Alternatives to Linear Analysis of Energy Balance Data from Lactating Dairy Cows

Derivation of the maintenance energy requirements and efficiency of metabolizable energy utilization for dry and lactating Jersey cows

Maintenance energy is the energy required to conserve the state of an animal when no work is completed. Dietary energy must be supplied to meet maintenance requirements before milk can be produced. The objectives of the current experiment were to quantify the maintenance energy requirement of Jersey cows when lactating or dry. Energetic measures were collected on 8 Jersey cows and evaluated across 3 physiological phases and nutritional planes: lactation, dry cows fed at maintenance, and fasted dry cows. Through total collection of feces and urine as well as using headbox-style indirect calorimeters, energy balance and heat production data were measured across all phases. Lactation data were collected across four 28-d periods. Data for cows fed at maintenance were collected after 14 d and fasting heat production was measured during the last 24 h of a 96-h fast. Net energy for maintenance (NE_M) requirements, and the efficiency of converting metabolizable energy (ME) into net energy were compared between lactating and dry (maintenance or fasting phase) cows. Heat production of dry cows fed at maintenance, which represents ME for maintenance, was 0.146 ± 0.0087 Mcal per unit of metabolic body weight (BW^0.75, MBW). Fasting heat production, which represents NE_M, was 0.102 ± 0.0071 Mcal/MBW. Energy balance was calculated as tissue energy plus milk energy. When estimated via regressing energy balance on ME intake, NE_M was not different between dry and lactating cows (0.120 ± 0.32 vs. 0.103 ± 0.0052 Mcal/MBW). However, the slope of the regression of energy balance on ME intake was greater for dry compared with lactating cows (0.714 ± 0.046 vs. 0.685 ± 0.010) when evaluated with a fixed intercept. This suggests that dry cows were more efficient at converting ME into net energy and that the efficiency of utilizing ME for maintenance may be greater than for lactation. Our measurements of NE_M and the slope of ME on energy balance were greater than the value used by the National Research Council (2001), which are 0.080 Mcal/MBW for NE_M and approximately 0.64 for the slope. Results of this study suggest that NE_M and the efficiency of converting ME into NE_M of modern lactating Jersey cows are similar to recent measurements on modern Holstein cows and greater than previous measurements.

The use of an upgraded GreenFeed system and milk fatty acids to estimate energy balance in early-lactation cows

Measurements of energy balance (EB) require the use of respiration chambers, which are quite expensive and laborious. The GreenFeed (GF) system (C-Lock Inc.) has been developed to offer a less expensive, user friendly alternative. In this study, we used the GF system to estimate the EB of cows in early lactation and compared it with EB predicted from energy requirements for dairy cows in the Finnish feeding standards. We also evaluated the association between milk fatty acids and the GF estimated EB. The cows were fed the same grass silage but supplemented with either cereal grain or fibrous by-product concentrate. Cows were followed from 1 to 18 wk of lactation, and measurements of energy metabolism variables were taken. Data were subjected to ANOVA using the mixed model procedure of SAS (SAS Institute Inc.). The repeatability estimates of the gaseous exchanges from the GF were moderate to high, presenting an opportunity to use it for indirect calorimetry in EB estimates. Energy metabolism variables were not different between cows fed different concentrates. However, cows fed the grain concentrate produced more methane (24.0 MJ/d or 62.9 kJ/MJ of gross energy) from increased digestibility than cows fed the by-product concentrate (21.3 MJ/d or 56.5 kJ/MJ of gross energy). Nitrogen metabolism was also not different between the diets. Milk long-chain fatty acids displayed an inverse time course with EB and de novo fatty acids. There was good concordance (0.85) between EB predicted using energy requirements derived from the Finnish feed table and EB estimated by the GF system. In conclusion, the GF can accurately estimate EB in early-lactating dairy cows. However, more data are needed to further validate the system for a wide range of dietary conditions.

Residual carbon dioxide as an index of feed efficiency in lactating dairy cows

High feed costs make feed conversion efficiency a desirable target for genetic improvement. Residual feed intake (RFI), calculated as the difference between observed and predicted intake, is a commonly used estimate of feed efficiency. However, determination of feed efficiency in dairy herds is challenging due to difficulties in measuring feed intake of individual animals reliably. Using residual CO₂ (RCO₂) production as an estimate of feed efficiency would allow ranking the cows according to feed efficiency, provided that CO₂ production is closely related to heat production and feed intake. The objective of this study was to evaluate the potential of RCO₂ as an index of feed efficiency using data from respiration calorimetry studies (289 cow per period observations). Heat production was precisely predicted from CO₂ production [root mean square error (RMSE)] adjusted for random effects was 1.5% of observed mean]. Dry matter intake (DMI) was better predicted from energy-corrected milk (ECM) yield and CO₂ production than from ECM yield and body weight in the model (adjusted RSME = 0.92 vs. 1.39 kg/d). Residual CO₂ production estimated as the difference between actual CO₂ production and that predicted from ECM yield, metabolic body weight was closely related to RFI (adjusted RMSE = 0.42) that was calculated as the difference between actual DMI and that predicted from ECM, metabolic body weight, and energy balance (EB). When the cows were categorized in 3 groups of equal sizes on the basis of RCO₂ (low, medium, and high), low RCO₂ cows had lower DMI, RFI, methane production and intensity (g/kg ECM), and heat production, but higher efficiency of metabolizable energy utilization for lactation than high RCO₂ cows. When RFI was predicted from RCO₂, the residuals (observed - predicted) were negatively related to EB and digestibility. Predicting RFI with a 2-variable model based on RCO₂ and digestibility, adjusted RMSE decreased to 0.23 kg/d, and residuals were not significantly related to EB. The cows in low RCO₂ group had a higher energy digestibility than the cows in the high RCO₂ group, and differences in EB were observed between the groups. Error of the model predicting residual ECM production from RCO₂ was 1.41 kg/d. The residuals were positively related to ECM yield and energy digestibility. Predicting residual ECM from RCO₂ and ECM yield decreased adjusted RMSE to 1.07 kg/d, and further to 0.78 kg/d when digestibility was included in the 2-variable model. It is concluded that RCO₂ has a potential for ranking individual cows based on feed efficiency.

Maintenance energy requirement and efficiency of utilisation of metabolisable energy for milk production of Bos taurus × Bos indicus crossbred tropical dairy cows: a meta-analysis

ContextDairy consumption has the ability to provide nutrient dense food in low-income countries. However, cows in the tropics may not be able to reach their full potential due to poor nutrition. In tropical regions, milk is mostly produced by Bos taurus × Bos indicus crossbred cattle for which no nutrient requirement tables have been fully developed. Although many novel feeds and feed additives have been tested, nutrient requirements specifically targeting energy and protein for these livestock need to be estimated accurately for milk production to increase sustainably. AimsTo determine the net energy for lactation (NEL) requirement for maintenance and efficiency of utilisation of metabolisable energy intake (MEI) for milk production (kL) of Bos taurus × Bos indicus crossbred dairy cows in the tropics. MethodsA meta-analysis using 141 observations from 38 independent studies in tropical regions with crossbred dairy cows was conducted. The energy produced in milk corrected for zero energy balance (EL0) was regressed by MEI including other covariates. This meta-regression analysis was conducted by frequentist inference via optimisation in RStan. Key resultsThe best-fit model contained only MEI as a covariate. This model predicted a net energy for lactation value at maintenance of 0.323 MJ/kg BW0.75.day (s.e. = 0.0004) with variations for each specific study. The efficiency with which MEI is used for milk production was estimated to be 0.554 (s.e. = 0.00008), which was common for all studies. ConclusionThe key energy parameters estimated in this study should replace commonly used values derived from Bos taurus breeds when formulating diets for crossbred tropical cattle. ImplicationsNutritional requirement tables need to be estimated specifically for Bos taurus × Bos indicus crossbred dairy cows as their requirements differ from Western breeds. Using appropriate nutritional requirements of crossbred cattle would lead to better nutrition and increased production as determined by their genetic merit.

Short communication: Variation in feed efficiency hampers use of carbon dioxide as a tracer gas in measuring methane emissions in on-farm conditions

Breeding cows for low CH₄ emissions requires that the trait is variable and that it can be recorded with low cost from an adequate number of individuals and with high precision, but not necessarily with high accuracy if the trait is measured with high repeatability. The CH₄:CO₂ ratio in expired breath is a trait often used as a tracer with the production of CO₂ predicted from body weight (BW), energy-corrected milk yield, and days of pregnancy. This approach assumes that efficiency of energy utilization for maintenance and production is constant. Data (307 cow-period observations) from 2 locations using the same setup for measuring CH₄ and CO₂ in respiration chambers were compiled, and observed production of CH₄ and CO₂ was compared with the equivalent predicted production using 2 different approaches. Carbon dioxide production was predicted using a previously reported model based on metabolic BW and energy-corrected milk production and a currently developed model based on energy requirements and the relationship between observed CO₂ and heat production (models 1 and 2, respectively). Animals used were categorized (low, medium, and high efficiency) according to (1) residual feed intake and (2) residual milk production. Model 1 underestimated CH₄ production by 15%, whereas model 2 overestimated CH₄ by 1.4% for the whole database. Model 1 underestimated CO₂ production by 2.8 and 0.9 kg/d for low- and high-efficiency cows, respectively, whereas model 2 underestimated CO₂ production by 0.9 kg/d for low-efficient animals but overestimated it by 1.2 kg/d for high-efficiency cows. Efficient cows produce less heat, and consequently CO₂, per unit of metabolic body weight and energy-corrected milk than inefficient cows, challenging the use of CO₂ as a tracer gas. Because of biased estimates of CO₂ production, the models overestimated CH₄ production of high-efficiency cows by, on average, 17% relative to low-efficiency cows, respectively. Selecting low CH₄-emitting cows using a CO₂ tracer method can therefore favor inefficient cows over efficient cows.

The effects of energy metabolism variables on feed efficiency in respiration chamber studies with lactating dairy cows

The objective of the present study was to investigate factors related to variation in feed efficiency (FE) among cows. Data included 841 cow/period observations from 31 energy metabolism studies assembled across 3 research stations. The cows were categorized into low-, medium-, and high-FE groups according to residual feed intake (RFI), residual energy-corrected milk (RECM), and feed conversion efficiency (FCE). Mixed model regression was conducted to identify differences among the efficiency groups in animal and energy metabolism traits. Partial regression coefficients of both RFI and RECM agreed with published energy requirements more closely than cofficients derived from production experiments. Within RFI groups, efficient (Low-RFI) cows ate less, had a higher digestibility, produced less methane (CH₄) and heat, and had a higher efficiency of metabolizable energy (ME) utilization for milk production. High-RECM (most efficient) cows produced 6.0 kg/d more of energy-corrected milk (ECM) than their Low-RECM (least efficient) contemporaries at the same feed intake. They had a higher digestibility, produced less CH₄ and heat, and had a higher efficiency of ME utilization for milk production. The contributions of improved digestibility, reduced CH₄, and reduced urinary energy losses to increased ME intake at the same feed intake were 84, 12, and 4%, respectively. For both RFI and RECM analysis, increased metabolizability contributed to approximately 35% improved FE, with the remaining 65% attributed to the greater efficiency of utilization of ME. The analysis within RECM groups suggested that the difference in ME utilization was mainly due to the higher maintenance requirement of Low-RECM cows compared with Medium- and High-RECM cows, whereas the difference between Medium- and High-RECM cows resulted mainly from the higher efficiency of ME utilization for milk production in High-RECM cows. The main difference within FCE (ECM/DMI) categories was a greater (8.2 kg/d) ECM yield at the expense of mobilization in High-FCE cows compared with Low-FCE cows. Methane intensity (CH₄/ECM) was lower for efficient cows than for inefficient cows. The results indicated that RFI and RECM are different traits. We concluded that there is considerable variation in FE among cows that is not related to dilution of maintenance requirement or nutrient partitioning. Improving FE is a sustainable approach to reduce CH₄ production per unit of product, and at the same time improve the economics of milk production.

Use of indirect calorimetry to evaluate utilization of energy in lactating Jersey dairy cattle consuming diets with increasing inclusion of hydrolyzed feather meal

A study using indirect calorimetry and 12 lactating multiparous Jersey cows (53 ± 23 d in milk at the beginning of the experiment; mean ± standard deviation) was conducted to evaluate the utilization of energy in cattle consuming diets containing increasing hydrolyzed feather meal (HFM). A triplicated 4 × 4 Latin square design with 35-d periods (28-d adaption and 4-d collections) was used to compare 4 different dietary treatments. Treatments contained (DM basis) HFM at 0% (0HFM), 3.3% (3.3HFM), 6.7% (6.7MFM), and 10.0% (10HFM). Diets were formulated such that HFM replaced blood meal and nonenzymatically browned soybean meal. With increasing HFM, linear increases were observed for dietary NEL content (1.61, 1.64, 1.69, and 1.70 ± 0.042 Mcal/kg of DM for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively), and the efficiency of converting ME to NEL (0.708, 0.711, 0.717, and 0.719). Apparent total-tract digestibility of CP linearly decreased with increasing HFM (63.4, 61.1, 59.9, and 58.6 ± 1.46% for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively), whereas long-chain fatty acid digestibility increased with increasing HFM (77.2, 77.7, 78.5, and 80.6 ± 1.30%). With increased inclusion of HFM, fecal N excretion increased (199, 230, 239, 237 ± 12.1 g/d for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively), whereas urinary N excretion decreased (166, 151, 155, and 119 ± 14.8 g/d). Increasing the concentration of HFM resulted in a quadratic effect on DMI (19.6, 20.2, 20.3, and 19.1 ± 0.79 kg/d for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively) and milk yield (31.7, 32.0, 31.9, and 29.7 ± 1.32 kg/d). Increasing HFM linearly decreased the milk protein concentration (3.34, 3.29, 3.23, and 3.23 ± 0.158 for 0HFM, 3.3HFM, 6.7MFM, and 10HFM, respectively) and yield (1.05, 1.05, 1.02, and 0.96 ± 0.040 kg). The inclusion of HFM did not affect energy-correct milk yield (average of 39.3 ± 1.54). Results of this study suggest that HFM can increase dietary NEL content compared with blood meal and nonenzymatically browned soybean meal and maintained energy-corrected milk yield; however, feeding HFM at greater than 6.7% of diet DM decreased DMI, and protein availability may have been reduced with increased HFM, leading to a linear decrease in milk protein concentration and yield.

Effects of feeding wheat or corn and of rumen fistulation on milk production and methane emissions of dairy cows

There has been little research that has quantified methane (CH4) yields when dairy cows consume diets containing wheat grain. Furthermore, although rumen-fistulated animals have been used in many experiments concerned with measuring CH4 emissions, no research has examined the effect of rumen fistulation on in vivo CH4 emissions and yield. This experiment examined the effects of including either wheat or corn grain in the diet and the effects of rumen fistulation on yields of milk and milk components, CH4 emissions, yields, and intensities. Eight rumen-fistulated and six non-fistulated Holstein dairy cows in late lactation were offered a wheat-based diet (WHT) and a corn-based diet (CRN) in a crossover design. For the WHT diet, cows were offered daily, 22.4 kg DM containing 45.5% lucerne hay, 8.9% canola meal, 0.5% mineral mix, 0.5% molasses powder and 44.6% rolled wheat. The CRN diet was similar to the WHT diet except that rolled corn replaced the wheat. There was no difference between the WHT and CRN diets on mean milk yields (27.8 vs 27.9 kg/day), but the WHT diet substantially reduced milk fat concentration (2.76 vs 4.23%) and milk fat yield (0.77 vs 1.18 kg/day). Methane emissions (218 vs 424 g/day), CH4 yield (11.1 vs 19.5 g/kg dry matter intake) and CH4 intensity (7.6 vs 15.7 g/kg milk) were all reduced ~45% by the WHT diet compared with the CRN diet. Rumen fistulation did not affect dry matter intake, milk production, milk composition or CH4 emissions, but decreased CH4 yield and intensity. Including wheat in the diet of dairy cows has the potential to be an effective strategy to reduce their greenhouse gas emissions. In addition, rumen fistulation was associated with a small reduction in CH4 yield and intensity, and this should be considered when using rumen-fistulated cows in research concerned with CH4 emissions.

Evidence for increasing digestive and metabolic efficiency of energy utilization with age of dairy cattle as determined in two feeding regimes

The changes taking place with age in energy turnover of dairy cattle are largely unknown. It is unclear whether the efficiency of energy utilization in digestion (characterized by faecal and methane energy losses) and in metabolism (characterized by urine and heat energy losses) is altered with age. In the present study, energy balance data were obtained from 30 lactating Brown Swiss dairy cows aged between 2 and 10 years, and 12 heifers from 0.5 to 2 years of age. In order to evaluate a possible dependence of age effects on diet type, half of the cattle each originated from two herds kept at the same farm, which were fed either on a forage-only diet or on the same forage diet but complemented with 5 kg/day of concentrate since their first calving. During 2 days, the gaseous exchange of the animals was quantified in open-circuit respiration chambers, followed by an 8-day period of feed, faeces, urine and milk collection. Daily amounts and energy contents were used to calculate complete energy balances. Age and feeding regime effects were analysed by parametric regression analysis where BW, milk yield and hay proportion in forage as consumed were considered as covariates. Relative to intake of gross energy, the availability of metabolizable energy (ME) increased with age. This was not the result of an increasing energy digestibility, but of proportionately lower energy losses with methane (following a curvilinear relationship with the greatest losses in middle-aged cows) and urine (continuously declining). The efficiency of utilization of ME for milk production (k l) increased with age. Potential reasons include an increase in the propionate-to-acetate ratio in the rumen because of a shift away from fibre degradation and methane formation as well as lower urine energy losses. The greater k l allowed older cows to accrete more energy reserves in the body. As expected, offering concentrate enhanced digestibility, metabolizability and metabolic utilization of energy. Age and feeding regime did not interact significantly. In conclusion, older cows seem to have digestive and metabolic strategies to use dietary energy to a certain degree more efficiently than younger cows.

Effect of dietary net energy concentration on dry matter intake and energy partition in cows in mid-lactation under heat stress

This study aimed to determine the net energy requirement of Holstein cows in mid-lactation under heat stress. Twenty-five multiparous Holstein cows were randomly allocated to five groups corresponding to five isonitrogenous total mixed rations, with net energy for lactation (NE_L ) content of 6.15 (NE-6.15), 6.36 (NE-6.36), 6.64 (NE-6.64), 6.95 (NE-6.95), 7.36 (NE-7.36) MJ/kg of dry matter (DM), respectively. Throughout the experimental period the average temperature humidity index at 07.00, 14.00 and 22.00 hours was 72.1, 88.7, and 77.6, respectively. DM intake decreased significantly with the elevated dietary NE_L concentration. Fat corrected milk increased quadratically, and milk fat content and milk energy (MJ/kg) reached the greatest in the NE-6.95 group with increasing dietary NE_L content. Strong correlations were found between dietary NE_L content and: (i) DM intake; (ii) NE_L intake; (iii) milk energy (E_l ); (iv) E_l /metabolizable energy intake (MEI); (v) E_l /NE_L intake, as well as between NE_L intake and fat corrected milk yield (FCM). The suitable net energy required for dairy cows producing 1 kg FCM ranged from 5.01 to 5.03 MJ, was concluded from the above-stated regressions. Correlation between heat production (HP) and MEI could be expressed as: Log (HP) = -0.4304 + 0.2963*MEI (n = 15, R²  = 0.99, Root Mean Square Error (RMSE) = 0.18). Fasting HP was 0.3712 MJ/kg^0.75 when extrapolating MEI to zero.

Estimation of the maintenance energy requirements, methane emissions and nitrogen utilization efficiency of two suckler cow genotypes

Seventeen non-lactating dairy-bred suckler cows (LF; Limousin×Holstein-Friesian) and 17 non-lactating beef composite breed suckler cows (ST; Stabiliser) were used to study enteric methane emissions and energy and nitrogen (N) utilization from grass silage diets. Cows were housed in cubicle accommodation for 17 days, and then moved to individual tie-stalls for an 8-day digestibility balance including a 2-day adaption followed by immediate transfer to an indirect, open-circuit, respiration calorimeters for 3 days with gaseous exchange recorded over the last two of these days. Grass silage was offered ad libitum once daily at 0900 h throughout the study. There were no significant differences (P>0.05) between the genotypes for energy intakes, energy outputs or energy use efficiency, or for methane emission rates (methane emissions per unit of dry matter intake or energy intake), or for N metabolism characteristics (N intake or N output in faeces or urine). Accordingly, the data for both cow genotypes were pooled and used to develop relationships between inputs and outputs. Regression of energy retention against ME intake (r 2=0.52; P<0.001) indicated values for net energy requirements for maintenance of 0.386, 0.392 and 0.375 MJ/kg0.75 for LF+ST, LF and ST respectively. Methane energy output was 0.066 of gross energy intake when the intercept was omitted from the linear equation (r 2=0.59; P<0.001). There were positive linear relationships between N intake and N outputs in manure, and manure N accounted for 0.923 of the N intake. The present results provide approaches to predict maintenance energy requirement, methane emission and manure N output for suckler cows and further information is required to evaluate their application in a wide range of suckler production systems.

Use of dry citrus pulp or soybean hulls as a replacement for corn grain in energy and nitrogen partitioning, methane emissions, and milk performance in lactating Murciano-Granadina goats

The aim of this study was to assess the effect of substitution of dietary corn grain by dry citrus pulp or soybean hulls on energy and nitrogen partitioning, substrate oxidation, methane emission, and milk performance in dairy goats during midlactation. Twelve multiparous Murciano-Granadina goats of similar body weight (41.7 ± 2.8 kg) were split in 3 groups in an incomplete crossover design. One group of 4 goats was fed a mixed ration with 605 g/kg of dry matter of corn grain (CRG), another group replaced corn grain with dry citrus pulp (CTP), and the last with soybean hulls (SYH). The goats were allocated to individual metabolism cages. After 14 d of adaptation, feed intake, total fecal and urine output, and milk yield were recorded daily over a 5-d period. Then, gas exchange measurements were recorded by a mobile open-circuit indirect calorimetry system using a head box. Dry matter intake was similar for all 3 groups (1.53 kg/d, on average). Total replacement of the concentrate with fibrous by-products increased fiber apparent digestibility. The metabolizable energy intake was significantly greater for diet CRG than SYH (1,193 vs. 1,079 kJ/kg of BW⁰·⁷⁵, respectively), CTP showed an intermediate value. The heat production was higher for the fiber diet than starchy diet (908 vs. 843 kJ/kg of BW⁰·⁷⁵ for SYH and CRG, respectively). The efficiency of use of metabolizable energy for milk production obtained by regression was 0.59. Goats fed CTP and SYH diets produced similar CH₄ emissions (34.8 g/d, on average), significantly higher compared with goats fed the CRG diet (24.7 g/d). Goats of the 3 treatments were in negative energy balance, so the oxidation of fat was greater than for carbohydrates. No significant differences were observed for milk production (1.72 kg/d), and milk fat was significantly greater for a more fibrous diet compared with a starchy diet (6.57 vs. 4.95% in SYH and CRG, respectively).

A Bayesian approach to analyze energy balance data from lactating dairy cows

The objective of the present investigation was to develop a Bayesian framework for updating and integrating covariate information into key parameters of metabolizable energy (ME) systems for dairy cows. The study addressed specifically the effects of genetic improvements and feed quality on key parameters in current ME systems. These are net and metabolizable energy for maintenance (NE(M) and ME(M), respectively), efficiency of utilization of ME for milk production (k(L)) and growth (k(G)), and efficiency of utilization of body stores for milk production (k(T)). Data were collated from 38 studies, yielding 701 individual cow observations on milk energy, ME intake, and tissue gain and loss. A function based on a linear relationship between milk energy and ME intake and correcting for tissue energy loss or gain served as the basis of a full Bayesian hierarchical model. The within-study variability was modeled by a Student t-distribution and the between-study variability in the structural parameters was modeled by a multivariate normal distribution. A meaningful relationship between genetic improvements in milk production and the key parameters could not be established. The parameter k(L) was linearly related to feed metabolizability, and the slope predicted a 0.010 (-0.0004; 0.0210) change per 0.1-unit change in metabolizability. The effect of metabolizability on k(L) was smaller than assumed in present feed evaluation systems and its significance was dependent on collection of studies included in the analysis. Three sets of population estimates (with 95% credible interval in parentheses) were generated, reflecting different degrees of prior belief: (1) Noninformative priors yielded 0.28 (0.23; 0.33) MJ/(kg(0.75)d), 0.55 (0.51; 0.58), 0.86 (0.81; 0.93) and 0.66 (0.58; 0.75), for NE(M), k(L), k(G), and k(T), respectively; (2) Introducing an informative prior that was derived from a fasting metabolism study served to combine the most recent information on energy metabolism in modern dairy cows. The new estimates of NE(M), k(L), k(G) and k(T) were 0.34 (0.28; 0.39) MJ/(kg(0.75)d), 0.58 (0.54; 0.62), 0.89 (0.85; 0.95), and 0.69 (0.60; 0.79), respectively; (3) finally, all informative priors were used that were established from literature, yielding estimates for NE(M), k(L), k(G), and k(T) of 0.29 (0.11; 0.46) MJ/(kg(0.75)d), 0.60 (0.54; 0.70), 0.70 (0.50; 0.88), and 0.80 (0.67; 0.97), respectively. Bayesian methods are especially applicable in meta-analytical studies as information can enter at various stages in the hierarchical model.

Effects of stage of lactation and level of feed intake on energy utilization by Alpine dairy goats

Thirty-six lactating Alpine does were used to determine effects of stage of lactation and level of feed intake on energy utilization. Twelve does were assigned to measurement periods in early, mid, and late lactation (wk 5, 13, and 27, respectively). For 6 does of each group, after ad libitum consumption of a 60% concentrate diet, feed intake was restricted to near the metabolizable energy (ME) requirement for maintenance (ME(m)) for 8 d followed by fasting for 4 d. For other does, fasting immediately followed ad libitum consumption. Intake of ME was similar among stages of lactation with ad libitum intake (22.1, 22.1, and 19.8 kJ/d in early, mid, and late lactation, respectively). The efficiency of ME use for maintenance determined with does fed near ME(m) averaged 81%. Fasting heat energy was greater for ad libitum consumption than for near ME(m) consumption [368 vs. 326 kJ/kg of body weight (BW)(0.75)] and was numerically lowest among stages in late lactation with near ME(m) intake (334, 350, and 295 kJ/kg of BW(0.75) in early, mid, and late lactation, respectively) and ad libitum consumption (386, 384, and 333 kJ/kg of BW(0.75) in early, mid, and late lactation, respectively). The efficiency of use of dietary ME for lactation was greater for consumption near ME(m) than for consumption ad libitum (67.9 vs. 58.6%) and with ad libitum consumption tended to decrease with advancing stage of lactation (63.9, 57.3, and 54.5% for early, mid, and late lactation, respectively). Estimated ME(m) was greater for ad libitum intake than for near ME(m) intake and was lowest during late lactation (429, 432, and 358 kJ/kg of BW(0.75) for near ME(m) intake and 494, 471, and 399 kJ/kg of BW(0.75) for ad libitum intake in early, mid, and late lactation, respectively). However, because of increasing BW as the experiment progressed, ME(m) (MJ/d) was similar among stages of lactation with both levels of intake. The efficiency of ME use for maintenance and lactation was similar among stages of lactation and greater with near ME(m) intake than ad libitum intake (77.1 vs. 67.7%). In conclusion, the ME(m) requirement (kJ/kg of BW(0.75)) of does in late lactation was less than in early and mid lactation. A marked effect of restricted feed intake subsequent to ad libitum consumption on estimates of efficiency of energy use for maintenance and lactation was observed compared with use of nonlactating animals. Level of feed intake can have substantial effect on estimates of energy utilization by lactating dairy goats.

Recent advances in modeling nutrient utilization in ruminants

Mathematical modeling techniques have been applied to study various aspects of the ruminant, such as rumen function, postabsorptive metabolism, and product composition. This review focuses on advances made in modeling rumen fermentation and its associated rumen disorders, and energy and nutrient utilization and excretion with respect to environmental issues. Accurate prediction of fermentation stoichiometry has an impact on estimating the type of energy-yielding substrate available to the animal, and the ratio of lipogenic to glucogenic VFA is an important determinant of methanogenesis. Recent advances in modeling VFA stoichiometry offer ways for dietary manipulation to shift the fermentation in favor of glucogenic VFA. Increasing energy to the animal by supplementing with starch can lead to health problems such as subacute rumen acidosis caused by rumen pH depression. Mathematical models have been developed to describe changes in rumen pH and rumen fermentation. Models that relate rumen temperature to rumen pH have also been developed and have the potential to aid in the diagnosis of subacute rumen acidosis. The effect of pH has been studied mechanistically, and in such models, fractional passage rate has a large impact on substrate degradation and microbial efficiency in the rumen and should be an important theme in future studies. The efficiency with which energy is utilized by ruminants has been updated in recent studies. Mechanistic models of N utilization indicate that reducing dietary protein concentration, matching protein degradability to the microbial requirement, and increasing the energy status of the animal will reduce the output of N as waste. Recent mechanistic P models calculate the P requirement by taking into account P recycled through saliva and endogenous losses. Mechanistic P models suggest reducing current P amounts for lactating dairy cattle to at least 0.35% P in the diet, with a potential reduction of up to 1.3 kt/yr. A model that integrates nutrient utilization and health has great potential benefit for ruminant nutrition research. Finally, whole-animal or farm level models are discussed. An example that used a multiple-criteria decision-making framework is reviewed, and the approach is considered to be appropriate in dealing with the multidimensional nature of agricultural systems and can be applied to assist the decision process in cattle operations.

Meta-analysis of phosphorus balance data from growing pigs

Many studies have highlighted concerns over current methods of determining endogenous P losses and P requirements in growing pigs. Therefore, a database containing observations on 350 pigs was assembled from various studies. Four functions for analyzing P balance data were considered: 1) a straight line, 2) a diminishing returns function (monomolecular), 3) a sigmoidal function with a fixed point of inflection (Gompertz), and 4) a sigmoidal function with a flexible point of inflection (Richards). The nonlinear functions were specifically reparameterized to assign biological meaning to the parameters. Meta-analysis of the data was conducted to estimate endogenous P excretion, maintenance requirement, and efficiency of utilization. Phosphorus retention was regressed against either available P intake or total P intake [all variables scaled by metabolic BW (BW(0.75))]. There was evidence of non-linearity in the data, and the monomolecular function provided the best fit to the data. The Richards equation did not fit the data well and appeared overparameterized. Estimates of endogenous P excretion of 14 and 17 mg/kg of BW(0.75) x d based on available and total P analysis, respectively, were predicted by the monomolecular equation, which were within the range reported in the literature. Maintenance requirement values of 15 mg of available P/kg of BW(0.75) x d and 37 mg of total P/kg of BW(0.75) x d were obtained, based on the monomolecular equation. Average efficiencies of conversion of dietary P to retained P were 65 and 36% for available and total P, respectively, with greater efficiency values calculated for low P intakes. Although the monomolecular equation fitted the data best, more observations at high P intakes/kg of BW(0.75) are required to determine conclusively whether P retention scaled by metabolic BW is linearly related to available or total P intake.

The efficiency of utilization of metabolizable energy for milk production: a comparison of Holstein with F1 Montbeliarde × Holstein cows

The objectives were to demonstrate the potential of heat production measurements to characterize the gross and net efficiencies of dairy cows under commercial conditions and to compare the efficiencies of purebred Holstein and Montbeliarde × Holstein F1 dairy cows. The heat productions of seven Holstein (H) and seven Montbeliarde × Holstein (MH) cows were measured over two 10-day periods separated by a 75-day interval, during the summer of 2004, in a commercial high-yielding dairy herd in Israel. Energy expenditure was measured by monitoring heart rates and oxygen consumption per heart beat. Milk yield and composition were recorded for these cows and their investment of energy in the milk was calculated from the milk yield and composition. Live weight and body condition score were also recorded in parallel with these measurements. Metabolizable energy (ME) intake was estimated as the sum of heat production, energy in milk and body energy balance. The MH cows were heavier by 90 kg, had higher body condition scores by 0·9 units and secreted proportionately 0·19 and 0·38 less energy in their milk than H cows in the first and second periods, respectively. The gross energy efficiencies, expressed as the percentage of milk production plus body retention in ME intake were 48·3 and 43·4% in the first period and 45·6 and 32·8% in the second period, for H and MH cows, respectively. The milk production of MH cows in this study was lower than the potential of this cross, however, MH cows that expressed this potential would still be expected to require proportionately 0·10 greater intake of ME than H cows, per unit of energy in milk.

Physiology, regulation and multifunctional activity of the gut wall: a rationale for multicompartmental modelling

A rationale is given for a modelling approach to identify the mechanisms involved in the functioning and metabolic activity of tissues in the wall of the gastrointestinal tract. Maintenance and productive functions are discussed and related to the distinct compartments of the gastrointestinal tract and the metabolic costs involved. Functions identified are: tissue turnover; tissue proliferation; ion transport; nutrient transport; secretions of digestive enzymes, mucus and immunoglobulins; production of immune cells. The major nutrients involved include glucose, amino acids and volatile fatty acids.In vivomeasurements of net portal fluxes of these nutrients in pigs and ruminants are evaluated to illustrate the complexity of physiology and metabolic activity of the gastrointestinal tract. Experimental evidence indicates that high, but variable and specific, nutrient costs are involved in the functioning of the gastrointestinal tract.

Evaluation of Net Energy Expenditures of Dairy Cows According to Body Weight Changes over a Full Lactation

Equations that predict daily dry matter intake (DMI) of a lactating cow could be evaluated by comparing the predicted accumulation of energy in body weight (BW) over the course of lactation with the observed BW evolution. However, to do so requires that first the energy balance calculations from observed DMI are evaluated. The purpose of the work reported here was to determine the degree of deviation of predicted from observed BW, according to net energy for lactation (NE(L)) balance calculated from weekly observations of DMI, BW, and fat-corrected milk production in 21 sets of full-lactation data, and to determine an appropriate correction of the NE(L) bias for subsequent DMI prediction evaluations. When the National Research Council maintenance equation 0.08 x BW(kg)(0.75) was used in energy balance calculation, BW was overpredicted with an increasing difference between the cumulative predicted BW and observed BW as lactation progressed. Placing all the error of BW prediction into maintenance energy expenditures resulted in a best-fit equation of 0.096 +/- 0.003 Mcal/kg of BW(0.75). A time-dependent equation was also developed, in which weekly maintenance expenditures were determined as the NE(L) expenditure to yield a zero NE(L) balance and could be described by a second-order polynomial equation related to week of lactation (WOL) where maintenance NE(L) = [-0.0227(+/- 0.0098) x WOL2 + 1.352(+/- 0.456) x WOL + 78.09(+/- 4.92) Mcal/kg of BW(0.75)] x 10(-3). Average maintenance energy expenditure at the onset of lactation was approximately 0.08 Mcal/kg of BW(0.75), and this value increased to a plateau at wk 15 of lactation of approximately 0.098 Mcal/kg of BW(0.75). Standard deviations between data sets of weekly maintenance parameter estimates throughout lactation were large but consistent at approximately 25% of the mean. Revision of the maintenance energy expenditure estimate substantially improved BW prediction by the energy balance model. On average, the 0.096 Mcal of NE(L)/kg of BW(0.75) equation resulted in the best BW predictions, although substantial variation existed around this value.