The effects of the forage-to-concentrate ratio on the conversion of digestible energy to metabolizable energy in growing beef steers

Feeding Management Strategies to Mitigate Methane and Improve Production Efficiency in Feedlot Cattle

Mitigation of greenhouse gases and decreasing nutrient excretion have become increasingly important goals for the beef cattle industry. Because feed intake is a major driver of enteric CH₄ production and nutrient excretion, feeding management systems could be important mitigation tools. Programmed feeding uses net energy equations to determine the feed required to yield a specific rate of gain, whereas restricted feeding typically involves decreasing intake relative to the expected or observed ad libitum intake. In the context of growing/finishing systems typical of those in the United States and Western Canada, experimental results with programmed and restricted feeding have often shown decreased overall feed intake and increased gain efficiency relative to ad libitum feeding, but too much restriction can negatively affect harvest weight and associated carcass quality. Slick feed bunk management is a time-based restriction that limits day-to-day variation in feed deliveries, but the effects on intake and performance are not well defined. Simulations to estimate enteric CH₄ emission and nitrogen excretion indicated that programmed feeding of a high-grain diet could appreciably decrease CH₄ emissions and nitrogen excretion compared with traditional growing programs based on high-forage diets. For feedlot finishing, programming gain for a portion of the feeding period will decrease CH₄ emission and N excretion only if cattle perform better than expected during the programmed phase or if compensatory growth occurs when cattle are transitioned to ad libitum feeding. Optimal approaches to implement programmed or restricted feeding that will yield increased efficiency should be the subject of future research in this area.

A comparison of average daily gain, apparent digestibilities, energy balance, rumen fermentation parameters, and serum metabolites between yaks (Bos grunniens) and Qaidam cattle (Bos taurus) consuming diets differing in energy level

Yaks (Bos grunniens), indigenous to the harsh Qinghai-Tibetan Plateau, are well adapted to the severe conditions, and graze natural pasture without supplements all year round. Qaidam cattle (Bos taurus), introduced to the Qinghai-Tibetan Plateau 1,700 years ago, are raised at a lower altitude than yaks, provided with shelter at night and offered supplements in winter. Based on their different backgrounds, we hypothesized that yaks have lower energy requirements for maintenance than cattle. To test this hypothesis, we measured average daily gain (ADG), apparent digestibilities, energy balance, rumen fermentation parameters, and serum metabolites in growing yaks and cattle offered diets differing in metabolizable energy (ME) levels (6.62, 8.02, 9.42 and 10.80 MJ/kg), but with the same crude protein concentration. Six castrated yaks (155 ± 5.8 kg) and 6 castrated Qaidam cattle (154 ± 8.0 kg), all 2.5 years old, were used in 2 concurrent 4 × 4 Latin square designs. Neutral and acid detergent fiber digestibilities were greater (P < 0.05) in yaks than in cattle, and decreased linearly (P < 0.05) with increasing dietary energy level; whereas, digestibilities of dry matter, organic matter, crude protein and ether extract increased (P < 0.05) linearly with increasing energy level. The ADG was greater (P < 0.001) in yaks than in cattle, and increased (P < 0.05) linearly with increasing energy levels. From the regressions of ADG on ME intake, the estimated ME requirement for maintenance was lower (P < 0.05) in yaks than in cattle (0.43 vs. 0.57 MJ/kg BW^0.75). The ratios of digestible energy (DE):gross energy and ME:DE were higher (P < 0.05) in yaks than in cattle, and increased (P < 0.05) linearly with increasing dietary energy level. Ruminal pH decreased (P < 0.05), whereas concentrations of total volatile fatty acids (VFAs) and ammonia increased (P < 0.01) with increasing dietary energy level, and all were greater (P < 0.05) in yaks than in cattle. Concentrations of ruminal acetate and iso-VFAs were greater (P < 0.05), whereas propionate was lower (P < 0.05) in yaks than in cattle; acetate decreased (P < 0.001), whereas butyrate and propionate increased (P < 0.001) linearly with increasing dietary energy level. Serum concentrations of β-hydroxybutyrate were lower (interaction, P < 0.001) in yaks than in cattle fed diets of 9.42 and 10.80 MJ/kg, whereas non-esterified fatty acids were greater (interaction, P < 0.01) in yaks than in cattle fed diets of 6.62 and 8.02 MJ/kg. Concentrations of serum leptin and growth hormone were greater in yaks than in cattle and serum insulin and growth hormone increased (P < 0.01) linearly with increasing dietary energy level. Our hypothesis that yaks have lower energy requirements for maintenance than cattle was supported. This lower requirement confers an advantage to yaks over Qaidam cattle in consuming low energy diets during the long winter on the Qinghai-Tibetan Plateau.

Enteric methane emissions, growth, and carcass characteristics of feedlot steers fed a garlic- and citrus-based feed additive in diets with three different forage concentrations

One hundred and forty-four Angus × Simmental steers were allotted by body weight (BW; 363 kg), breed composition, and farm origin to a 3 × 2 factorial arrangement of six treatments (4 pens per treatment) to determine the effect of Mootral (garlic + citrus extract; 0.25% of the diet dry matter [DM] vs. 0.0%) on methane (CH4) emissions, growth, and carcass characteristics of feedlot cattle. During the first 84 d, cattle were fed three different forage concentrations in the diet (15%, 41.5%, or 68% corn silage) with or without Mootral. From day 85 to slaughter, corn silage was included at 15% of the diet DM with or without Mootral. CH4 emissions were measured on day 42 to 46 and day 203 to 207. Data were analyzed using the GLIMMIX procedure of SAS. Mootral did not affect CH4 emissions on days 42 to 46 (P ≥ 0.47), but there was a forage effect, where steers fed the 68% corn silage emitted more CH4 on a g/d (P = 0.05) and a g/kg of dry matter intake (DMI; P = 0.007) basis and tended (P = 0.07) to produce more CH4 on g/kg BW basis compared to steers fed the 15% corn silage diet. On day 203 to 207, steers fed Mootral emitted less (P ≤ 0.03) CH4 on a g/d, g/kg DMI, and g/kg BW basis compared to steers not fed Mootral. There was an interaction (P = 0.03) between forage concentration and Mootral for DMI from day 0 to 84, where Mootral decreased DMI of steers fed 15% corn silage but did not affect DMI of steers fed 41.5% or 68% corn silage. There were no effects (P ≥ 0.22) of forage concentration or Mootral on BW or average daily gain at any time, or on DMI from day 84 to slaughter and overall. However, overall calculated net energy for maintenance (NEm) and net energy for gain (NEg) tended to be greater for steers fed Mootral (P ≤ 0.10). Intake from day 0 to 84 was lower and gain:feed from day 0 to 84 and overall was greater (P = 0.04) for steers fed 68% compared to steers fed 41.5% corn silage. Calculated NEm and NEg from day 0 to 84 and overall were greater for steers fed 68% corn silage compared to steers fed 41.5% corn silage (P ≤ 0.03). Mootral tended to decrease (P ≤ 0.09) fat thickness and yield grade. In conclusion, increasing forage concentration increased CH4 emissions and Mootral decreased CH4 production in 15% corn silage diets and tended to improve carcass leanness.

Board Invited Review: Enteric methane mitigation interventions

Mitigation of enteric methane (CH₄) presents a feasible approach to curbing agriculture’s contribution to climate change. One intervention for reduction is dietary reformulation, which manipulates the composition of feedstuffs in ruminant diets to redirect fermentation processes toward low CH₄ emissions. Examples include reducing the relative proportion of forages to concentrates, determining the rate of digestibility and passage rate from the rumen, and dietary lipid inclusion. Feed additives present another intervention for CH₄ abatement and are classified based on their mode of action. Through inhibition of key enzymes, 3-nitrooxypropanol (3-NOP) and halogenated compounds directly target the methanogenesis pathway. Rumen environment modifiers, including nitrates, essential oils, and tannins, act on the conditions that affect methanogens and remove the accessibility of fermentation products needed for CH₄ formation. Low CH₄-emitting animals can also be directly or indirectly selected through breeding interventions, and genome-wide association studies are expected to provide efficient selection decisions. Overall, dietary reformulation and feed additive inclusion provide immediate and reversible effects, while selective breeding produces lasting, cumulative CH₄ emission reductions.

Predicting metabolizable energy from digestible energy for growing and finishing beef cattle and relationships to the prediction of methane

Reliable predictions of metabolizable energy (ME) from digestible energy (DE) are necessary to prescribe nutrient requirements of beef cattle accurately. A previously developed database that included 87 treatment means from 23 respiration calorimetry studies has been updated to evaluate the efficiency of converting DE to ME by adding 47 treatment means from 11 additional studies. Diets were fed to growing-finishing cattle under individual feeding conditions. A citation-adjusted linear regression equation was developed where dietary ME concentration (Mcal/kg of dry matter [DM]) was the dependent variable and dietary DE concentration (Mcal/kg) was the independent variable: ME = 1.0001 × DE - 0.3926; r2 = 0.99, root mean square prediction error [RMSPE] = 0.04, and P < 0.01 for the intercept and slope. The slope did not differ from unity (95% CI = 0.936 to 1.065); therefore, the intercept (95% CI = -0.567 to -0.218) defines the value of ME predicted from DE. For practical use, we recommend ME = DE - 0.39. Based on the relationship between DE and ME, we calculated the citation-adjusted loss of methane, which yielded a value of 0.2433 Mcal/kg of dry matter intake (DMI; SE = 0.0134). This value was also adjusted for the effects of DMI above maintenance, yielding a citation-adjusted relationship: CH4, Mcal/kg = 0.3344 - 0.05639 × multiple of maintenance; r2 = 0.536, RMSPE = 0.0245, and P < 0.01 for the intercept and slope. Both the 0.2433 value and the result of the intake-adjusted equation can be multiplied by DMI to yield an estimate of methane production. These two approaches were evaluated using a second, independent database comprising 129 data points from 29 published studies. Four equations in the literature that used DMI or intake energy to predict methane production also were evaluated with the second database. The mean bias was substantially greater for the two new equations, but slope bias was substantially less than noted for the other DMI-based equations. Our results suggest that ME for growing and finishing cattle can be predicted from DE across a wide range of diets, cattle types, and intake levels by simply subtracting a constant from DE. Mean bias associated with our two new methane emission equations suggests that further research is needed to determine whether coefficients to predict methane from DMI could be developed for specific diet types, levels of DMI relative to body weight, or other variables that affect the emission of methane.

Development of a model to predict dietary metabolizable energy from digestible energy in beef cattle

Understanding the utilization of feed energy is essential for precision feeding in beef cattle production. We aimed to assess whether predicting the metabolizable energy (ME) to digestible energy (DE) ratio (MDR), rather than a prediction of ME with DE, is feasible and to develop a model equation to predict MDR in beef cattle. We constructed a literature database based on published data. A meta-analysis was conducted with 306 means from 69 studies containing both dietary DE and ME concentrations measured by calorimetry to test whether exclusion of the y-intercept is adequate in the linear relationship between DE and ME. A random coefficient model with study as the random variable was used to develop equations to predict MDR in growing and finishing beef cattle. Routinely measured or calculated variables in the field (body weight, age, daily gain, intake, and dietary nutrient components) were chosen as explanatory variables. The developed equations were evaluated with other published equations. The no-intercept linear equation was found to represent the relationship between DE and ME more appropriately than the equation with a y-intercept. The y-intercept (-0.025 ± 0.0525) was not different from 0 (P = 0.638), and Akaike and Bayesian information criteria of the no-intercept model were smaller than those with the y-intercept. Within our growing and finishing cattle data, the animal's physiological stage was not a significant variable affecting MDR after accounting for the study effect (P = 0.213). The mean (±SE) of MDR was 0.849 (±0.0063). The best equation for predicting MDR (n = 106 from 28 studies) was 0.9410 ( ± 0.02160) +0.0042 ( ± 0.00186) × DMI (kg) - 0.0017 ( ± 0.00024) × NDF(% DM) - 0.0022 ( ± 0.00084) × CP(% DM). We also presented a model with a positive coefficient for the ether extract (n = 80 from 22 studies). When using these equations, the observed ME was predicted with high precision (R2 = 0.92). The model accuracy was also high, as shown by the high concordance correlation coefficient (>0.95) and small root mean square error of prediction (RMSEP), <5% of the observed mean. Moreover, a significant portion of the RMSEP was due to random bias (> 93%), without mean or slope bias (P > 0.05). We concluded that dietary ME in beef cattle could be accurately estimated from dietary DE and its conversion factor, MDR, predicted by the dry matter intake and concentration of several dietary nutrients, using the 2 equations developed in this study.

Developing Equations for Converting Digestible Energy to Metabolizable Energy for Korean Hanwoo Beef Cattle

Simple Summary

The available energy in feedstuff represents the largest proportion of the total cost for intensive beef production. Therefore, the energy content of feeds must be known before diet formulation. The determination of digestible energy (DE) and metabolizable energy (ME) values by animal experiments is both time-consuming and costly. Predictive equations to estimate the ME from DE can be useful for feed ingredient evaluations and diet formulations. A range of regression equations were developed in the present study, taking into consideration the gender and body weights of the animals, as well as the feed nutrients, to predict the relationship between the DE and ME. An evaluation of these equations suggested predicting the ME value based on ME = 0.9215 × DE − 0.1434 (R² = 0.999). The generation of these predictive equations represents a step towards updating the ME:DE default conversion factor value of 0.82 adopted from the National Research Council to meet the ME requirements of beef cattle in Korea. The new recommended predictive equation enables the adjustment of the nutrient requirements, thus enhancing animal productivity and maximising the economic return for beef farmers.

Abstract

This study was performed to update and generate prediction equations for converting digestible energy (DE) to metabolizable energy (ME) for Korean Hanwoo beef cattle, taking into consideration the gender (male and female) and body weights (BW above and below 350 kg) of the animals. The data consisted of 141 measurements from respiratory chambers with a wide range of diets and energy intake levels. A simple linear regression of the overall unadjusted data suggested a strong relationship between the DE and ME (Mcal/kg DM): ME = 0.8722 × DE + 0.0016 (coefficient of determination (R²) = 0.946, root mean square error (RMSE) = 0.107, p < 0.001 for intercept and slope). Mixed-model regression analyses to adjust for the effects of the experiment from which the data were obtained similarly showed a strong linear relationship between the DE and ME (Mcal/kg of DM): ME = 0.9215 × DE − 0.1434 (R² = 0.999, RMSE = 0.004, p < 0.001 for the intercept and slope). The DE was strongly related to the ME for both genders: ME = 0.8621 × DE + 0.0808 (R² = 0.9600, RMSE = 0.083, p < 0.001 for the intercept and slope) and ME = 0.7785 × DE + 0.1546 (R² = 0.971, RMSE = 0.070, p < 0.001 for the intercept and slope) for male and female Hanwoo cattle, respectively. By BW, the simple linear regression similarly showed a strong relationship between the DE and ME for Hanwoo above and below 350 kg BW: ME = 0.9833 × DE − 0.2760 (R² = 0.991, RMSE = 0.055, p < 0.001 for the intercept and slope) and ME = 0.72975 × DE + 0.38744 (R² = 0.913, RMSE = 0.100, p < 0.001 for the intercept and slope), respectively. A multiple regression using the DE and dietary factors as independent variables did not improve the accuracy of the ME prediction (ME = 1.149 × DE − 0.045 × crude protein + 0.011 × neutral detergent fibre − 0.027 × acid detergent fibre + 0.683).