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Department of Animal Science, Michigan State University, East Lansing 48824-1225
Corresponding author:
M. S. Allen; e-mail:
allenm{at}pilot.msu.edu.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONACKNOWLEDGEMENTSREFERENCES |
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Key Words: conservation method of corn • energy spilling • microbial N • microbial efficiency • rate of passage
Abbreviation key: TRDOM = true ruminally degraded OM, HM = high moisture corn, DG = dry ground corn, NANMN = nonammonia nonmicrobial nitrogen
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONACKNOWLEDGEMENTSREFERENCES |
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Although microbial protein production is often limited by energy supplied from OM fermentation in the rumen, efficiency of microbial N production varies significantly. Microbial efficiency, defined as g of microbial N passing to the duodenum per kilogram of true ruminally degraded OM (TRDOM), ranges more than twofold (Clark et al., 1992). Clark et al. (1992) found a quadratic relationship between TRDOM and microbial efficiency, suggesting factors other than TRDOM affect microbial protein synthesis. Energy spilling or energy uncoupling refers to energy that is wasted for nongrowth functions, and increases with low ruminal pH (Strobel and Russell, 1986) or lack of degradable N (Ricke and Schaefer, 1996). Bacteria fermenting nonstructural carbohydrates may decrease microbial efficiency when peptides or amino acids are insufficient (Russell and Sniffen, 1984). Faster rate of passage was also shown to be positively related to microbial efficiency (Oba and Allen, 2000).
Although various factors affecting microbial efficiency in vitro have been reported, the effect of diet fermentability on microbial efficiency in vivo has not been consistent (Overton et al., 1995; Plascencia and Zinn, 1996; Crocker et al., 1998; Knowlton et al., 1998; Callison et al., 2001). Production of microbial N in the rumen is often limited by fermentable energy, but diet fermentability might directly and indirectly affect microbial efficiency by altering ruminal pH or rate of passage. Fermentability of diets is primarily affected by the concentration and fermentability of starch. Corn grain is the major source of dietary starch for lactating dairy cows in the United States. It is often fed as high moisture corn (HM) or dry ground corn (DG), and HM has greater starch degradability in the rumen (Ying et al., 1998). The objective of this experiment was to evaluate the effect of diet fermentability altered by feeding HM and DG at two concentrations of dietary starch on efficiency of microbial N production.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONACKNOWLEDGEMENTSREFERENCES |
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Treatments and Cows
Eight multiparous Holstein cows (55 ± 15.9 DIM; mean ± SD) from the Michigan State University Dairy Cattle Teaching and Research Center were randomly assigned to treatment sequence within a duplicated 4 x 4 Latin square balanced for carryover effects with a 2 x 2 factorial arrangement of treatments. Factors evaluated were dietary starch concentration (21 vs. 32%) and conservation method of corn grain (HM vs. DG). Treatment periods were 21 d, with the final 10 d used to collect samples and data. Cows were cannulated ruminally and duodenally before calving. Duodenal cannulas were soft gutter type made of Tygon and vinyl tubing (Crocker et al., 1998). The duodenum was fistulated between the pylorus, and the pancreatic duct and cannulas were placed between 10th and 11th ribs as described by Robinson et al. (1985). Surgeries were performed at the Department of Large Animal Clinical Science, College of Veterinary Medicine, Michigan State University. At the beginning of the experiment, empty BW (ruminal digesta removed) of cows were 565.5 ± 58.5 kg (mean ± SD).
One corn hybrid (Pioneer 3730; Pioneer Hi-bred International, Inc., Johnston, IA) was grown in 1998, and half of the field was harvested as HM at a DM concentration of 63.2%. The HM was ground to mean particle size of 1863 µm and ensiled in a 2.4- x 9.0-m silage bag (Ag Bagger, Ag Bag Corp., Blair, NE). The remaining half of the field was harvested as dry corn at 89.7% of DM. Dry corn was finely ground to a mean particle size of 885 µm. Nutrient composition for corn grain treatments is shown in Table 1
. Experimental diets contained HM corn or DG corn, corn silage (50% of forage DM), alfalfa silage (50% of forage DM), a premix of protein supplement (soybean meal, distillers grains, and blood meal), and a premix of minerals and vitamins (Table 2). All diets were formulated for 18% dietary CP concentration, and fed as a TMR.
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Ruminal pH was monitored from d 16 through 19 (96 h) of each period by a computerized data acquisition system (Dado and Allen, 1993). Ruminal pH data were recorded for each cow every 5 s. Electrodes for ruminal pH determination were checked daily and calibrated as needed, and ruminal pH data were deleted for the entire day if pH drifted more than 0.1 unit at pH 7 and 4. The system successfully collected 90.6% of the total ruminal pH data (69,120 observations per cow per period). Daily mean, minimum, maximum, variation range, time below pH 6.0, 5.8, and 5.5, and area below the pH 6.0, 5.8, and 5.5 were calculated. Response variables were averaged over 4 d for each period.
Chromic oxide was used as a marker to estimate nutrient digestibility in the rumen and in the total tract. Gelatin capsules (1.5 oz. Tropac Inc., Airfield, NJ) containing 5 g of chromic oxide and ground spelt hulls (Wiley mill, 2-mm screen; Authur H. Thomas, Philadelphia, PA) were dosed through the rumen cannula at 0600, 1400, and 2200 h (total of 15 g of Cr2O3/d) from 7 to 14 d with the priming dose of 3X on d 7. Duodenal samples (1000 g per a cow) and fecal samples (500 g) were collected every 9 h from 12 to 14 d so that eight samples were taken for each cow, representing every 3 h of a 24-hour period to account for diurnal variation. Ruminal contents were sampled near the reticulo-omasal orifice every 4 h on d 15 to obtain a microbial pellet. Samples were immediately frozen at -20°C.
Sample and Statistical Analysis
All samples were composited to one sample per cow per period before drying. Dudodenal samples were composited and separated into primarily solid and liquid phases with four layers of cheesecloth. Both phases were weighed, the ratio of each phase was determined, and subsamples were taken from both phases according to the ratio determined for each sample to minimize sampling errors due to segregation of samples into solid and liquid phases. Diet ingredients, orts, and feces were dried in a 55°C forced-air oven for 72 h and analyzed for DM concentration. Ruminal digesta, duodenal samples, and microbial pellets obtained after differential centrifugation of ruminal fluid (Overton et al., 1995) were lyophilized (Tri-Philizer MP; FTS Systems, Stone Ridge, NY). All samples were ground with a Wiley mill (1-mm screen; Authur H. Thomas). Samples were analyzed for ash, NDF, ADF, lignin, indigestible NDF, CP, and starch. Ash concentration was determined after 5 h of oxidation at 500°C in a muffle furnace. Concentrations of NDF and ADF were determined [(Van Soest et al., 1991); method A for NDF]. Crude protein was analyzed according to Hach et al. (1985). Starch was measured by an enzymatic method (Karkalas, 1985) after samples were gelatinized with sodium hydroxide, and glucose concentration was measured using glucose oxidase (Glucose kit #510; Sigma Chemical Co., St. Louis, MO) and absorbance was determined with micro-plate reader (SpectraMax 190; Molecular Devices Corp., Sunnyvale, CA). Indigestible NDF was estimated as NDF residue after 120-h in vitro fermentation (Goering and Van Soest, 1990). Ruminal fluid for the in vitro incubations was collected from a nonpregnant dry cow fed alfalfa hay only. Concentrations of all nutrients except for DM were expressed as percentages of DM determined by drying at 105°C for more than 8 h in a forced-air oven. Corn grain treatments were dry sieved through eight sieves (sieve apertures: 4750, 2360, 1180, 600, 300, 150, 75 µm and bottom pan), using a sieve shaker (model RX-86; W.S. Tyler Inc., Gastonia, NC) for approximately 20 min until the bottom pan weight was constant, and mean particle size of corn grain was calculated (ASAE, 1968).
Duodenal digesta and fecal samples were analyzed for concentrations of Cr. Samples were digested with phosphoric acid (Williams, 1962), and quantified by flame atomic absorption spectrometry (SpectraAA 220; Varian, Victoria, Australia) according to manufacturer’s recommendation. Ruminal pool sizes (kg) of DM, OM, NDF, indigestible NDF, and starch were determined by multiplying the concentration of each component by the ruminal digesta DM weight (kg) except for DM. Turnover rate in the rumen, passage rate from the rumen, and ruminal digestion rate of each component (%/h) were calculated (Oba and Allen, 2003b)
Purines concentration was used as a microbial marker, and total purines were measured by spectrophotometer (Beckman Instruments, Inc., Fullerton, CA) at 260 nm (Zinn and Owens, 1986). Ratios of purines to microbial N, starch, and OM were determined for microbial pellets. Duodenal digesta were analyzed for purine concentration, and duodenal flow of microbial N, starch, and OM were calculated by multiplying the ratios obtained from microbial pellets. Duodenal samples were analyzed for ammonia concentration to estimate nonammonia N and nonammonia nonmicrobial N flow to the duodenum. Dried duodenal digesta samples were hydrated for 20 min to extract ammonia N retained in samples. Ammonia concentration was determined for the duodenal samples and the centrifuged rumen fluid according to Broderick and Kang (1980).
All data were analyzed using the fit model procedure of JMP (version 4, SAS Institute, Cary, NC) according to the following model:
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where
µ = overall mean,
Ci = random effect of cow (i = 1 to 8),
Pj = fixed effect of period (j = 1 to 4),
Tk = fixed effect of treatment (k = 1 to 4), and
eijkl = residual, assumed to be normally distributed.
Period x treatment interaction was originally evaluated, but it was removed from the statistical model because interaction was not significant. Orthogonal contrasts were made for the effect of dietary starch concentration, conservation method of corn grain, and interaction of dietary starch concentration and conservation method. Treatment effects and their interaction were declared significant at P < 0.05 and P < 0.10, respectively, and tendency for treatment effects were declared at P < 0.10. When interactions of main effects were significant, treatment means were compared using Student’s t-test and differences were declared significant at P < 0.05.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONACKNOWLEDGEMENTSREFERENCES |
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) and for HM treatment compared with DG treatment (P < 0.03). Treatment means for TRDOM varied from 7.7 kg/d for DG treatment in low starch diets to 11.3 kg/d for HM treatment in high starch diets, which is within the range reported by Allen (1997) for lactating dairy cows: 9.8 ± 2.1 kg/d. Ammonia concentration in the rumen was greater for low starch diets compared with high starch diets (P < 0.02), although N intake was less for low starch diets compared with high starch diets (P < 0.01). This cannot be attributed to decreased ruminal degradation of feed protein for high starch diets. Nonammonia nonmicrobial N (NANMN) flow to the duodenum as a percentage of N intake tended to be lower for high starch diets compared to low starch diets (P < 0.08), and NANMN flow (g/d) was numerically lower for high starch diets (P = 0.16). The lower ruminal ammonia concentration observed for high starch diets in this experiment can be attributed to increased utilization of ruminally degraded N for microbial protein synthesis for high starch diets. Microbial N flow was greater for high starch diets compared with low starch diets (P < 0.01). Microbial N production was probably limited by the energy available from fermentable substrates for low starch diets.
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Microbial Efficiency
Microbial N flow to the duodenum was greater for high starch diets compared with low starch diets, which can be explained by greater TRDOM for high starch diets. Microbial N flow was positively related to TRDOM across cow-period observations for this experiment (Figure 1). Although efficiency for microbial N production, defined as grams of microbial N flow at the duodenum per kilogram of TRDOM, was not affected by dietary starch concentration, it was greater for DG treatment compared with HM treatment (P < 0.03). Cows fed DG maintained a similar flow of microbial N as cows fed HM corn despite lower TRDOM. Although energy from OM fermentation in the rumen limits maximum microbial N production, microbial efficiency varies greatly (Clark et al., 1992). In this experiment, microbial efficiency decreased as TRDOM increased (Figure 2), indicating that factors other than availability of energy limited efficiency of microbial N production and that energy from OM fermentation was uncoupled from microbial growth.
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). No relationships were observed between microbial efficiency and daily mean ruminal pH (Table 5; Figure 3), daily minimum ruminal pH (Figure 4) or other expressions of ruminal pH (data not shown). Therefore, lower microbial efficiency for HM compared with DG treatment was because of factors unrelated to ruminal pH in this experiment. Russell and Wilson (1996) proposed that low ruminal pH decreases microbial growth by accumulation of intracellular VFA, but no relationship was observed between microbial efficiency and total VFA concentration in the rumen (P= 0.49) or undissociated total VFA concentration in the rumen (calculated from daily means of ruminal pH and VFA concentration; P = 0.18) for this experiment.
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). Decreased microbial efficiency for HM treatment was probably not from a deficiency of ammonia N in the rumen.
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Digestion Kinetics and Microbial Efficiency
Rate of starch digestion in the rumen was greater for HM treatments compared with DG treatments, and passage rate of OM and starch was greater for cows fed DG than for cows fed HM (Table 6). Microbial efficiency was positively correlated with rate of passage of OM and starch and negatively correlated with TRDOM and digestion rate of starch (Table 7) but was not correlated with digestion rate or passage rate of the potentially digestible NDF fraction. Although many microbial organisms flow from the rumen attached to fibrous particles, passage rate of NDF was not related to microbial efficiency possibly because differences in dietary starch sources and concentrations were the primary factors affecting microbial efficiency in this experiment. Microbial efficiency increased as digestion rate of starch decreased (Figure 6; three outliers were not influential observations for this relationship; DFFITS <0.8), indicating that energy from starch fermentation might not have been efficiently utilized for microbial growth as rate of starch digestion increased. As discussed above, this might be because of a deficiency of amino acids, peptides, or any unknown growth factors. In addition, maximum rate of fermentation might have exceeded the maximum growth rate of the microbial population.
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), indicating that energy from ruminal fermentation was more efficiently utilized for microbial growth as passage rate for starch and OM increased. This is consistent with previous observations in vitro. Isaacson et al. (1975) evaluated efficiency of microbial growth in a glucose medium at dilution rates of 0.02, 0.06, and 0.12 h-1, and found YATP (g of microbial cell production per mole of ATP) increased as the dilution rate increased. Greater dilution rate decreased degradation and turnover of microbes in the rumen (Stouthamer and Bettenhaussen, 1973; Kennedy and Milligan, 1978), and greater passage rate of ruminal digesta possibly decreases microbial lysis and turnover in the rumen. Extensive microbial turnover in the rumen due to predation by protozoa also reduces microbial efficiency (Wallace and McPherson, 1987). Microbial efficiency can be divided into two factors: efficiency of microbial N production in the rumen and efficiency of microbial N passage.
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Because host animals can absorb microbial N only if it flows to the duodenum, rate of microbial N flow from the rumen is an important factor determining microbial efficiency. If rate of passage is decreased, energy supplied from OM fermentation in the rumen is wasted due to microbial turnover in the rumen.
Our results related to microbial efficiency for this experiment should be interpreted with caution. Microbial efficiency was greater than 70 g of microbial N per kilogram of TRDOM for three observations, but these high values of microbial efficiency might not be physiologically possible as discussed below. These three observations were all from DG treatments (one from high starch diet and two from low starch diet). Therefore, if these high values of microbial efficiency are caused by sampling error or problems associated with a single marker method to calculate duodenal flow, they might have caused bias that exaggerates treatment effects on microbial efficiency. Treatment means for observed microbial efficiency were also high in this experiment, ranging from 39.3 to 49.4 g of microbial N per kilogram of TRDOM. Our data fit within the range of variation reported in the literature (Clark et al., 1992), which is from less than 20 to 50 g of microbial N flow at the duodenum per kg of TRDOM. However, our methods might have overestimated microbial N flow at the duodenum because our values were greater than the theoretical maximum microbial efficiency, calculated as 31.3 g of microbial N/kg of TRDOM. The theoretical calculation requires partitioning of microbial efficiency into two factors: efficiency of microbial ATP production and efficiency of microbial N production.
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One mole of hexose equivalent TRDOM can generate up to 4 moles of ATP when it ferments to VFA (Harrison and McAllan, 1980), and theoretical maximum YATP was shown to be approximately 26 g of microbial cell/mole of ATP based on biochemical calculations (Hespell and Bryant, 1979). Assuming microbial cells are 8% N (Clark et al., 1992), one mole of hexose equivalent TRDOM can produce up to 8.3 g of microbial N (which equals to 51 g of microbial N/kg of TRDOM: 1 kg of TRDOM/(162 g of glucose per mole before hydrolysis) x 8.3 g/mole). However, maximum microbial efficiency can be limited by the efficiency of microbial ATP production (moles of ATP/kg of TRDOM). Less substrate is available for microbial ATP production as microbial cell production increases because TRDOM is conserved as fermentation end products and microbial cells. The partitioning of TRDOM into microbial cell synthesis and fermentation end product synthesis by which microbial ATP is generated at a maximum microbial efficiency is expressed in the following equation. Solving this equation for MN gives the theoretical maximum microbial efficiency of 31.3 (g of microbial N/kg of TRDOM).
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where
MN = microbial N, g
1000 = TRDOM (g)
0.08 = N concentration in microbial cells
162 = molecular weight of hexose equivalent (g/mole)
4 = ATP production per mole of hexose (moles/mole of hexose)
26 = microbial cell production per mole of ATP (g/mole of ATP)
We observed high microbial efficiency that is close to 50 g of microbial N/kg of TRDOM for DG treatments, but this high level of microbial efficiency would require approximately 8 moles of ATP production from one mole of hexose-equivalent TRDOM. This is not theoretically acceptable, and the reasons for disagreement between the observed data and the theoretical maximum values are not known. However, efficiency of microbial ATP production is not well established because measured microbial ATP production has not been reported in the literature. Microbial production of VFA is associated with formation of reducing equivalents as well as ATP production. Although it has been generally assumed that anaerobic bacteria do not possess phosphorylation systems linked to electron transport, this has been argued (Russell and Wallace, 1997). Utilization of energy conserved in reducing equivalents for microbial growth might explain our observations. Further research is needed to understand energy metabolism of anaerobic bacteria.
Purines were used as a microbial marker in this experiment, and microbial N flow was determined by N:purines ratio in microbial pellets and concentration of purines in duodenal digesta. The N:purines ratio in our experiment (1.16) is close to the mean value of 1.06 reported in the literature by Clark et al. (1992), but microbial efficiency could be overestimated if the N:purines ratio in microbial pellets is higher than actual MN:purines ratio in duodenal digesta. In addition, contamination of purines from other sources, if occurred, possibly increased analyzed microbial N flow because our methods assumed that duodenal digesta contains no purines originating from either feeds or epithelial cells of the digestive tract. We do not know whether theoretical calculation underestimated actual microbial efficiency or whether our analytical methods overestimated microbial efficiency.
Another possible explanation for relatively high microbial efficiency observed in this experiment is overestimation of duodenal DM flow. In a companion paper, we mentioned the possibility of underestimation in ruminal NDF digestibility from overestimation of duodenal NDF flow, which might have been because of an overestimate of duodenal DM flow because of potential marker flow problems. Overestimated duodenal DM flow (including NDF and microbial cells) relative to flow of chromic oxide would result in an underestimate of ruminal DM (including NDF) digestibility, and an overestimate of microbial N yield and efficiency of microbial N production. To minimize this problem, we sampled from the duodenum fewer times (but distributed evenly throughout the day) and took larger samples than in some other studies. Although it is impossible to identify whether sampling errors occurred, we acknowledge this possibility.
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CONCLUSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONACKNOWLEDGEMENTSREFERENCES |
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ACKNOWLEDGEMENTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONACKNOWLEDGEMENTSREFERENCES |
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FOOTNOTES |
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Received for publication March 18, 2002. Accepted for publication June 11, 2002.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONACKNOWLEDGEMENTSREFERENCES |
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