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ANIMAL NUTRITION |
Department of Animal Sciences and Industry, Kansas State University, Manhattan 66506
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Abstract |
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 Top Abstract INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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Key Words: chemical composition • digestible energy • forage • regression model
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INTRODUCTION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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) and is characterized by remarkably high annual forage production (3,000 to 6,700 kg/ha; Launchbaugh and Owensby, 1978) relative to other native grassland types. Tallgrass prairie hay (TPH) is often fed to beef cattle in the region because of its abundance and low relative cost; however, animal performance is difficult to predict because the energetic value of TPH is poorly defined. Variable chemical composition limits the practicality of tabular energy values for most grass hay types (Harlan et al., 1991). Therefore, techniques that are sensitive to differences in composition should be used to predict the energy content of TPH for beef cattle. Furthermore, the influences of forage intake level and protein nutrition must also be considered to estimate accurately energy availability from TPH (Brown, 1966; Tyrrell and Moe, 1975; Weiss, 1993).
Fecal energy is the largest and most variable loss of intake energy from most forage diets (Brown, 1966). When fecal energy loss is known, ME and NE can be estimated using standard equations (Garrett, 1980; Minson, 1982). Measurement of DE is impractical for individual forage samples; therefore, empirical equations relating forage chemical components to DE are frequently used. The major limitation of empirical models is population specificity (Abrams, 1988); however, empirical prediction of DE for a single forage type provides an equitable balance of accuracy, speed, and economy (Conrad et al., 1984).
There were 3 objectives to our studies: 1) to establish the potential DE content of TPH from diverse samples fed at maintenance when ruminally degradable protein was not limiting to ruminal fiber digestion, 2) to construct mathematical models to predict DE at or near maintenance from the TPH chemical composition, and 3) to propose a model to adjust apparent DE for use in situations where forage intake exceeds maintenance.
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MATERIALS AND METHODS |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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Determination of Maintenance DE – Trial 1
Thirteen Hereford x Angus steers (average initial BW = 277 ± 15 kg) were used in a 4-period, incomplete Latin square experiment to determine the DE content of 13 diverse samples of TPH fed near maintenance (Cochran and Cox, 1957; Table 1). Hay samples (approximately 5,500 kg) were collected in east-central Kansas along a north-south gradient: 5 samples from Geary, Pottawatomie, and Riley counties in northern Kansas; 6 samples from Chase and Wabaunsee counties in central Kansas; and 2 samples from Greenwood County in southern Kansas. Major graminoid species in the TPH, in order of abundance, were big bluestem (Andropogon gerardii Vitman), indiangrass (Sorghastrum nutans [L.] Nash), little bluestem (Schizachyrium scoparium [Michx.] Nash), sideoats grama (Bouteloua curtipendula [Michx.] Torr.), and switchgrass (Panicum virgatum L.). Native forbs were also present but comprised less than 5% of the total biomass.
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). Weather patterns appeared to result in lower than average forage yields. Seven of the TPH samples were preserved as 1.5- x 1.5-m cylindrical bales (approximately 450 kg) and stored outdoors. The remaining samples were preserved as 0.75- x 0.5- x 0.5-m square bales (approximately 35 kg) and were stored in covered enclosures. All TPH samples were tub-ground (approximately 10-cm particle size) and stored in weather-resistant receptacles 7 d before the study began. Samples that exhibited visual indications of spoilage or were noticeably moist and warm in the interior of the bale at the time of grinding were considered heat damaged. Four hay samples, all stored outdoors, were heat damaged to some degree but were included in the experiment.
Standard conditions for the estimation of DE were achieved using the principles outlined by Blaxter (1962); DE for a particular diet was measured in a thermoneutral environment near maintenance energy intake (DEm) in the absence of nutrient deficiencies. Implicit with this approach are 2 assumptions: 1) maintenance requirements are not affected by age, sex, or physiological state of the test animals and, therefore, DE measurements are applicable to all classes of beef cattle; and 2) obtaining maximal digestion is dependent upon maintaining an adequate ruminally degradable protein (RDP) supply, which is consistent with previous digestion research involving TPH (Scott and Hibberd, 1990; Köster et al., 1996; Olson et al., 1999).
Maintenance requirements for NE were calculated from metabolic BW (NRC, 2000). The amount of TPH required for maintenance (i.e., 1.5% of BW daily) was estimated from the average forage ADF concentration using the appropriate equations (Garrett, 1980; Minson, 1982). Köster et al. (1996) determined that RDP intake equal to 11% of total digestible OM intake resulted in optimal ruminal function and forage utilization by nonpregnant, dry cows consuming TPH. Taking into consideration intake of total OM and forage RDP (measured enzymatically; Coblentz et al., 1999), it was ascertained that soybean meal fed at 0.2% of BW daily would supply sufficient RDP to maintain the ratio of RDP intake to total digestible OM intake suggested by Köster et al. (1996; Table 2).
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) and supplemental soybean meal indicated potential deficiencies in Na, I, Cu, Co, and P. Commercial trace-mineral (Farmland Industries, Kansas City, MO; manufacturer guaranteed analysis: not less than 98% NaCl, 0.2% Mn, 0.1% Fe, 0.1% Mg, 0.05% S, 0.025% Cu, 0.01% Co, 0.008% Zn, and 0.007% I) and dicalcium phosphate preparations were mixed with the supplements and were fed to each steer at rates of 60 and 46 g/d, respectively.
Prescribed amounts of supplement and forage were offered individually to steers at 0700 h daily during 4 consecutive 23-d periods. Steers were allowed to adapt to the assigned hay samples for the first 14 d of each period. Total tract diet digestion was assessed from d 15 to 23 according to the methods of Cochran and Galyean (1994); forage and supplement samples were collected from d 15 to 21 and total fecal output was collected from d 17 to 23. Supplement consumption was complete each day. When daily forage refusals exceeded 1% of the forage DM offered, ort samples were retained. Fecal collection bags were emptied once daily at 0600 h, and the contents were weighed, emptied onto a clean sheet of polyethylene, and mixed thoroughly by hand. Forage and fecal material were subsampled (approximately 3% of daily total) and weighed.
Daily forage, supplement, and fecal samples were dried in a forced-air oven (96 h; 50°C), weighed, and ground (No. 4 Wiley mill, Thomas Scientific, Swedesboro, NJ) to pass a 1-mm screen. Forage and feces were composited within animal and period. Daily supplement samples were composited across animal within period.
Forage, supplements, orts, and feces were analyzed for DM (12 h; 105°C), OM (8 h; 450°C), and Kjeldahl N. These samples were also analyzed for NDF (without amylase or sulfite), ADF, and acid detergent-insoluble ash (ADIA) using the procedure described by Van Soest et al. (1991). Acetyl bromide lignin (ABL) was measured according to the methods of Iiyama and Wallis (1990), and ADIN and ADL were measured according to the methods of Goering and Van Soest (1970). Gross energy of forage, orts, and feces were measured using an adiabatic oxygen bomb calorimeter (DSC-60, Shimadzu, Columbia, MD). Samples of TPH were hydrolyzed to determine neutral monosaccharide content (Hoebler et al., 1989). Monosaccharides were subsequently converted to alditol acetate derivatives (Blakeney et al., 1983) and quantified via GLC (Titgemeyer et al., 1996). Alkali-labile phenolic acids in TPH were measured by HPLC (Titgemeyer et al., 1991).
Total tract nutrient digestion coefficients were calculated using ADIA as an internal marker according to the methods described by Cochran and Galyean (1994). Stafford et al. (1996) reported that fecal recovery of ingested ADIA from steers consuming TPH was quantitative and that supplementation regime did not influence fecal recovery of ADIA. Nutrient intake and digestion data were analyzed using models appropriate for an incomplete Latin square. Models, analyzed via the GLM procedure (SAS Inst. Inc., Cary, NC), included terms for steer, period, and TPH sample. When the F-tests were significant (P < 0.05), means were separated using LSD.
A correlation matrix was prepared using the CORR procedure of SAS to examine the relationships between TPH chemical components, nutrient intake, and nutrient digestion. Chemical components of TPH correlated to DE (P < 0.2) were subjected to iterative regression analysis to predict DE concentration of the diet. Regression equations were constructed in forward-stepwise fashion using the MAXR feature of SAS. Predictive power was considered maximized when the mean square error reached apogee. Equations were selected for presentation based on statistical merit, with consideration for goodness of fit (R2) and prediction error (Sy*x).
Measurement of the Effect of Intake on DE – Trial 2
Sixteen Hereford x Angus steers (average initial BW = 261 ± 17 kg) were used in a 22-d randomized complete-block experiment to measure the effect of forage intake level on apparent dietary DE concentration. Steers were blocked by BW and assigned to receive TPH in amounts equal to 1.3, 1.7, 2.1, or 2.5% of BW daily (DM basis). All steers were fed soybean meal in amounts calculated to provide RDP equal to 11% of the projected digestible OM intake (0.17, 0.23, 0.28, and 0.33% of BW daily for 1.3, 1.7, 2.1, and 2.5% TPH diets, respectively; Table 2
). Forage and supplement RDP was estimated using an enzymatic procedure (Coblentz et al., 1999).
The TPH used in trial 2 was representative of hays used in trial 1, in terms of chemical and grass species composition (Tables 1 and 2). Hay was harvested during July and preserved as 0.75- x 0.5- x 0.5-m square bales (35 kg). Procedures for hay storage, hay processing, vitamin supplementation of steers, mineral supplementation of steers, and housing of steers were identical to those described for trial 1.
Quantities of supplement and forage appropriate for each treatment were offered individually to steers at 0700 h daily during one 22-d sampling period. Steers were allowed to adapt to the assigned forage intake levels for the first 14 d of the trial. Total tract diet digestion was measured from d 15 to 22. Forage and supplement samples were collected from d 14 to 21. Fecal grab samples were collected at 6-h intervals from d 17 to 21. The collection interval was staggered by 1 h each day so that 1 sample was collected from each steer for each hour of the day. Consumption of hay and supplement was complete each day. Daily forage, supplement, and fecal samples were dried in a forced-air oven (96 h; 50°C), weighed, and ground (No. 4 Wiley mill) to pass a 1-mm screen. Forage and supplement samples were composited across steer and treatment. Fecal samples were composited within steer. Chemical analyses of forage, supplements, and feces were conducted as described for trial 1.
Total tract nutrient digestion coefficients were calculated using ADIA as an internal marker (Cochran and Galyean, 1994). Nutrient intake and digestion data were analyzed using models appropriate for a randomized complete block experiment. Models, analyzed via Proc GLM of SAS, included terms for treatment and block. Orthogonal polynomial contrasts were used to partition treatment sums of squares. Maintenance requirements for NE were calculated from metabolic BW, as in trial 1 (NRC, 2000). Published equations were used to calculate diet ME and NEm from the apparent DE concentration (Garrett, 1980; Minson, 1982). Apparent digestions of DM, OM, NDF, and GE were regressed on the ratio of NEm intake to maintenance NE requirement to estimate apparent digestion coefficients at 1 x maintenance. Measured digestion coefficients were then expressed relative to maintenance. Scaled digestion coefficients were regressed on the ratio of NEm intake to maintenance NE requirement to determine the percentage change in apparent digestion of DM, OM, NDF, and GE per multiple of maintenance intake.
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RESULTS AND DISCUSSION |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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Compositional features of individual TPH samples are presented in Table 1. Concentrations of N were relatively low and varied considerably among samples, as is typical with warm-season hay (Minson, 1982). Potentially available N appeared to vary widely among TPH samples as ADIN comprised 17 to 68% of total N. Fiber constituents NDF and ADF averaged 67.4 and 42.5%, respectively. The GE concentration (3.75 ± 0.09 Mcal/kg) varied only slightly among TPH samples.
Glucose and xylose were the predominant sugars in TPH cell walls, together comprising between 35.4 and 44.2% of DM. The sum of arabinose, galactose, mannose, and rhamnose concentrations accounted for a minor proportion of TPH cell wall (5.3 to 7.5% of DM). Titgemeyer et al. (1996) showed that, as big bluestem plants matured phenologically, xylose concentration in cell walls increased while glucose concentration remained constant. The ratio of xylose to glucose, which averaged 0.78 ± 0.07 among TPH samples in our study, may serve as a useful indicator of relative forage maturity. Ferulic acid and p-coumaric acid, noncore lignin compounds, averaged 0.51 ± 0.04 and 0.57 ± 0.13% of DM, respectively. Ferulic acid is associated with xylans of the secondary plant cell wall and may cause reduced ruminal fiber degradation and energy yield (Jung, 1989). Similarly, p-coumaric acid is primarily linked to core lignin and increases markedly in big bluestem as the plant matures (Titgemeyer et al., 1996).
Gross energy intake fell within a narrow range (Table 3; 0.26 ± 0.01 Mcal/kg of BW0.75). Conversely, intake of NDF, intake of digestible OM, OM digestion, NDF digestion, and DE varied considerably among TPH samples fed to steers at 1.5% of BW daily. Intake of NDF and digestible OM varied by 8.2 and 11.7 g/kg of BW0.75, respectively, among TPH samples. Similarly, the range in OM digestion, NDF digestion, and DE of TPH samples varied by 18.4, 12.3, and 17.9%, respectively.
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; Olson et al., 1999; Schmidt et al., 2006) but, in this study, N was supplemented to limit its direct impact on digestion.
Several empirical equations have been developed to predict digestion of grass hays from forage N or CP values (Minson, 1982; NRC, 2000). Accuracy of these equations has generally been poor. Weiss (1993) suggested that, although N functions as a uniform fraction in most feeds, it is a poor predictor of digestion because it constitutes a relatively small proportion of total forage DM.
Energy content of TPH fed at 1.5% of BW daily is shown in Table 4. Digestible energy of TPH ranged from 1.56 to 2.32 Mcal/kg. These values were somewhat less than those reported for grass hays in the northeastern United States (Harlan et al., 1991). The NRC (2000, 2001) related 1 kg of TDN to 4.409 Mcal of DE. In our study, 1 kg of digestible OM was equivalent to 4.184 Mcal of DE. Weiss (1993) suggested that a conversion efficiency of 0.82 was appropriate for estimating ME from DE for diets containing between 2 and 4 Mcal of DE/kg. Digestible energy was converted to ME with slightly lower efficiency (76.9%) by dairy cows consuming grass hay at maintenance (Harlan et al., 1991); moreover, the TPH in our study had an average DE content (i.e., 2.01 Mcal/kg) at the bottom of the range indicated by Weiss (1993). Therefore, we used the DE-to-ME conversion factor of 0.80 suggested by Minson (1982) that was developed for forage-based diets. The major weakness of conversion factors like these is that they do not consider chemical differences between TPH that may have influenced ME content (e.g., content of phenolic derivatives).
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. The average feeding level in that database was 1.1 x maintenance, a value somewhat greater than that in our study. Few diets (<1%) with less than 1.91 Mcal of ME/kg were included. Weiss (1993) commented that the major limitation associated with the mathematical conversion of DE to NE values was a lack of measured ME and NE values from low-quality diets.
The average feeding level achieved in our experiment was calculated to be 0.7 x maintenance; however, a wide range (0.4 to 0.96 x maintenance) was observed. Harlan et al. (1991) reported similar ranges in energy intake relative to maintenance for grass hay fed in fixed daily portions. Clearly, the TPH samples used in our study were not uniform in terms of energy availability. Techniques for estimation of TPH energy content must be sensitive to differences in chemical makeup among TPH.
Gross energy content of TPH diets was a poor predictor of DE (r2 = 0.39, Sy*x = 0.18; Table 5). This was expected because of slight variation in GE content among TPH samples. Conversely, intake of digestible OM (g/kg of BW0.75) predicted DE (Mcal/kg) with a high degree of accuracy (r2 = 0.91, Sy*x = 0.07). Although nearly as difficult to measure directly as DE, DM digestion (DMD) and OM digestion (OMD) have been used to estimate forage DE (Moir, 1961; Rittenhouse et al., 1971; Minson, 1982). Digestion of DM and OM were good predictors of DE (r2 > 0.9; Sy*x 
0.06) in our study. The accuracy of these equations was similar to those published previously (Moir, 1961; Rittenhouse et al., 1971). Digestion of NDF accounted for most of the variation in DE (r2 = 0.63, Sy*x = 0.14; Table 5), but was less accurate at predicting DE than DMD or OMD. Rittenhouse et al. (1971) and Minson (1982) showed OMD to be a slightly superior predictor of DE compared with DMD. In our study, DMD and OMD predicted DE with similar accuracy. Additionally, Rittenhouse et al. (1971) commented that prediction of DE from DMD or OMD was not affected by supplementation.
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; Harlan et al., 1991; Weiss, 1993).
When constructing regression models to predict forage DE from chemical composition, it is desirable that independent variables be related causally to DE (i.e., independent of sample population). Causal relationships can be difficult to establish definitively; therefore, empirical models are most reliable when developed and used for a single forage type (Abrams, 1988; Weiss et al., 1992).
For this reason, use of generalized empirical models (i.e., those intended for use with several forage types) has been discouraged in favor of summative, theoretical models. Summative models that are based on digestion coefficients for various chemical fractions of feed are the most theoretically sound method of estimating energy supply from a variety of feedstuffs (Goering and Van Soest, 1970; Conrad et al., 1984; NRC, 2001). The summative approach also has limitations. First, digestion of one or more chemical components must be known or estimated (Weiss, 1993). Second, measurement of digestion coefficients is time consuming and expensive. Empirical estimation of forage DE is appealing for reasons of simplicity, speed, and relatively inexpensive measurement of independent variable values (Harlan et al., 1991). Furthermore, prediction of energy availability using theoretical models and forage-specific empirical models yielded similarly accurate results (Conrad et al., 1984).
Neither empirical nor theoretical models consider the influences of associative effects or intake on the energy yield from forages. In most cases, it is desirable to provide adjustments for these factors. For the purposes of predicting the energy values of low-protein forages, associative effects relating to protein supplementation should arguably be regarded as a part of normal feeding practices and, therefore, factored into the model by default. Conversely, level of intake must be considered separately because of the wide range in DMI that might occur because of physiological state or a management imposition.
Regression models developed to predict dietary DE (Mcal/kg) from forage chemical composition values are depicted in Figure 1. Forage ABL was the best single predictor of DE (Figure 1a):
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 | [1] |
Forage ABL accounted for most the variation in DE content of TPH (r2 = 0.57) and Sy*x was reasonably small (0.15). Single-component regression models seldom explain most of the fluctuation in energy availability (Weiss, 1993).
The use of lignin measurements in empirical regression models has been criticized because lignin does not meet the minimum criteria for a uniform feed fraction: consistent digestion, absorption, and content in metabolic end products (Goering and Van Soest, 1970; Weiss, 1993). Nonetheless, lignin measurements have been used as a predictor of forage energy, particularly with low-quality forages, owing to the strength of the statistical relationship between lignin and energy content (Minson, 1982; Donker, 1989; Givens et al., 1990; Harlan et al., 1991; Undersander et al., 1993). Several commercial feed-testing laboratories use empirical equations to predict DE, TDN, or DMD based on some measure of lignin (Undersander et al., 1993; Weiss, 1993).
Multiple regression models (i.e., 2 to 5 independent variables) relating the chemical composition of TPH to DE content are shown in Figures 1b through 1e. The coefficient of determination (R2) associated with multiple regression models usually increases with the number of independent variables included (Neter and Wasserman, 1974). As such, the improvement in R2 may only be a statistical artifact and not a true indicator of absolute accuracy (Weiss, 1993). This makes direct comparisons of our models with the work of others inadvisable; however, relative accuracy of equations generated from a single population of forages, as in the present study, may be contrasted using both R2 and Sy*x.
Most the variation in DE content of TPH was explained by the optimal 2-variable model, which included forage CP and ADL content (R2 = 0.73, Sy*x = 0.13; Figure 1b):
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The appearance of ADL in the 2-variable model was surprising; ABL was more strongly related than ADL to DE (r = –0.75 vs. –0.67). A possible reason for this observation was that there was a lower correlation between CP and ADL (r = –0.23) than between CP and ABL (r = –0.60). Intercorrelation generally weakens predictive power of a multiple regression model (Steel and Torrie, 1980). Another possible reason for the replacement of ABL with ADL in the model was that the range in forage ADL was relatively wide compared with ABL (Table 1). Goodness-of-fit is usually improved when the range of independent variables is wide instead of narrow (Neter and Wasserman, 1974; Weiss, 1993).
Further improvements in fit and reductions in Sy*x were observed when the iterative modeling process was carried to its conclusion. The Sy*x continued to decline somewhat up to the addition of a fifth variable to the model. Thereafter, it increased slightly.
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 | [4] |
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As evidenced from the plots in Figure 1, little bias was associated with prediction of the DE content of TPH. Deviation of the regression line from the isopleth appeared to be small for all regression models. It remains to be seen which of the proposed regression models will be most practical to use. Equations 1 and 2 have the advantage of simplicity but may not encompass sufficient variation in DE. Equations 4 and 5 appear more accurate than simpler models; however, they require more time and money to generate input variables and may be over-parameterized in relation to the small number of TPH samples in our database.
The TDN content (at 1 x maintenance) of the TPH samples in our database was predicted using a summative equation (NRC, 2001; Eq. 2–5). These estimates were subsequently converted to DE (NRC, 2001; Eq. 2–1). The summative equation required 7 inputs (DM basis): ash, CP, ether extract, NDF, neutral detergent-insoluble CP, acid detergent-insoluble CP, and ADL. These inputs were used to estimate truly digestible nonfiber carbohydrate, truly digestible CP for forages, truly digestible fatty acids, and truly digestible NDF. Predictive capabilities of the summative equation with the TPH samples in our database were poor compared with the regression equations presented above, in contrast to the report by Conrad et al. (1984; Figure 2). There are at least 2 reasons for this. First, the summative model is based on a theoretical TDN calculation; TDN calculations generally overestimate the value of low-quality forages (Weiss, 1998). Second, predictive capabilities of the regression models were likely to appear relatively strong given that they were developed from the same database from which they were used to predict DE. It should also be noted that all of the regression equations proposed above predicted DE of TPH with fewer compositional inputs than the summative equation.
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Fecal energy is generally regarded as the largest and most variable loss of intake energy in ruminant diets. One of the primary causes of variation in fecal energy loss, and thus DE, is level of intake (Brown, 1966). Intake of GE, forage OM, total OM, and digestible OM by steers during trial 2 increased linearly (P < 0.01) with forage feeding level (Table 6). Digestion of DM, OM, NDF, and GE decreased linearly (P < 0.01) as forage intake increased; however, there were tendencies for DM digestion, NDF digestion, and DE (P = 0.09, 0.17, and 0.10, respectively) to respond cubically to forage intake. Diet DE (Mcal/kg) responded to forage intake level similarly (linear, P < 0.01; cubic, P = 0.10). The decline in digestion that occurred between the 1.7 and the 2.1% BW daily feeding levels was of slightly greater magnitude than that which occurred between 1.3 and 1.7% of BW daily or between 2.1 and 2.5% of BW daily.
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; Colucci et al., 1982; Edionwe and Owen, 1989); however, the effect of intake on digestion varied considerably between individual feedstuffs and diets (Colucci et al., 1982; Edionwe and Owen, 1989; Weiss, 1993). Tyrrell and Moe (1975) noted that the magnitude of depression in dietary fiber digestion may be greater than that of other feed components in response to increased intake (Tyrrell and Moe, 1975). Depression in DM, OM, and NDF digestion were of similar magnitude in our study.
Intakes in trial 2 were estimated to range approximately from 1 to 2 x maintenance feeding (Figure 3). As DMI increased between 1 and 2 x maintenance, depression in digestion was similar for DM, OM, NDF, and GE. Digestion of GE was estimated to decrease 7.4% between 1 and 2 x maintenance intake (Figure 3d). Similarly, DM digestion, OM digestion, and NDF digestion decreased approximately 8.4, 8.0, and 9.2% between 1 and 2 x maintenance intake (Figures 3a, 3b, and 3c). Relationships between intake level and DM, OM, and GE digestion were strong (r2 = 0.86, 0.85, and 0.81, respectively); however, intake level did not explain most the variation in NDF digestion (r2 = 0.50).
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who found that DM digestion of a corn silage-soyhull diet decreased approximately 7% per multiple of maintenance intake. Apparent digestion of growing and finishing rations (i.e., 50 to 75% concentrate) decreased an average of 4% for each multiple of maintenance intake (Moe et al., 1965). Using the adjustment of Moe et al. (1965), the NRC (1981) recommended decreasing tabular TDN values by a total of 8% when feeding at levels consistent with normal production (i.e., 2 to 3.5 x maintenance). Conversely, Edionwe and Owen (1989) reported that digestion of mixed diets (1:1 forage to concentrate) was depressed to a much greater degree per unit of maintenance intake (9.3 to 11.2%). Conclusions
Digestible energy content of TPH-based diets fed at 1.5% BW (i.e., an average of 0.7 x maintenance) varied with chemical composition and ranged from 1.56 to 2.32 Mcal/kg. Empirical prediction equations based on chemical composition explained most variation in DE content. Digestible energy decreased 7.4% between 1 and 2 x the maintenance feeding level of TPH. These results were interpreted to suggest that tabular energy values for native forages are probably inappropriate. Energy availability can be defined in dynamic terms using forage-specific empirical models with consideration for the effects of intake level. Knowledge of the capability of native forages to support productive functions in beef cattle is incomplete; therefore, further characterization of the energy content of native forages is warranted.
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Footnotes |
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3 Present address: New Mexico State University, Box 3003, MSC 3AE, Las Cruces, NM 88003.
4 Present address: 625 Colorado, Elkhart, KS 67950.
5 Present address: 260531 Co. Rd. S, Gering, NE 69341.
2 Corresponding author: kcolson{at}ksu.edu
Received for publication September 5, 2007. Accepted for publication February 12, 2008.
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LITERATURE CITED |
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TopAbstractINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONLITERATURE CITED |
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