and validation. In summary, using multitrait RFI can improve the accuracy of the ranking of dairy cows' feed efficiency, consequently improving economic and environmental sustainability on dairy farms.

Effects of grass species and harvest date on cell wall components and feed efficiency of dairy cows

There is a balance between DM yield and feed value when choosing types of grasses on a farm depending on the acreages of farmland and types of ruminants to be fed. Therefore, optimisation of the harvest strategy for grass silage is important for profitable dairy farming. Tall fescue has high DM yield and can replace traditional grasses, such as timothy, in Northern Europe in a changing climate as it has been shown to be more drought tolerant. As differences in climate responses previously have been related to differences in cell wall structure between grass species and, consequently, in digestibility, it is highly relevant to compare these species at similar maturity stages and to investigate if a very early harvest date will diminish potential differences between the species. This study evaluated the effects of harvest date and forage species on the concentration of hydroxycinnamic acids in silages and its relationship to feed efficiency of dairy cows. Tall fescue and timothy were harvested at very early date on May 25 or at early date on May 31 in the spring growth cycle. Forty lactating dairy cows were used in a block design. Cows received 1 of 4 treatments: (1) tall fescue harvested at very early date, (2) timothy harvested at very early date, (3) tall fescue harvested at early date, and (4) timothy harvested at early date. Diets were formulated to have the same forage-to-concentrate ratio (49:51 on DM basis). Tall fescue silages showed greater concentrations of DM, ash, and CP than timothy silages. Grasses harvested at early date showed greater concentrations of NDF, ADL, and cell wall than grasses harvested at very early date. Tall fescue silages showed greater concentration of p-coumaric acid and lower in vitro organic matter digestibility (IVOMD) compared to timothy silages. Milk production and composition were not affected by treatments but cows fed tall fescue-based diets showed lower milk protein yield and greater milk urea nitrogen than when timothy-based diets were fed. Furthermore, cows receiving timothy-based diets showed greater feed efficiency compared to cows receiving tall fescue-based diets. Thus, the lower concentration of p-coumaric acid and the higher IVOMD was associated with greater feed efficiency of cows fed timothy-based diets compared to tall fescue-based diets.

A new protein requirement system for dairy cows

Accurate prediction of protein requirements for maintenance and lactation is needed to develop more profitable diets and reduce N loss and its environmental impact. A new factorial approach for accounting for net protein requirement for maintenance (NP_M) and metabolizable protein (MP) efficiency for lactation (EMP_L) was developed from a meta-analysis of 223 N balance trials. We defined NP_M as the sum of the endogenous protein fecal and urinary excretion and estimated it from the intercept of a nonlinear equation between N intake and combined total N fecal and urinary excretion. Our model had a strong goodness-of-fit to estimate NP_M (6.32 ± 0.15 g protein/kg metabolic body weight; n = 807 treatment means; r = 0.91). We calculated the EMP_L as a proportion of the N intake, minus N excreted in feces and urine, that was secreted in milk. A fixed-EMP_L value of 0.705 ± 0.020 was proposed. In a second independent data set, nonammonia-nonmicrobial-N and microbial-N ruminal outflows were measured, and the adequacy of the MP prediction (51 studies; n = 192 means treatments) was assessed. Our system based on the fixed-EMP_L model predicted the MP requirement for lactation and maintenance with higher accuracy than several North American and European dairy cattle nutrition models, including the INRA (2018) and NASEM (2021). Only the NRC (2001), CNCPS 6.5, and Feed into Milk (2004) models had similar accuracy to predict MP requirement. Our system may contribute to improve the prediction for MP requirements of maintenance and lactation. However, most refined predictive models of intestinal digestibility for rumen undegradable protein and microbial protein are still needed to reduce the evaluation biases in our model and external models for predicting the MP requirements of dairy cows.

Predicting nitrogen use efficiency, nitrogen loss and dry matter intake of individual dairy cows in late lactation by including mid-infrared spectra of milk samples

BACKGROUND

Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment. Meanwhile, the increasing demand for dairy products will result in more pollution if N losses are not controlled. Therefore, a more efficient, and environmentally friendly production system is needed, in which nitrogen use efficiency (NUE) of dairy cows plays a key role. To genetically improve NUE, extensively recorded and cost-effective proxies are essential, which can be obtained by including mid-infrared (MIR) spectra of milk in prediction models for NUE. This study aimed to develop and validate the best prediction model of NUE, nitrogen loss (NL) and dry matter intake (DMI) for individual dairy cows in China.

RESULTS

A total of 86 lactating Chinese Holstein cows were used in this study. After data editing, 704 records were obtained for calibration and validation. Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait. Results showed that the coefficient of determination (R²) of the best model in within-herd validation was 0.66 for NUE, 0.58 for NL and 0.63 for DMI. For external validation, reasonable prediction results were only observed for NUE, with R² ranging from 0.58 to 0.63, while the R² of the other two traits was below 0.50. The infrared waves from 973.54 to 988.46 cm^-1 and daily milk yield were the most important variables for prediction.

CONCLUSION

The results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations. The model of NUE could be used for the datasets that are similar to the calibration dataset. The prediction models for NL and 3-day moving average of DMI (DMI_a) generated lower accuracies in within-herd validation. Results also indicated that information of MIR spectra variables increased the predictive ability of models. Additionally, pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation. These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected.

Plasma proteins δ15N vs plasma urea as candidate biomarkers of between-animal variations of feed efficiency in beef cattle: Phenotypic and genetic evaluation

Identifying animals that are superior in terms of feed efficiency may improve the profitability and sustainability of the beef cattle sector. However, measuring feed efficiency is costly and time-consuming. Biomarkers should thus be explored and validated to predict between-animal variation of feed efficiency for both genetic selection and precision feeding. In this work, we aimed to assess and validate two previously identified biomarkers of nitrogen (N) use efficiency in ruminants, plasma urea concentrations and the ¹⁵N natural abundance in plasma proteins (plasma δ¹⁵N), to predict the between-animal variation in feed efficiency when animals were fed two contrasted diets (high-starch vs high-fibre diets). We used an experimental network design with a total of 588 young bulls tested for feed efficiency through two different traits (feed conversion efficiency [FCE] and residual feed intake [RFI]) during at least 6 months in 12 cohorts (farm × period combination). Animals reared in the same cohort, receiving the same diet and housed in the same pen, were considered as a contemporary group (CG). To analyse between-animal variations and explore relationships between biomarkers and feed efficiency, two statistical approaches, based either on mixed-effect models or regressions from residuals, were conducted to remove the between-CG variability. Between-animal variation of plasma δ¹⁵N was significantly correlated with feed efficiency measured through the two criteria traits and regardless of the statistical approach. Conversely, plasma urea was not correlated to FCE and showed only a weak, although significant, correlation with RFI. The response of plasma δ¹⁵N to FCE variations was higher when animals were fed a high-starch compared to a high-fibre diet. In addition, we identified two dietary factors, the metabolisable protein to net energy ratio and the rumen protein balance that influenced the relation between plasma δ¹⁵N and FCE variations. Concerning the genetic evaluation, and despite the moderate heritability of the two biomarkers (0.28), the size of our experimental setup was insufficient to detect significant genetic correlations between feed efficiency and the biomarkers. However, we validated the potential of plasma δ¹⁵N to phenotypically discriminate two animals reared in identical conditions in terms of feed efficiency as long as they differ by at least 0.049 g/g for FCE and 1.67 kg/d for RFI. Altogether, the study showed phenotypic, but non-genetic, relationships between plasma proteins δ¹⁵N and feed efficiency that varied according to the efficiency index and the diet utilised.

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

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

Invited review: Disentangling residual feed intake-Insights and approaches to make it more fit for purpose in the modern context

Residual feed intake (RFI) is an increasingly used trait to analyze feed efficiency in livestock, and in some sectors such as dairy cattle, it is one of the most frequently used traits. Although the principle for calculating RFI is always the same (i.e., using the residual of a regression of intake on performance predictors), a wide range of models are found in the literature, with different predictors, different ways of considering intake, and more recently, different statistical approaches. Consequently, the results are not easily comparable from one study to another as they reflect different biological variabilities, and the relationship between the residual (i.e., RFI) and the underlying true efficiency also differs. In this review, the components of the RFI equation are explored with respect to the underlying biological processes. The aim of this decomposition is to provide a better understanding of which of the processes in this complex trait contribute significantly to the individual variability in efficiency. The intricacies associated with the residual term, as well as the energy sinks and the intake term, are broken down and discussed. Based on this exploration as well as on some recent literature, new forms of the RFI equation are proposed to better separate the efficiency terms from errors and inaccuracies. The review also considers the time period of measurement of RFI. This is a key consideration for the accuracy of the RFI estimation itself, and also for understanding the relationships between short-term efficiency, animal resilience, and long-term efficiency. As livestock production moves toward sustainable efficiency, these considerations are increasingly important to bring to bear in RFI estimations.

Estimation of genetic parameters for predicted nitrogen use efficiency and losses in early lactation of Holstein cows

The objective of this study was to estimate genetic parameters of predicted N use efficiency (PNUE) and N losses (PNL) as proxies of N use and loss for Holstein cows. Furthermore, we have assessed approximate genetic correlations between PNUE, PNL, and dairy production, health, longevity, and conformation traits. These traits are considered important in many countries and are currently evaluated by the International Bull Evaluation Service (Interbull). The values of PNUE and PNL were obtained by using the combined milk mid-infrared (MIR) spectrum, parity, and milk yield-based prediction equations on test-day MIR records with days in milk (DIM) between 5 and 50 d. After editing, the final data set comprised 46,163 records of 21,462 cows from 154 farms in 5 countries. Each trait was divided into primiparous and multiparous (including second to fifth parity) groups. Genetic parameters and breeding values were estimated by using a multitrait (2-trait, 2-parity classes) repeatability model. Herd-year-season of calving, DIM, age of calving, and parity were used as fixed effects. Random effects were defined as parity (within-parity permanent environment), nongenetic cow (across-parity permanent environment), additive genetic animal, and residual effects. The estimated heritability of PNUE and PNL in the first and later parity were 0.13, 0.12, 0.14, and 0.13, and the repeatability values were 0.49, 0.40, 0.55, and 0.43, respectively. The estimated approximate genetic correlations between PNUE and PNL were negative and high (from -0.89 to -0.53), whereas the phenotypic correlations were also negative but relatively low (from -0.45 to -0.11). At a level of reliability of more than 0.30 for all novel traits, a total of 504 bulls born after 1995 had also publishable Interbull multiple-trait across-country estimated breeding values (EBV). The approximate genetic correlations between PNUE and the other 30 traits of interest, estimated as corrected correlations between EBV of bulls, ranged from -0.46 (udder depth) to 0.47 (milk yield). Obtained results showed the complex genetic relationship between efficiency, production, and other traits: for instance, more efficient cows seem to give more milk, which is linked to deeper udders, but seem to have lower health, fertility, and longevity. Additionally, the approximate genetic correlations between PNL, lower values representing less loss of N, and the 30 other traits, were from -0.32 (angularity) to 0.57 (direct calving ease). Even if further research is needed, our results provided preliminary evidence that the PNUE and PNL traits used as proxies could be included in genetic improvement programs in Holstein cows and could help their management.

Looking for high-production and sustainable diets for lactating cows: A survey in Italy

The aim of the present study was to evaluate, through a survey conducted on commercial farms, the global warming potential (GWP) of different lactating cow total mixed rations (TMR) and to identify the best dietary strategies to increase feed efficiency (FE) and reduce enteric CH4 emission. A total of 171 dairy herds were selected: data about dry matter intake (DMI), lactating cow TMR composition, and milk production and composition were provided by farmers. Diet GWP (kg of CO2 equivalents; CO2eq) was calculated as sum of GWP (kg of CO2eq) of each included ingredient, considering inputs needed at field level, feed processing, and transport. For soybean solvent meal, land use change was included in the assessment. Enteric methane production (g/d) was estimated [using the equation CH4 (g/d) = 2.54 + 19.14 × DMI] to calculate CH4 emission for kilograms of fat- and protein-corrected milk (FPCM). The data set was analyzed by generalized linear model and logistic analysis using SAS 9.4 (SAS Institute Inc., Cary, NC). The frequency distribution showed wide variation among farms for GWP (kg of CO2eq) of TMR: approximately 25% of the surveyed farms showed a diet GWP of 15 kg of CO2eq, 20% showed a GWP of 13 kg of CO2eq, and 16.7% showed a GWP of 17 kg of CO2eq. The variation among farms was due to the feedstuffs used. Among feedstuffs, soybean meal (SBM) had the highest correlation with the GWP of the TMR as shown by the following equation: TMR GWP (kg of CO2eq) = 2.49 × kg of SBM + 6.9 (R2 = 0.547). Moreover, diets with inclusion of SBM >15% of dry matter (DM) did not result in higher milk production than diets with a lower inclusion of SBM (≤15%). Average daily milk production of cows was 29.8 [standard deviation (SD) 4.83] kg with fat and protein contents of 3.86% (SD 0.22) and 3.40% (SD 0.14), respectively. The average DMI (kg/d) of lactating cows was 22.3 (SD 2.23). Logistic analysis demonstrated that corn silage ≤30% of diet DM was associated with higher FE. Almost 50% of farms had an average value of 15.0 g of CH4/kg of FPCM and about 30% of farms had an average of 12.5 g of CH4/kg of FPCM. The results demonstrated that lower enteric CH4 production was related to inclusion (% of diet DM) of ≤12% alfalfa hay and >30% corn silage. Diets with >34% neutral detergent fiber had higher CH4 production (>14.0 g/kg of FPCM) than those with lower neutral detergent fiber content. In contrast, lower enteric CH4 production (≤14.0 g/kg of FPCM) was related to diets characterized by net energy of lactation (NEL) >1.61 Mcal/kg and >4% ether extract. The variability in TMR GWP shows significant potential for reducing the GWP of a diet through choice and inclusion levels of ingredients (mainly SBM) and the possibility of decreasing methane enteric emission associated with milk production on a commercial scale.

Pre-Grazing Herbage Mass Affects Grazing Behavior, Herbage Disappearance, and the Residual Nutritive Value of a Pasture during the First Grazing Session

Simple Summary

The progressive defoliation carried out by dairy cows during the grazing-down process affects the characteristics of the pasture, the dry matter intake and the productive performance of the animals, particularly during the first hours of grazing. This is especially relevant when increasing the efficiency in pasture-based dairy systems. Two pre-grazing herbage masses (high and medium herbage masses) were used to evaluate the process of defoliation carried out by dairy cows during the first hours after the beginning of grazing and its effects on the pasture and animals. The pre-grazing herbage mass affected the ingestive behavior of dairy cows, which influenced the productive performance, and the morphological characteristics and nutritive value of the pasture. It is concluded that pre-grazing herbage mass affects the grazing process carried out by dairy cows during the first hours after the allocation of a new grazing area, modifying the eating pattern of the dairy cows. The results of our study allow highlighting the importance of grazing management in pasture-based dairy systems.

Abstract

During the first hours after the allocation of a grazing strip (first grazing session, GS), dairy cows eat most of the daily dry matter (DM) available. There are few studies that analyze how the grazing-down process changes the characteristics of the pasture during the first GS. The objective of this study was to evaluate the effect of two pre-grazing herbage masses (HM; medium herbage mass (MHM) and high herbage mass (HHM) on the DM disappearance, grazing behavior of dairy cows, and the residual nutritive value of a pasture during the first GS. Two groups of twelve dairy cows were used to evaluate the grazing-down process, during a period of 62 days. The pre-grazing HM modified the bite rate, bite mass, and dry matter intake during the first GS. The pre-grazing HM affected the process of herbage disappearance of the pasture, especially during the first 60 min of the GS. The nutrient selection differential for acid detergent fiber was greater for HHM compared with MHM (0.93 vs. 0.86). In conclusion, pre-grazing HM affects the structural characteristics and the residual nutritive value of the pasture. The grazing process in the first GS was modified by the HM, affecting the defoliation and the DM disappearance rate of the pasture.

Nitrogen partitioning and microbial protein synthesis in lactating dairy cows with different phenotypic residual feed intake

Background

Residual feed intake (RFI) is an inheritable measure of feed efficiency that is independent on level of production. However, physiological and metabolic mechanisms underlying divergent RFI are not fully elucidated. This study was conducted to investigate dietary nitrogen (N) partitioning and microbial protein synthesis in lactating dairy cows divergent in phenotypic RFI.

Results

Thirty Holstein dairy cows (milk yield = 35.3 ± 4.71 kg/d; milk protein yield = 1.18 ± 0.13 kg/d; mean ± standard deviation) were selected for the experiment to derive RFI. After the RFI measurement period of 50 d, the 10 lowest RFI cows and 8 highest RFI cows were selected. The low RFI cows had lower dry matter intake (DMI, P < 0.05) than the high RFI cows, but they produced similar energy-corrected milk. The ratios of milk to DMI (1.41 vs. 1.24, P < 0.01) and energy-corrected milk to DMI (1.48 vs. 1.36, P < 0.01) were greater in low RFI cows than those in the high RFI cows. The low RFI cows had lower milk urea nitrogen than that in the high RFI cows (P = 0.05). Apparent digestibility of nutrients did not differ between two groups (P > 0.10). Compared with high RFI animals, the low RFI cows had a lower retention of N (5.72 vs. 51.4 g/d, P < 0.05) and a higher partition of feed N to milk N (29.7% vs. 26.5%, P < 0.05).

Conclusions

The results suggest that differences in N partition, synthesis of microbial protein, and utilization of metabolizable protein could be part of the mechanisms associated with variance in the RFI.

Effect of experimental design on responses to 2 concentrations of metabolizable protein in multiparous dairy cows

The objective of this research was to characterize the implications of changing between diets formulated to be adequate (ADMP) or low (LOMP) in metabolizable protein in a Latin square (LSq) design or of feeding the same diets continuously in a randomized complete block experimental design (RCBD). Fifty-four multiparous early-lactation cows (initial average ± SD; parity 2.8 ± 0.9, 85.8 ± 31 d in milk, 715 ± 63 kg of body weight, 29.1 ± 2.7 kg of dry matter intake/d, and 57.7 ± 5.7 kg of milk yield/d) were blocked by parity and days in milk and were then randomly assigned to experimental design, with 16 cows assigned to LSq and 38 cows assigned to RCBD. Cows within blocks in LSq were randomly assigned to sequence in a 4-sequence, 4-period, 2-treatment LSq balanced for the effects of previous treatment carryover. Cows within blocks in RCBD were randomly assigned to dietary treatment, which was fed over the same four 28-d periods as the cows in LSq. Treatment diets were formulated to be similar in composition with the exception of exchanging an equal quantity of expeller soybean meal from ADMP (16.5% crude protein; 28.4% ash-free, amylase-treated neutral detergent fiber organic matter) for soybean hulls in LOMP (14.6% crude protein; 31.1% ash-free, amylase-treated neutral detergent fiber organic matter). Cows were individually fed treatment diets in a tiestall barn once daily for ad libitum consumption, milked 3 times daily, and administered recombinant bovine somatotropin every 14 d. Milk yield and feed offered and refused were measured daily; BW was recorded on 2 consecutive days each week; milk composition was measured at 6 consecutive milkings each week; and spot samples of feces, urine, and blood were collected during the last week of each period and a covariate period. Experimental designs were analyzed separately using results from wk 4 of each period with mixed effects modeling. Dry matter intake and milk fat yield were not affected by diet in either design, whereas milk and protein yields were greater for cows fed ADMP in both designs. Milk fat and protein percentage responses and milk energy output inferences were different between designs. Milk fat yield and percentage responses were affected by previous treatment carryover in LSq. Metabolic and digestibility inferences were very similar between designs. Under the conditions of this experiment, inferences on N metabolism and the majority of production measurements were not affected by experimental design, with the principal exceptions of milk fat and protein percentage and milk energy output.

Characteristics of boli formed by dairy cows upon ingestion of fresh ryegrass, lucerne or chicory

This study examined the comminution of fresh herbage, subsequent nutrient release, and the characteristics of swallowed boli from three physically and chemically contrasting forages during ingestive mastication by dairy cows. The extent and pattern of nutrient release will determine their availability to rumen microflora, and potentially influence their efficiency of use. The forages evaluated were perennial ryegrass (ryegrass, Lolium perenne L., cv Alto AR37), lucerne (Medicago sativa L., cv Torlesse) and chicory (Cichorium intybus L., cv Choice). Experimental design was a 3×3 cross-over with three forages and three consecutive 1-day measurement periods, conducted twice. Six non-lactating, pregnant, multiparous Holstein-Friesian×Jersey cows (Bos taurus) were used, with the first cross-over applied to three mature (10.1±0.61 years old; BW 631±64 kg) cows, and the second to three young (4.8±0.02 years; BW 505±19 kg) cows. Fresh cut forage was offered to the cows following partial rumen evacuation. Swallowed boli were collected directly at the cardia at the commencement, middle and end of the first feeding bout of the first meal of the day. Forage species did not affect the fresh weight of ingested boli (mean 169 g, P=0.605) but the proportion of saliva in boli varied between forage. Boli of chicory contained the greatest amount of herbage material and least amount of saliva, whereas ryegrass boli were the opposite. Boli fresh weight tended to increase as time in the meal progressed, but the age of the cow was not shown to affect any boli characteristics or nutrient release. Particle size reduction was affected by forage, with 31%, 38% and 35% of chicory, lucerne and ryegrass herbage reduced to <2 mm. There was little evidence of relationship between comminution and any physical or chemical characteristic of the forage, except in ryegrass where extent of comminution was moderately correlated with herbage strength. Proportional release of herbage soluble carbohydrate exceeded that of N during mastication. Differences in loss of N were moderately correlated with the amount of N in the herbage (R 2=0.53) but herbage comminution was not strongly correlated with release of either N or carbohydrate. These findings illustrate the complex animal×forage interactions that occur during mastication, and that it is not possible to infer nutrient loss from herbage based on herbage characteristics as the driver for this differ between species.

Biological efficiency profiles over the lactation period in multiparous high-producing dairy cows under divergent production systems

Abstract. The study examined variation in energetic-efficiency profiles among production systems and cow parities. Further, the correlation between cows' body condition score (BCS) and energetic efficiency over the lactation period was determined. Biological efficiency was defined using four measures of production efficiency and two measures of energetic efficiency. The following were measures of energetic efficiency: the net energy intake required to produce 1 kg milk solids (NEin / MS) and the proportion of net energy utilized for milk production after accounting for maintenance (NElact / (NEin- NEm)). Seven years of data were gathered from a total of 595 Holstein-Friesian cows in a long-term genetics × feeding–management interaction project. Two feeding regimes – High forage (HF) and Low forage (LF) – were applied to each of two genetic lines (Control (C) and Select (S)), giving four dairy production systems: Low Forage Control (LFC), Low Forage Select (LFS), High Forage Control (HFC) and High Forage Select (HFS). LFS was the most efficient system using all measures. Variation in the rate and scale of change at which the cows' energetic efficiency declined over lactation was significantly different (P < 0.001) amongst different dairy production systems and parities. Loss of efficiency over the lactation period was lower in Select cows than in Control cows and increased with parity. The trajectory of energetic-efficiency profiles was influenced by cow genetic line, and yet the level of the efficiency profile was influenced by the feeding regime. There was a strong relationship between BCS and energetic efficiency. Continued in situ monitoring of cows' biological efficiency may enable optimal management of dairy systems.

Prediction of nutrient digestibility and energy concentrations in fresh grass using nutrient composition

Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.

Diet-animal fractionation of nitrogen stable isotopes reflects the efficiency of nitrogen assimilation in ruminants

The natural abundance of ¹⁵N in animal proteins (δ¹⁵Nanimal) is greater than that in the diet consumed by the animals (δ¹⁵Ndiet), with a discrimination factor (Δ¹⁵N = δ¹⁵Nanimal - δ¹⁵Ndiet) that is known to vary according to nutritional conditions. The objectives of the present study were to test the hypothesis that Δ¹⁵N variations depend on the efficiency of nitrogen utilisation (ENU) in growing beef cattle, and to identify some of the physiological mechanisms responsible for this N isotopic fractionation in ruminants. Thus, we performed the regression of the Δ¹⁵N of plasma proteins obtained from thirty-five finishing beef cattle fed standard and non-conventional diets against different feed efficiency indices, including ENU. We also performed the regression of the Δ¹⁵N of different ruminant N pools (plasma and milk proteins, urine and faeces) against different splanchnic N fluxes obtained from multi-catheterised lactating dairy cows. The Δ¹⁵N of plasma proteins was negatively correlated with feed efficiency indices in beef cattle, especially ENU (body protein gain/N intake) and efficiency of metabolisable protein (MP) utilisation (body protein gain/MP intake). Although Δ¹⁵N obtained from different N pools in dairy cows were all negatively correlated with ENU, the highest correlation was found when Δ¹⁵N was calculated from plasma proteins. Δ¹⁵N showed no correlation with urea-N recycling or rumen NH₃ absorption, but exhibited a strong correlation with liver urea synthesis and splanchnic amino acid metabolism, which points to a dominant role of splanchnic tissues in the present N isotopic fractionation study.