scholarly journals Applicability of the True Metabolizable Energy System in Practical Feed Formulation

1982 ◽  
Vol 61 (2) ◽  
pp. 351-356 ◽  
Author(s):  
N.M. DALE ◽  
H.L. FULLER
Keyword(s):  
Energy System ◽  
Metabolizable Energy ◽  
Feed Formulation

scholarly journals The Deviation between Dairy Cow Metabolizable Energy Requirements and Pasture Supply on a Dairy Farm Using Proximal Hyperspectral Sensing

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 240
Author(s):  
Federico Duranovich ◽  
Nicolás López-Villalobos ◽  
Nicola Shadbolt ◽  
Ina Draganova ◽  
Ian Yule ◽  
...  
Keyword(s):  
Milk Fat ◽  
Supply And Demand ◽  
Dairy Farm ◽  
Energy System ◽  
Metabolizable Energy ◽  
Feeding Strategies ◽  
Canopy Reflectance ◽  
Estimate Variance ◽  
Hyperspectral Sensing ◽  
Daily Total

This study aimed at determining the extent to which the deviation of daily total metabolizable energy (MEt) requirements of individual cows from the metabolizable energy (ME) supplied per cow (DME) varied throughout the production season in a pasture-based dairy farm using proximal hyperspectral sensing (PHS). Herd tests, milk production, herbage and feed allocation data were collected during the 2016–2017 and 2017–2018 production seasons at Dairy 1, Massey University, New Zealand. Herbage ME was determined from canopy reflectance acquired using PHS. Orthogonal polynomials were used to model lactation curves for yields of milk, fat, protein and live weights of cows. Daily dietary ME supplied per cow to the herd and ME requirements of cows were calculated using the Agricultural Food and Research Council (AFRC) energy system of 1993. A linear model including the random effects of breed and cow was used to estimate variance components for DME. Daily herd MEt estimated requirements oscillated between a fifth above or below the ME supplied throughout the production seasons. DME was mostly explained by observations made within a cow rather than between cows or breeds. Having daily estimates of individual cow requirements for MEt in addition to ME dietary supply can potentially contribute to achieving a more precise fit between supply and demand for feed in a pasture-based dairy farm by devising feeding strategies aimed at reducing DME.

scholarly journals Relationships of retained energy and retained protein that influence the determination of cattle requirements of energy and protein using the California Net Energy System

2018 ◽  
Vol 3 (3) ◽  
pp. 1029-1039 ◽  
Author(s):  
Luis O Tedeschi
Keyword(s):  
Body Fat ◽  
Energy System ◽  
The Body ◽  
Metabolizable Energy ◽  
Net Energy ◽  
Body Protein ◽  
Protein Requirements ◽  
Growing Cattle ◽  
Lower Correlation

Abstract Interrelationships between retained energy (RE) and retained protein (RP) that are essential in determining the efficiency of use of feeds and the assessment of energy and protein requirements of growing cattle were analyzed. Two concerns were identified. The first concern was the conundrum of a satisfactory correlation between observed and predicted RE (r = 0.93) or between observed and predicted RP when using predicted RE to estimate RP (r = 0.939), but a much lower correlation between observed and predicted RP when using observed RE to estimate RP (r = 0.679). The higher correlation when using predicted vs. observed RE is a concern because it indicates an interdependency between predicted RP and predicted RE that is needed to predict RP with a higher precision. These internal offsetting errors create an apparent overall adequacy of nutrition modeling that is elusive, thus potentially destabilizing the predictability of nutrition models when submodels are changed independently. In part, the unsatisfactory prediction of RP from observed RE might be related to the fact that body fat has a caloric value that is 1.65 times greater than body protein and the body deposition of fat increases exponentially as an animal matures, whereas body deposition of protein tends to plateau. Thus, body fat is more influential than body protein in determining RE, and inaccuracies in measuring body protein will be reflected in the RP comparison but suppressed in the RE calculation. The second concern is related to the disconnection when predicting partial efficiency of use of metabolizable energy for growth (kG) using the proportion of RE deposited as protein—carcass approach—vs. using the concentration of metabolizable energy of the diet—diet approach. The culprit of this disconnection might be related to how energy losses that are associated with supporting energy-expending processes (HiEv) are allocated between these approaches. When computing kG, the diet approach likely assigns the HiEv to the RE pool, whereas the carcass approach ignores the HiEV, assigning it to the overall heat production that is used to support the tissue metabolism. Opportunities exist for improving the California Net Energy System regarding the relationships of RE and RP in computing the requirements for energy and protein by growing cattle, but procedural changes might be needed such as increased accuracy in the determination of body composition and better partitioning of energy.

scholarly journals How did Lofgreen and Garrett do the math?

2019 ◽  
Vol 3 (3) ◽  
pp. 1011-1017
Author(s):  
James W Oltjen
Keyword(s):  
Body Weight ◽  
Energy Content ◽  
Energy System ◽  
Metabolizable Energy ◽  
Net Energy ◽  
Significant Difference ◽  
Linear Fit ◽  
Metabolizable Energy Intake ◽  
Logarithmic Equation ◽  
Finishing Beef Cattle

Abstract Lofgreen and Garrett introduced a new system for predicting growing and finishing beef cattle energy requirements and feed values using net energy concepts. Based on data from comparative slaughter experiments they mathematically derived the California Net Energy System. Scaling values to body weight to the ¾ power, they summarized metabolizable energy intake (ME), energy retained (energy balance [EB]), and heat production (HP) data. They regressed the logarithm of HP on ME and extended the line to zero intake, and estimated fasting HP at 0.077 Mcal/kg0.75, similar to previous estimates. They found no significant difference in fasting HP between steers and heifers. Above maintenance, however, a logarithmic fit of EB on ME does not allow for increased EB once ME is greater than 340 kcal/kg0.75, or about three times maintenance intake. So based on their previous work, they used a linear fit so that partial efficiency of gain above maintenance was constant for a given feed. They show that with increasing roughage level efficiency of gain (slope) decreases, consistent with increasing efficiency of gain and maintenance with greater metabolizable energy of the feed. Making the system useful required that gain in body weight be related to EB. They settled on a parabolic equation, with significant differences between steers and heifers. Lofgreen and Garrett also used data from a number of experiments to relate ME and EB to estimate the ME required for maintenance (ME = HP) and then related the amount of feed that provided that amount of ME to the metabolizable energy content of the feed (MEc), resulting in a logarithmic equation. Then they related that amount of feed to the net energy for gain calculated as the slope of the EB line when regressed against feed intake. Combining the two equations, they estimate the net energy for maintenance and gain per unit feed (Mcal/kg dry matter) as a function of MEc: 0.4258 × 1.663MEc and 2.544–5.670 × 0.6012MEc, respectively. Finally, they show how to calculate net energy for maintenance and gain from experiments where two levels of a ration are fed and EB measured, where one level is fed and a metabolism trial is conducted, or when just a metabolism trial is conducted—but results are not consistent between designs.

scholarly journals Applying the California net energy system to growing goats1

2019 ◽  
Vol 3 (3) ◽  
pp. 999-1010
Author(s):  
Izabelle A M A Teixeira ◽  
Amélia K Almeida ◽  
Márcia H M R Fernandes ◽  
Kleber T Resende
Keyword(s):  
Energy Use ◽  
Energy System ◽  
Metabolizable Energy ◽  
Energy Requirements ◽  
Net Energy ◽  
Dairy Goats ◽  
Indigenous Goats ◽  
Metabolizable Energy Intake ◽  
Degree Of Maturity ◽  
Body Energy

Abstract The aim of this review is to describe the main findings of studies carried out during the last decades applying the California net energy system (CNES) in goats. This review also highlights the strengths and pitfalls while using CNES in studies with goats, as well as provides future perspectives on energy requirements of goats. The nonlinear relationship between heat production and metabolizable energy intake was used to estimate net energy requirements for maintenance (NEm). Our studies showed that NEm of intact and castrated male Saanen goats were approximately 15% greater than female Saanen goats. Similarly, NEm of meat goats (i.e., >50% Boer) was 8.5% greater than NEm of dairy and indigenous goats. The first partial derivative of allometric equations using empty body weight (EBW) as independent variable and body energy as dependent variable was used to estimate net energy requirements for gain (NEg). In this matter, female Saanen goats had greater NEg than males; also, castrated males had greater NEg than intact males. This means that females have more body fat than males when evaluated at a given EBW or that degree of maturity affects NEg. Our preliminary results showed that indigenous goats had NEg 14% and 27.5% greater than meat and dairy goats, respectively. Sex and genotype also affect the efficiency of energy use for growth. The present study suggests that losses in urine and methane in goats are lower than previously reported for bovine and sheep, resulting in greater metabolizable energy:digestible energy ratio (i.e., 0.87 to 0.90). It was demonstrated that the CNES successfully works for goats and that the use of comparative slaughter technique enhances the understanding of energy partition in this species, allowing the development of models applied specifically to goat. However, these models require their evaluation in real-world conditions, permitting continuous adjustments.

A new net energy system for ruminants

1974 ◽  
Vol 19 (2) ◽  
pp. 141-148 ◽  
Author(s):  
J. Harkins ◽  
R. A. Edwards ◽  
P. Mcdonald
Keyword(s):  
Linear Programming ◽  
Research Council ◽  
Agricultural Research ◽  
Energy System ◽  
Metabolizable Energy ◽  
Net Energy ◽  
Iterative Approach ◽  
Agricultural Research Council ◽  
Growing Cattle

SUMMARYA simplified Net Energy system for ruminants is described. It is based on the Metabolizable Energy system outlined by the Agricultural Research Council (1965) and enables a non-iterative approach to be used in the formulation of rations. The method is suitable for use in linear programming work and is illustrated, with appropriate tables, for growing cattle.

PARTITIONING METABOLIZABLE ENERGY UTILIZATION IN RUMINANTS TO INCLUDE A FACTOR FOR ASSIMILATION OF FOOD INTAKE AND ITS APPLICATION FOR EVALUATING ENERGY REQUIREMENTS OF GROWING-FATTENING CATTLE

1986 ◽  
Vol 66 (3) ◽  
pp. 723-733 ◽  
Author(s):  
V. GIRARD
Keyword(s):  
Heat Production ◽  
Dry Matter ◽  
National Research Council ◽  
Energy System ◽  
Metabolizable Energy ◽  
Energy Utilization ◽  
Dry Matter Intake ◽  
National Academy Of Sciences ◽  
Caloric Value ◽  
Energy Retention

A mathematical analysis of heat production by growing ruminants was used to assess the physiological importance of assimilation and digestion of dry matter intake. Energy retention (ER) was calculated according to National Academy of Sciences-National Research Council (NAS-NRC) (1984) for 300- and 600-kg cattle fed hay or corn silage with approximately 0, 25, 50 and 75% oat or corn grain. Protein synthesis was calculated for each ER using NAS-NRC (1984) standards for medium- and large-frame bulls, steers and heifers. Fat retention was then estimated by removing the caloric value of protein from ER and dividing the result by the caloric value of fat. Heat production (Y, MJ), obtained as the difference between metabolizable energy (ME) intake and energy retention, was related to the animal's metabolic weight (X1, kg), to the protein (X2, kg) and fat (X3, kg deposited and to the dry matter intake (X4, kg):[Formula: see text]This equation explained 99.9% of the variation of individual heat productions predicted by the California net energy system (NAS-NRC 1984). Heat production per kilogram dry matter intake (3.85 MJ) ranged from 38% at maintenance to 48% above maintenance of the total heat produced, which is similar to values reported in the literature from physiological studies. Metabolizable energy efficiency for fasting, gain of protein and gain of fat was respectively 102, 63 and 64%, whatever feed-stuffs were used. The proposed energy system can be summarized and used as follows: ME requirement = ME for fasting + ME for gain of fat + ME for gain of protein + ME for dry matter intake. In this form, ordinary ME values for feedstuffs are used. Key words: Ruminant, growth, protein fat efficiency, system, intake energy

scholarly journals Estimating digestible energy values of feeds and diets and integrating those values into net energy systems

2018 ◽  
Vol 3 (3) ◽  
pp. 953-961 ◽  
Author(s):  
William P Weiss ◽  
Alexander W Tebbe
Keyword(s):  
Energy System ◽  
Metabolizable Energy ◽  
Neutral Detergent Fiber ◽  
Net Energy ◽  
Nutrient Analysis ◽  
Digestible Energy ◽  
Important Variation ◽  
Negative Effect ◽  
Gross Energy

Abstract The California Net Energy System (CNES) used a combination of measured and tabular metabolizable energy (ME) values and changes in body composition gain to determine net energy requirements for maintenance and gain and their corresponding dietary concentrations. The accuracy of the CNES depends on the accuracy of the feed ME values. Feed or diet ME values can be measured directly but are expensive and require specialized facilities; therefore, most ME values are estimated from digestible energy (DE) values, which are often estimated from the concentration of total digestible nutrients (TDN). Both DE and TDN values are often from tables and not based on actual nutrient analysis. The use of tabular values eliminates important within-feed variation in composition and digestibility. Furthermore, the use of TDN to estimate DE does not account for important variation in the gross energy value of feeds. A better approach would be to estimate DE concentration directly from nutrient composition or in vitro (or in situ) digestibility measurements. This approach incorporates within-feed variation into the energy system and eliminates the issues of using TDN. A widely used summative equation based on the commonly measured feed fractions (ash, crude protein, neutral detergent fiber, and fat) has been shown to accurately estimate DE concentrations of many diets for cattle; however, deficiencies in that equation have been identified and include an overestimation of DE provided by fat and an exaggerated negative effect of intake on digestibility. Replacing the nonfiber carbohydrate term (which included everything that was not measured) in the equation with measured starch concentration and residual organic matter (i.e., nonfiber carbohydrate minus starch) should improve accuracy by accounting for more variation in starch digestibility. More accurate estimates of DE will improve the accuracy of ME values, which will ultimately lead to more accurate NE values.

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