R.A. Kohn

Corn silage versus corn silage:alfalfa hay mixtures for dairy cows: Effects of dietary potassium, calcium, and cation-anion difference

Corn silage (CS) has replaced alfalfa hay (AH) and haylage as the major forage fed to lactating dairy cows, yet many dairy producers believe that inclusion of small amounts of alfalfa hay or haylage improves feed intake and milk production. Alfalfa contains greater concentrations of K and Ca than corn silage and has an inherently higher dietary cation-anion difference (DCAD). Supplemental dietary buffers such as NaHCO(3) and K(2)CO(3) increase DCAD and summaries of studies with these buffers showed improved performance in CS-based diets but not in AH-based diets. We speculated that improvements in performance with AH addition to CS-based diets could be due to differences in mineral and DCAD concentrations between the 2 forages. The objective of this experiment was to test the effects of forage (CS vs. AH) and mineral supplementation on production responses using 45 lactating Holstein cows during the first 20 wk postpartum. Dietary treatments included (1) 50:50 mixture of AH and CS as the forage (AHCS); (2) CS as the sole forage; and (3) CS fortified with mineral supplements (CaCO(3) and K(2)CO(3)) to match the Ca and K content of the AHCS diet (CS-DCAD). Feed intake and milk production were equivalent or greater for cows fed the CS and CS-DCAD diets compared with those fed the AHCS diet. Fat percentage was greater in cows fed the CS compared with the AHCS diet. Fat-corrected milk (FCM; 3.5%) tended to be greater in cows fed the CS and CS-DCAD diets compared with the AHCS diet. Feed efficiencies measured as FCM/dry matter intake were 1.76, 1.80, and 1.94 for the AHCS, CS, and CS-DCAD diets, respectively. The combined effects of reduced feed intake and increased FCM contributed to increased feed efficiency with the CS-DCAD diet, which contained 1.41% K compared with 1.18% K in the CS diet, and we speculate that this might be the result of added dietary K and DCAD effects on digestive efficiency. These results indicate no advantage to including AH in CS-based diets, but suggest that improving mineral supplementation in CS-based diets may increase feed efficiency.

A fecal test for assessing phosphorus overfeeding on dairy farms: evaluation using extensive farm data.

Managing P on dairy farms requires the assessment and monitoring of P status of the animals so that potential overfeeding may be minimized. Numerous published studies have demonstrated that for lactating dairy cows, increasing P concentrations in diets led to greater P excretion in feces. More recent work reported that inorganic P (P(i)) in 0.1% HCl extracts of feces (fecal extract P(i), g/kg) closely reflects dietary P changes. This has led to the proposal that 0.1% HCl fecal extract P(i) may serve as an indicator of the animals P status (adequate or excessive) when compared with a benchmark value. Here, we present the results of an extensive evaluation of the proposed fecal P indicator test. With samples (n=575) from >90 farms, fecal total P (TP, g/kg) and fecal extract P were positively correlated with dietary P (X, g/kg): TP=1.92X - 0.17 (R2=0.36); fecal extract P=1.82X - 2.54 (R2=0.46). Fecal extract P was responsive to dietary P changes, whereas the remaining P, calculated as TP minus fecal extract P, was not. A provisional benchmark value of fecal extract P representing near-adequate P status was set at 4.75g/kg. Assessment of the farm data using the benchmark indicated that 316 out of 575 data points were associated with possible P overfeeding. Advantages of the fecal-based test over feed-based analysis to assess P status are discussed. The fecal extract P method is a simple and practical test that can be used as an assessment tool for helping dairy producers improve P management and reduce their environmental footprint.

Modeling Nutrient Fluxes and Plasma Ketone Bodies in Periparturient Cows

A mechanistic model was developed to study the interrelationship between glucose and lipid metabolism in periparturient cows. The driving variables were dry matter intake, feed composition, calf birth weight, milk production, and milk components. The response variables were body fat content and concentrations of plasma glucose, glycerol, nonesterified fatty acids (NEFA), and total ketone bodies (KB). Fetal growth and milk synthesis were assigned the highest priority for glucose demand in the model. The rate of fat mobilization was expressed as a function of glucose deficiency. The model assumed first-order kinetics for utilization of NEFA and KB. Model prediction errors were 19, 43, 48, and 36% of mean predictions for glucose, glycerol, NEFA, and KB, respectively. A linear bias was observed in KB and glycerol predictions. The model may be useful for understanding and explaining ketosis development.

Evaluation of a mechanistic model of glucose and lipid metabolism in periparturient cows.

A mechanistic model was previously developed to quantitatively describe glucose and lipid metabolism in periparturient cows. The objectives of the current study were to evaluate the accuracy and precision of the model by comparing predictions to data collected in an independent experiment; to identify the critical metabolic processes for ketosis development; and to use the model to evaluate the relative importance of dry matter intake, calf birth weight, milk yield, and body condition score on nutrition management. Residuals (observed - predicted) were regressed on model predictions using the independent data for the model inputs, and prediction error was calculated. Each model parameter (e.g., the rate of glucose consumption by peripheral tissues) was increased independently by 1 standard deviation to identify the critical metabolic processes for ketosis development. Critical control points to prevent ketosis were identified by increasing the driving variables of the model by 1 standard deviation to estimate the response in ketone body formation. The root mean square prediction error was 0.527 mM for ketone body predictions. The sensitivity analysis indicated that in the first few days of lactation, the rate of nonesterified fatty acid utilization had a greater effect on ketone body concentrations in periparturient cows than the other parameters tested in the model. The model was consistent with the knowledge that over-fattening during the prepartum period should be avoided to help prevent ketosis.

Impacts of ruminal microorganisms on the production of fuels: how can we intercede from the outside?

The ruminal microbiome rapidly converts plant biomass to short-chain fatty acids (SCFA) that nourish the ruminant animal host. Because of its high species diversity, functional redundancy, and ease of extraruminal cultivation, this mixed microbial community is a particularly accomplished practitioner of the carboxylate platform for producing fuels and chemical precursors. Unlike reactor microbiomes derived from anaerobic digesters or sediments, the ruminal community naturally produces high concentrations of SCFA, with only modest methane production owing to the absence of both proton-reducing acetogens and aceticlastic methanogens. The extraruminal fermentation can be improved by addition of ethanol or lactate product streams, particularly in concert with reverse β-oxidizing bacteria (e.g., Clostridium kluyveri or Megasphaera elsdenii) that facilitate production of valeric and caproic acids. Application of fundamental principles of thermodynamics allows identification of optimal conditions for SCFA chain elongation, as well as discovery of novel synthetic capabilities (e.g., medium-chain alcohol and alkane production) by this mixed culture system.

Composition, shell strength, and metabolizable energy of Mulinia lateralis and Ischadium recurvum as food for wintering surf scoters (Melanitta perspicillata)

Decline in surf scoter (Melanitta perspicillata) waterfowl populations wintering in the Chesapeake Bay has been associated with changes in the availability of benthic bivalves. The Bay has become more eutrophic, causing changes in the benthos available to surf scoters. The subsequent decline in oyster beds (Crassostrea virginica) has reduced the hard substrate needed by the hooked mussel (Ischadium recurvum), one of the primary prey items for surf scoters, causing the surf scoter to switch to a more opportune species, the dwarf surfclam (Mulinia lateralis). The composition (macronutrients, minerals, and amino acids), shell strength (N), and metabolizable energy (kJ) of these prey items were quantified to determine the relative foraging values for wintering scoters. Pooled samples of each prey item were analyzed to determine composition. Shell strength (N) was measured using a shell crack compression test. Total collection digestibility trials were conducted on eight captive surf scoters. For the prey size range commonly consumed by surf scoters (6–12 mm for M. lateralis and 18–24 mm for I. recurvum), I. recurvum contained higher ash, protein, lipid, and energy per individual organism than M. lateralis. I. recurvum required significantly greater force to crack the shell relative to M. lateralis. No difference in metabolized energy was observed for these prey items in wintering surf scoters, despite I. recurvum’s higher ash content and harder shell than M. lateralis. Therefore, wintering surf scoters were able to obtain the same amount of energy from each prey item, implying that they can sustain themselves if forced to switch prey.

Using the second law of thermodynamics for enrichment and isolation of microorganisms to produce fuel alcohols or hydrocarbons

Fermentation of crops, waste biomass, or gases has been proposed as a means to produce desired chemicals and renewable fuels. The second law of thermodynamics has been shown to determine the net direction of metabolite flow in fermentation processes. In this article, we describe a process to isolate and direct the evolution of microorganisms that convert cellulosic biomass or gaseous CO2 and H2 to biofuels such as ethanol, 1-butanol, butane, or hexane (among others). Mathematical models of fermentation elucidated sets of conditions that thermodynamically favor synthesis of desired products. When these conditions were applied to mixed cultures from the rumen of a cow, bacteria that produced alcohols or alkanes were isolated. The examples demonstrate the first use of thermodynamic analysis to isolate bacteria and control fermentation processes for biofuel production among other uses.

Representing interconversions among volatile fatty acids in the Molly cow model

The Molly cow model uses fixed stoichiometric coefficients for predicting volatile fatty acid (VFA) production from the fermented individual dietary nutrient fractions of forage and concentrate. We previously showed that predictions of VFA production had large errors and hypothesized that it was due to a lack of representation of carbon exchange among VFA. The objectives of the present study were to add VFA interconversion equations based on thermodynamics to the Molly cow model and evaluate the effect of these additions on model accuracy and precision of VFA predictions. Previously described thermodynamic equations were introduced to represent interconversions among VFA. The model was further modified to predict de novo acetate, propionate, and butyrate production coefficients based on forage-to-concentrate ratios rather than discrete, fixed sets of coefficients for forage-based, concentrate-based, and mixed diets. Both the original model and the modified one were reparameterized and evaluated against a common data set containing 8 studies reporting pH, VFA concentration, and VFA production rates using isotope dilution techniques and 62 studies reporting VFA concentrations and pH. Evaluations after parameter estimation revealed that predictions of VFA production rates were not improved, with root mean squared prediction errors (RMSPE) of 77, 60, and 51% for acetate, propionate, and butyrate, respectively, for the revised model versus 75, 63, and 55, respectively, for the original model. The RMSPE for predictions of VFA concentrations were reduced from 28, 46, and 40% to 22, 31, and 26% for acetate, propionate, and butyrate, respectively, simply by rederiving the VFA coefficients, but minimal further improvement was achieved with the addition of thermodynamically driven interconversion equations (RMSPE of 21, 32, and 27% for acetate, propionate, and butyrate, respectively). Thus, the results indicate that thermodynamically driven interchanges among VFA, as represented in this study, may not be a primary determinant for the accuracy of predictions of net production rates. Including the effect of pH on VFA absorption reduced the mean bias of propionate production and slope bias of acetate production, but not the overall RMSPE. The larger prediction errors for VFA production as compared with concentrations suggest the data quality may not be high, or that our representation of VFA production and absorption as well as ruminal digestion is inadequate. Additional data are required to discriminate among these hypotheses.

Use of thermodynamic equations to improve predictions of volatile fatty acid production by the Molly cow model

Volatile fatty acids are important products of fermentation in ruminant animals contributing about 72% of the total energy supply (Bergman, 1990). They also affect ruminal hydrogen supply, which dictates methane production. Therefore it is imperative to be able to accurately predict VFA production. The Molly cow model is a dynamic mechanistic model which uses stoichiometry coefficients derived by Murphy et al. (1982) to predict VFA production. The coefficients are based on the assumption that substrate supply is a primary determinant of VFA production rates, and interconversions are assumed to either not occur or be constant across diets. Our recent work demonstrated that the model poorly predicted VFA production rates and that accounting for variable interconversion rates may improve prediction accuracy. The objectives of this study were to incorporate VFA interconversion equations and evaluate them in the Molly cow model.