Inhibition of methanogenesis by nitrate, with or without defaunation, in continuous culture.

Within the rumen, nitrate can serve as an alternative sink for aqueous hydrogen [H2(aq)] accumulating during fermentation, producing nitrite, which ideally is further reduced to ammonium but can accumulate under conditions not yet explained. Defaunation has also been associated with decreased methanogenesis in meta-analyses because protozoa contribute significantly to H2 production. In the present study, we applied a 2 × 2 factorial treatment arrangement in a 4 × 4 Latin square design to dual-flow continuous culture fermentors (n = 4). Treatments were control without nitrate (-NO3-) versus with nitrate (+NO3-; 1.5% of diet dry matter), factorialized with normal protozoa (faunated, FAUN) versus defaunation (DEF) by decreasing the temperature moderately and changing filters over the first 4 d of incubation. We detected no main effects of DEF or interaction of faunation status with +NO3-. The main effect of +NO3- increased H2(aq) by 11.0 µM (+117%) compared with -NO3-. The main effect of +NO3- also decreased daily CH4 production by 8.17 mmol CH4/d (31%) compared with -NO3-. Because there were no treatment effects on neutral detergent fiber digestibility, the main effect of +NO3- also decreased CH4 production by 1.43 mmol of CH4/g of neutral detergent fiber degraded compared with -NO3-. There were no effects of treatment on other nutrient digestibilities, N flow, or microbial N flow per gram of nutrient digested. The spike in H2(aq) after feeding NO3- provides evidence that methanogenesis is inhibited by substrate access rather than concentration, regardless of defaunation, or by direct inhibition of NO2-. Methanogens were not decreased by defaunation, suggesting a compensatory increase in non-protozoa-associated methanogens or an insignificant contribution of protozoa-associated methanogens. Despite adaptive reduction of NO3- to NH4+ and methane inhibition in continuous culture, practical considerations such as potential to depress dry matter intake and on-farm ration variability should be addressed before considering NO3- as an avenue for greater sustainability of greenhouse gas emissions in US dairy production.

Energy requirements and efficiency of energy utilization in growing dairy goats of different sexes.

The aim of this study was to investigate the effects of sex on the requirements for maintenance and efficiency of energy utilization in growing Saanen goats. A database from 7 comparative slaughter studies that included 238 Saanen goats was gathered to provide information for the development of prediction equations of energy requirements for maintenance and efficiency of energy utilization. The experimental design provided different levels of metabolizable energy intake (MEI) and empty body weight (EBW). The data were analyzed so that sex (e.g., intact males, castrated males, and females; n = 98, 80, and 60, respectively) was a fixed effect, and blocks nested in the studies and goat sex were random effects. For the development of linear and nonlinear equations, we used the MIXED and NLMIXED procedures in SAS (SAS Institute Inc., Cary, NC). Nonlinear regression equations were developed to predict heat production (HP, kcal/kg0.75 of EBW; dependent variable) from MEI (kcal/kg0.75 of EBW; independent variable). Using the comparative slaughter technique, the net energy requirement for maintenance (NEM) was calculated as the value of HP at MEI equal to zero. Additionally, NEM was evaluated based on the degree of maturity. The metabolizable energy requirement for maintenance was calculated as the value at which HP is equal to MEI. Efficiency of ME utilization for maintenance (km) was calculated as the ratio between NEM and the metabolizable energy requirement for maintenance. Efficiency of energy utilization for growth (kg) was assumed to be the slope of the linear regression of retained energy (RE) on MEI above the maintenance stage (model intercept equal to 0). Efficiencies of RE as protein (kp) and as fat (kf) were calculated using the multiple linear regression of MEI above the maintenance (model intercept equal to 0) on RE as protein and as fat, respectively. Sex affected NEM (75.0 ± 1.76 kcal/kg0.75 of EBW for males and 63.6 ± 2.89 kcal/kg0.75 of EBW for females) and sex did not affect km (0.63). In contrast, sex no longer affected NEM when degree of maturity was considered on its estimation. The kg was different between sexes (0.31 for castrated males and females, and 0.26 for intact males), but kp (0.21) and kf (0.80) were similar between sexes. These results may be useful for improving robustness of the energy requirement recommendations for dairy goats.

Altering the ratio of dietary C16:0 and cis-9 C18:1 interacts with production level in dairy cows: Effects on production responses and energy partitioning.

The objective of our study was to evaluate the effects of altering the dietary ratio of palmitic (C16:0) and oleic (cis-9 C18:1) acids on nutrient digestibility, energy partitioning, and production responses of lactating dairy cows. Cows were blocked by milk yield and assigned to 3 groups (12 cows per group) in a main plot: low (45.2 ± 1.7 kg/d), medium (53.0 ± 1.6 kg/d), and high (60.0 ± 1.9 kg/d). Within each production group, a truncated Latin square arrangement of fatty acid (FA) treatments was used in 2 consecutive 35-d periods. The FA treatments supplemented at 1.5% of diet dry matter were (1) 80:10 (80% C16:0 + 10% cis-9 C18:1), (2) 73:17 (73% C16:0 + 17% cis-9 C18:1), (3) 66:24 (66% C16:0 + 24% cis-9 C18:1), and (4) 60:30 (60% C16:0 + 30% cis-9 C18:1). Treatment × production group interactions were observed for yields of milk, fat-corrected milk, energy-corrected milk, milk fat, milk protein, and milk lactose and energy partitioned to milk. Increasing cis-9 C18:1 in FA treatments reduced fat-corrected milk, energy-corrected milk, and milk energy output in low-producing cows but increased these in high-producing cows. Increasing cis-9 C18:1 in FA treatments did not affect milk yield, milk protein yield, and milk lactose yield in low- and medium-producing cows but increased these in high-producing cows. Regardless of production level, there was no effect of treatments on dry matter intake; however, increasing cis-9 C18:1 in FA treatments increased body weight change and body condition score change. Increasing cis-9 C18:1 in FA treatments increased total FA digestibility due to a linear increase in 16- and 18-carbon FA digestibilities. Interactions between FA treatments and production level were observed for the yield of milk fat and milk FA sources. In low-producing cows, increasing cis-9 C18:1 in FA treatments decreased milk fat yield due to a decrease in de novo and mixed milk FA without changes in preformed milk FA. In contrast, in high-producing cows, increasing cis-9 C18:1 in FA treatments increased milk fat yield due to an increase in de novo and preformed milk FA. Our results indicate that high-producing dairy cows (averaging 60 kg/d) responded better to a fat supplement containing more cis-9 C18:1, whereas low-producing cows (averaging 45 kg/d) responded better to a supplement containing more C16:0.

Effect of source of trace minerals in either forage- or by-product-based diets fed to dairy cows: 2. Apparent absorption and retention of minerals.

Eighteen multiparous cows were used in a split-plot replicated Latin square with two 28-d periods to evaluate the effects of source of supplemental Cu, Zn, and Mn (sulfates or hydroxy) on apparent absorption of minerals when fed in either a forage- or by-product-based diet. The by-product diets were formulated to have greater concentrations of NDF and lesser concentrations of starch, and specific ingredients were chosen because they were good sources of soluble fiber and ß-glucans, which bind trace minerals in nonruminants. We hypothesized that hydroxy trace minerals would interact less with digesta and have greater apparent absorption compared with sulfate minerals, and the difference in apparent absorption would be greater for the by-product diet compared with the forage-based diet. During the 56-d experiment, cows remained on the same fiber treatment but source of supplemental trace mineral was different for each 28-d period; thus, all cows were exposed to both mineral treatments. During each period cows were fed no supplemental Cu, Zn, or Mn for 16 d, followed by 12 d of feeding supplemental minerals from either sulfate or hydroxy sources. Supplemental minerals for each of the mineral sources fed provided approximately 10, 35, and 32 mg/kg of supplemental Cu, Zn, and Mn, respectively, for both fiber treatments. Total Cu, Zn, and Mn dietary concentrations, respectively, were approximately 19, 65, and 70 mg/kg for the forage diets and 21, 85, and 79 for the by-product diets. Treatment had no effect on dry matter intake (24.2 kg/d) or milk production (34.9 kg/d). Cows consuming the by-product diets had greater Zn (1,863 vs. 1,453 mg/d) and Mn (1,790 vs. 1,588 mg/d) intake compared with cows fed forage diets, but apparent Zn absorption was similar between treatments. Manganese apparent absorption was greater for the by-product diets compared with the forage diets (16 vs. 11%). A fiber by mineral interaction was observed for Cu apparent absorption, as cows fed hydroxy minerals with forage diets had greater apparent absorption compared with cows fed sulfate minerals; however, the opposite was observed with the by-product diets. Source of supplemental trace minerals and type of fiber in diets affected availability of Cu and Mn and should be considered in ration formulation.

Sex effects on net protein and energy requirements for growth of Saanen goats.

Requirements for growth in the different sexes remain poorly quantified in goats. The objective of this study was to develop equations for estimating net protein (NPG) and net energy (NEG) for growth in Saanen goats of different sexes from 5 to 45 kg of body weight (BW). A data set from 7 comparative slaughter studies (238 individual records) of Saanen goats was used. Allometric equations were developed to determine body protein and energy contents in the empty BW (EBW) as dependent variables and EBW as the allometric predictor. Parameter estimates were obtained using a linearized (log-transformation) expression of the allometric equations using the MIXED procedure in SAS software (SAS Institute Inc., Cary, NC). The model included the random effect of the study and the fixed effects of sex (intact male, castrated male, and female; n = 94, 73, and 71, respectively), EBW, and their interactions. Net requirements for growth were estimated as the first partial derivative of the allometric equations with respect to EBW. Additionally, net requirements for growth were evaluated based on the degree of maturity. Monte Carlo techniques were used to estimate the uncertainty of the calculated net requirement values. Sex affected allometric relationships for protein and energy in Saanen goats. The allometric equation for protein content in the EBW of intact and castrated males was log10 protein (g) = 2.221 (±0.0224) + 1.015 (±0.0165) × log10 EBW (kg). For females, the relationship was log10 protein (g) = 2.277 (±0.0288) + 0.958 (±0.0218) × log10 EBW (kg). Therefore, NPG for males was greater than for females. The allometric equation for the energy content in the EBW of intact males was log10 energy (kcal) = 2.988 (±0.0323) + 1.240 (±0.0238) × log10 EBW (kg); of castrated males, log10 energy (kcal) = 2.873 (±0.0377) + 1.359 (±0.0283) × log10 EBW (kg); and of females, log10 energy (kcal) = 2.820 (±0.0377) + 1.442 (±0.0281) × log10 EBW (kg). The NEG of castrated males was greater than that of intact males and lower than that of females. Using degree of maturity for estimating NPG and NEG, we could remove the differences between sexes. These results indicate that NPG and NEG differ among sexes in growing Saanen goats, and this difference should be accounted for by feeding systems. Including the degree of maturity as predictor cancels out those differences across sexes in protein and energy requirements.

Net mineral requirements of dairy goats during pregnancy.

Mineral requirements of pregnant dairy goats are still not well defined; therefore, we investigated the net Ca, P, Mg, Na and K requirements for pregnancy and for maintenance during pregnancy in two separate experiments. Experiment 1 was performed to estimate the net Ca, P, Mg, Na and K requirements in goats carrying single or twin fetuses from 50 to 140 days of pregnancy (DOP). The net mineral requirements for pregnancy were determined by measuring mineral deposition in gravid uterus and mammary gland after comparative slaughter. In total, 57 dairy goats of two breeds (Oberhasli or Saanen), in their third or fourth parturition, were randomly assigned to groups based on litter size (single or twin) and day of slaughter (50, 80, 110 and 140 DOP) in a fully factorial design. Net mineral accretion for pregnancy did not differ by goat breed. The total daily Ca, P, Mg, Na and K requirements for pregnancy were greatest in goats carrying twins (P<0.05), and the requirements increased as pregnancy progressed. Experiment 2 was performed to estimate net Ca, P, Mg, Na and K requirements for dairy goat maintenance during pregnancy. In total, 58 dairy goats (Oberhasli and Saanen) carrying twin fetuses were assigned to groups based on slaughter day (80, 110 and 140 DOP) and feed restriction (ad libitum, 20% and 40% feed restriction) in a randomized block design. The net Ca, P and Mg requirements for maintenance did not vary by breed or over the course of pregnancy. The daily net requirements of Ca, P and Mg for maintenance were 60.4, 31.1 and 2.42 mg/kg live BW (LBW), respectively. The daily net Na requirement for maintenance was greater in Saanen goats (11.8 mg/kg LBW) than in Oberhasli goats (8.96 mg/kg LBW; P<0.05). Daily net K requirements increased as pregnancy progressed from 8.73 to 15.4 mg/kg LBW (P<0.01). The findings of this study will guide design of diets with adequate mineral content for pregnant goats throughout their pregnancy.

Energy and protein requirements of weaned male and female Saanen goats.

The objective of this research was to estimate the energy and protein requirements for maintenance and growth in male (castrated and intact) and female Saanen goat kids between 15 and 30 kg BW. To determine the net energy requirements for maintenance (NEm ) and the net protein requirements for maintenance (NPm ), 75 goats (25 castrated and 26 intact males and 24 females) were used. Twenty-one goats (seven castrated and eight intact males and six females) were randomly assigned for slaughter to estimate the initial empty body composition. The 54 remaining animals (18 castrated and 18 intact males and 18 females) were randomly assigned in a split-plot design using a 3 × 3 factorial arrangement with three sexes and three levels of intake (ad libitum and restricted feed to 75% or 50% of the ad libitum intake). Within each sex, six blocks (three goats per block) were formed and one goat was randomly assigned to each level of intake. The 75% and the 50% of ad libitum rationing were determined daily, based on the DMI of the animal fed ad libitum on the previous day. All animals within block were slaughtered when the animal fed ad libitum reached 30 kg BW. The net energy requirements for gain (NEg ) and the net protein requirements for gain (NPg ) were obtained using 58 animals (20 castrated and 20 intact males and 18 females). The animals were fed ad libitum and slaughtered at targeted BW (15, 23 or 30 kg). Sex did not affect NEg and NPm (277.8 kJ/kg0.75  BW day and 2.98 g CP/kg0.75  BW day respectively), as well as NPg (180.9 ± 6.48 g/kg EBW gain) in Saanen goat kids. However, castrated males and females had similar NEg (varied from 12.6 ± 0.424 to 17.9 ± 1.38 MJ/kg EBW gain), greater than intact males (varied from 9.74 ± 0.420 to 10.7 ± 0.984 MJ/kg EBW gain), as the BW increased from 15 to 30 kg.

Comparison of model predictions with measurements: A novel model-assessment method.

Frequently, scientific findings are aggregated using mathematical models. Because models are simplifications of the complex reality, it is necessary to assess whether they capture the relevant features of reality for a given application. An ideal assessment method should (1) account for the stochastic nature of observations and model predictions, (2) set a correct null hypothesis, (3) treat model predictions and observations interchangeably, and (4) provide quantitatively interpretable statistics relative to precision and accuracy. Current assessment methods show deficiencies in regards to at least one of these characteristics. The method being proposed is based on linear structural relationships. Unlike ordinary least-squares, where the projections from the observations to the regression line are parallel to the y-axis and inverse regression where they are parallel to the x-axis, the generalized projection regression method (GePReM) projects the observations on a regression line in a direction determined by the ratio of the precision of the observations to that of the mathematical model predictions. Estimation and testing issues arise when the model is expressed in the common slope-intercept format. A polar transformation circumvents these issues. The parameter for the angle between the regression line and the horizontal axis has symmetrical confidence intervals and is equivariant to the exchange of X and Y. The null hypothesis for the equivalence test is that the model predictions are not equivalent to the observations. Information size is calculated as the simple ratio of the variance of the true values of the observations and of the computer model predictions divided by their respective precision. This information size plays a critical role in determining the number of observations required and the size of the zone of practical tolerance for the equivalence tests. The terminology used in the comparison of measurement methods is adapted to that of model assessment based on the equivalence tests on the relative precision, regression slope, and mean bias. Two examples are presented, with complete details of the calculations required for parameter estimation, equivalence tests, and confidence intervals. The assessment method proposed is an alternative to other assessment methods available. Further research is required to establish the relative benefits and performance of this proposed method compared with others available in the literature.

Intestinal digestibility of long-chain fatty acids in lactating dairy cows: A meta-analysis and meta-regression.

The objective of this analysis was to examine the intestinal digestibility of individual long-chain fatty acids (FA) in lactating dairy cows. Available data were collated from 15 publications containing 61 treatments, which reported total and individual FA duodenal flows and calculations of intestinal digestibility. All studies involved lactating dairy cows, and estimates of digestibility were based on measurements either between the duodenum and ileum (18 treatments) or between the duodenum and feces (43 treatments). Fatty acid digestibility was calculated for C16:0, C18:0, C18:1 (cis and trans isomers), C18:2, and C18:3. Digestibility of C18:0 was lower than for C18:1 and C18:3, with no difference in digestibility between saturated FA (C16:0 and C18:0). We weighted the studies by the reciprocal of the variance to generate best-fit equations to predict individual FA digestibility based on duodenal flow of FA and dietary independent variables. The flow of C18:0 negatively affected the digestibility of C18:0 and was also included in the best-fit equations for all other 18-carbon FA using duodenal flow characteristics. The type of fat supplemented had an effect on digestibility of individual FA, with whole seeds having reduced digestibility. Our meta-analysis results showed minimal differences in the digestibility of individual FA. However, C18:0 flow through the duodenum had a negative effect on the digestibility of several individual FA, with the largest negative effect on C18:0 digestibility. The mechanisms that reduce C18:0 absorption at high concentrations are unknown and warrant further investigation.

Partitioning variation in nutrient composition data of common feeds and mixed diets on commercial dairy farms.

A large project involving commercial dairy farms was undertaken to identify important sources of variation in composition data of common feeds and mixed diets. This information is needed to develop appropriate sampling schedules for feeds and should reduce the uncertainty associated with the nutrient composition of delivered diets. The first subproject quantified sources of variation in the composition of corn and haycrop silages over a 2-wk period. Silages from 11 commercial dairy farms in Ohio and Vermont were sampled daily over a 14-d period. Most silages were sampled in duplicate each day, and all samples were assayed in duplicate. Total variance was partitioned into analytical, sampling, farm, and true day-to-day components. Farm was the largest source of variation, but within-farm variance was our primary interest. Sampling variance comprised 30 to 81% of within-farm variance depending on nutrient and type of silage. For dry matter, true day-to-day variation was the greatest source of variance, but for most other nutrients, sampling was the largest source of within-farm variation. The second subproject consisted of sampling feeds and total mixed rations (TMR) from 47 commercial dairy farms across the United States. Feeds and TMR were sampled monthly. Because samples were not assayed in duplicate, source of variation included farm, month, and residual (sampling plus analytical). For corn and alfalfa silages, month-to-month variation over a 12-mo period comprised about twice as much of the total within-farm variation as did day-to-day variation over a 14-d period in the first subproject. Although month-to-month variation was greater than sampling variation, sampling still accounted for 9 to 37% of the total within-farm variance for those 2 feeds. For TMR, sampling plus analytical variance accounted for approximately 40 to 70% of the total within-farm variance (depending on the nutrient). Variance components were estimated for several nutrients and for several common feeds. The contributions to total variance differed depending on feed and nutrient, but the information provided will help in determining whether on-farm samples should be taken and if so, how often. A major implication of this project is that sampling is a substantial source of variation in silages, concentrates, and TMR, and data from a single sample are likely not highly reliable.

A statistical filtering procedure to improve the accuracy of estimating population parameters in feed composition databases.

Accurate estimates of mean nutrient composition of feeds, nutrient variance (i.e., standard deviation), and covariance (i.e., correlation) are needed to develop a more quantitative approach of formulating diets to reduce risk and optimize safety factors. Commercial feed-testing laboratories have large databases of composition values for many feeds, but because of potentially misidentified feeds or poorly defined feed names, these databases are possibly contaminated by incorrect results and could generate inaccurate statistics. The objectives of this research were to (1) design a procedure (also known as a mathematical filter) that generates accurate estimates of the first 2 moments [i.e., the mean and (co)variance] of the nutrient distributions for the largest subpopulation within a feed in the presence of outliers and multiple subpopulations, and (2) use the procedure to generate feed composition tables with accurate means, variances, and correlations. Feed composition data (>1,300,000 samples) were collected from 2 major US commercial laboratories. A combination of a univariate step and 2 multivariate steps (principal components analysis and cluster analysis) were used to filter the data. On average, 13.5% of the total samples of a particular feed population were removed, of which the multivariate steps removed the majority (66% of removed samples). For some feeds, inaccurate identification (e.g., corn gluten feed samples included in the corn gluten meal population) was a primary reason for outliers, whereas for other feeds, subpopulations of a broader population were identified (e.g., immature alfalfa silage within a broad population of alfalfa silage). Application of the procedure did not usually affect the mean concentration of nutrients but greatly reduced the standard deviation and often changed the correlation estimates among nutrients. More accurate estimates of the variation of feeds and how they tend to vary will improve the economic evaluation of feeds and risk assessment of diets, and provide the ability to implement stochastic programming.

Casein synthesis is independently and additively related to individual essential amino acid supply.

Specific AA affect rates of milk protein synthesis in the mammary glands of lactating cows. The objective of this study was to quantify the rate of αS1-casein synthesis in response to Ile, Leu, Met, and Thr supplementation, and to test the single-limiting AA theory for milk protein synthesis by exploring interactions among these AA. Effects of Ile, Leu, Met, and Thr were studied in vitro with a composite design containing a central point repeated 4 times, with 2 axial points per AA and a complete 2(4) factorial. Other AA were at the concentration in Dulbecco's modified Eagle medium/F12 medium (DMEM). The experiment was replicated with mammary tissue from 5 lactating cows. Mammary tissue slices (0.12 ± 0.02 g) were incubated for 4h at 37°C in 5 mL of treatment medium containing (2)H5-Phe. Caseins were precipitated from cell homogenate supernatants. Enrichment with (2)H5-Phe of the N[34]LLRFFVAPFPE αS1 peptide was determined by matrix-assisted laser desorption/ionization-tandem time-of-flight (MALDI-TOF-TOF), which was used to determine enrichment of Phe in the transfer (t)RNA pool and αS1-casein fractional synthesis rates (CFSR). Data were analyzed with a polynomial mixed model containing linear, quadratic, and 2-factor interactions for Ile, Leu, Met, and Thr, and cow and residual as random factors. Interactions were not significant at P<0.1 and were removed from the model. Increasing concentrations of Ile, Leu, Met, and Thr simultaneously increased CFSR curvilinearly with a predicted maximum response of 4.32 ± 0.84%/h at 63% of DMEM concentrations. The maximum response to each of the 4 AA was at 71, 49, 60, and 32% of the concentration in DMEM, for Ile, Leu, Met, and Thr, respectively. These values correspond to 270, 120, 440, and 140% the plasma concentrations of Ile, Leu, Met, and Thr observed in lactating cows fed to meet National Research Council requirements, respectively. The CFSR estimated at those maxima were similar among AA (3.6 ± 0.6%/h). Individual AA effects on CFSR did not correlate with mammalian target of rapamycin (mTOR) signaling. Independent responses of CFSR to individual essential AA observed in this study contradict the single-limiting AA theory assumed in current requirement systems. The saturable responses in CFSR to these 4 AA also highlight the inadequacy of using a fixed postabsorptive AA efficiency approach for determining AA requirements for milk protein synthesis.

Isoleucine, leucine, methionine, and threonine effects on mammalian target of rapamycin signaling in mammary tissue.

Improved representation of postabsorptive N metabolism in lactating dairy cows requires a better understanding of protein synthesis regulation in the mammary glands. This study aimed to determine the quantitative effects of Ile, Leu, Met, and Thr on the phosphorylation state of signaling proteins that regulate protein synthesis. The experiment used a composite design with a central point, 2 axial points per AA, and a complete 2(4) factorial. All of the other AA were provided at the concentrations in Dulbecco's modified Eagle's medium. The experiment was replicated with tissues from 5 lactating cows. Mammary tissue slices (0.12 ± 0.02 g) were incubated for 4h. Total and site-specific phosphorylated mammalian target of rapamycin (mTOR; Ser2448), eukaryotic elongation factor (eEF) 2 (Thr56), ribosomal protein S6 (Ser235/236), and eukaryotic initiation factor 2α (Ser51) were determined by western immunoblotting. Tissue concentrations of the 4 AA studied responded linearly to media supply. Addition of Ile, Leu, Met, or Thr had no effect on eukaryotic initiation factor 2α phosphorylation. Isoleucine and Thr positively affected mTOR phosphorylation. However, the 2 AA had an antagonistic relationship. Similarly, Ile linearly increased ribosomal protein S6 phosphorylation, and Thr inhibited the Ile effect. In addition, eEF2 phosphorylation was linearly decreased by Ile and Leu. Threonine curvilinearly decreased eEF2 phosphorylation, Ile and Leu negatively interacted on eEF2, and Thr tended to inhibit Leu effects on eEF2. This work demonstrated saturable responses and interactions between AA on activation of the mTOR pathway. Incorporation of these concepts into milk protein response models will help to improve milk and milk protein yield predictions and increase postabsorptive N efficiency and reduce N excretion by dairy cows.

Effects of short-term variation in forage quality and forage to concentrate ratio on lactating dairy cows.

Within-farm variation in forage composition can be substantial and potentially costly, and it presents challenges for sampling the forage accurately. We hypothesized that day-to-day variation in forage neutral detergent fiber (FNDF) concentrations and diet variation caused by sampling error would have negative effects on production measures in lactating dairy cows. Twenty-four Holstein cows (73 d in milk) were used in 8 replicated 3 × 3 Latin squares with 21-d periods. Treatments were (1) control (CON), (2) variable (VAR), and (3) overreacting (ORR). On average, over the 21-d period, all 3 treatments were the same [24.7% FNDF and 48.2% forage dry matter (DM) composed of 67% alfalfa silage and 33% grass silage]. The CON treatment was essentially consistent day-to-day in total forage and FNDF concentrations and proportion of alfalfa and grass silages. The VAR treatment changed daily (in a random pattern) in proportion of alfalfa and grass silages fed, which resulted in day-to-day changes in FNDF (range was 21.5 to 28%). The ORR treatment varied in a 5-d cyclic pattern in total forage and FNDF concentrations (26, 24, 28, and 21.5% FNDF). Over the 21 d, ORR (25.1 kg/d) had higher DM intake compared with CON (24.5 kg/d) and VAR (24.3 kg/d). Milk production (42.8 kg/d), milk fat (3.5%), and milk protein (2.8%) were not affected by treatment; however, a treatment × day interaction was observed for milk production. Lower daily milk yields for VAR and ORR compared with CON were rare; they only followed sustained 4- and 5-d periods of feeding higher FNDF diets compared with CON. In contrast, increased daily milk yields for VAR and ORR versus CON were more frequent and followed sustained diet changes of only 2 or 3d. Lipolytic and lipogenic-related enzyme mRNA abundances in subcutaneous adipose tissue were not affected by treatment. Treatment × day interactions were observed for milk fatty acid markers of cellulolytic bacteria (iso-14:0, iso-15:0, iso-16:0) and lipolysis (18:0) and generally followed the expected response to changes in daily rations. Overall, extreme daily fluctuations in FNDF had no cumulative negative effect on production measures over a 21-d period, and daily responses to transient increases in FNDF were less than expected.

Effects of transient changes in silage dry matter concentration on lactating dairy cows.

Transient changes in the dry matter (DM) concentration of silages often occur, which will cause transient changes in the ration. To determine the effects of a transient change in silage DM, 24 Holstein cows (116 d in milk) were used in an 8 replicated 3×3 Latin square design with 21-d periods. Treatments were (1) control, (2) unbalanced (UNBAL), and (3) balanced (BAL). The control diet was designed to have a consistent day-to-day forage:concentrate ratio of 55:45 on a DM basis. The UNBAL and BAL diets were the same as the control diet for most of the period except during two 3-d bouts when water was added to the silage (simulating a rain event) to cause a 10-percentage unit decrease in silage DM concentration. During the bouts, the UNBAL diet was the same as that of the control on an as-fed basis, but on a DM basis, the forage:concentrate ratio decreased to 49:51, which reduced dietary concentrations of DM (63.9 vs. 66.2%) and forage NDF (21.0 vs. 23.6%), and increased starch (30.4 vs. 28.4%). The BAL treatment corrected for the change in silage DM by an increase in the inclusion of wet silage and had the same composition as the control diet on a DM basis, except for ration DM (66.2 vs. 63.9%). Over the 21-d period, treatment did not affect DM intake (DMI; 24.0 kg/d); however, DMI of cows on the UNBAL and BAL treatments tended to decrease during the wet bouts, especially during the second bout. The day following both bouts, DMI of cows fed BAL and UNBAL diets were greater than that of cows fed the control diet, which contributed to the lack of a treatment effect on DMI over the entire period. Milk production was greater for the UNBAL than control cows (39.8 vs. 39.3 kg/d) over the 21-d period. That difference was largely caused by increased milk yield during the first bout by cows on the UNBAL diet. Over the 21-d period, milk yield did not differ between control and BAL cows. Some small differences in milk fat and protein concentrations (≤ 0.1 percentage units) were observed between treatments. Total-tract digestibility of most nutrients was not affected by treatment. Overall, a 10-percentage unit decrease in silage DM over short-term bouts (with or without total mixed ration adjustment) had only minor effects on DMI, milk yield, and composition.

Mineral concentrations in diets, water, and milk and their value in estimating on-farm excretion of manure minerals in lactating dairy cows.

Thirty-nine commercial dairies in Merced County, California were enrolled in the present study to (1) compare lactating cow mineral intakes (via drinking water and total mixed ration) to the National Research Council (NRC) requirements, (2) evaluate the association between dietary concentrations of minerals with and without drinking water and adjusted for mineral concentrations in milk, and (3) compare 4 different methods to estimate excretion of minerals using either assays or estimations of milk mineral outputs and total daily mineral intake per cow with or without minerals coming from drinking water. Dairies were selected to represent a range of herd milk yields and a range of water mineral contents. Samples of total mixed ration, drinking water, and bulk tank milk were taken on 2 different days, 3 to 7d apart in each farm. Across-farm medians and percentile distributions were used to analyze results. The herd median milk yield interquartile ranged (10th to 90th percentile) from less than 25 to more than 39 kg/d and the concentration of total solids in water interquartile ranged from less than 200 to more than 1,490 mg/L. Including drinking water minerals in the diets increased dietary concentrations by <4% for all minerals except for Na and Cl, which increased by 9.3 and 6.5%, respectively. Concentrations of P and K in milk were essentially the same as the NRC value to estimate lactation requirements. However, NRC milk values of Ca, Cl, and Zn were 10 to 20% greater than dairy farm values; and Na, Cu, Fe, and Mn were no less than 36% below NRC values. Estimated excretion of minerals via manure varied substantially across farms. Farms in the 10th percentile did have 2 to 3 times less estimated mineral excretions than those in the 90th percentile (depending on the mineral). Although including water minerals increased excretion of most minerals, the actual median effect of Ca, Mg, S, Cu, Fe, and Mn was less than 5%, and about 8% for Na and Cl. Replacing assayed concentrations of minerals in milk with NRC constants resulted in reduced estimated excretion of Ca, Na, Cu, Fe, and Zn, but median differences were <5% except for Na which was 7.5%. Results indicate that not including mineral intake via drinking water and not using assayed concentrations of milk minerals lead to errors in estimation manure excretion of minerals (e.g., Ca, Na, Cl, and S).

Effects on lactating dairy cows of oscillating dietary concentrations of unsaturated and total long-chain fatty acids.

The nutrient composition of diets can vary from batch to batch because of variation in the nutrient composition of ingredients. The concentration of fat in distillers grains can be highly variable and, coupled with a high dietary inclusion rate, can result in substantial variation in the fat concentration of the total diet. Our hypothesis was that variation in dietary fat concentrations over short periods would have negative effects on production measures of dairy cattle. Twenty-four Holstein cows were used in 8 truncated Latin squares (3 cows × 2 periods). Periods were 16 d long, with a 12-d washout period separating the 2 periods. The 3 treatments were 1) control, 2) moderate variation, and 3) high variation. The control treatment was a consistent diet over the 16 d and contained 5.8% (dry basis) total long-chain fatty acids (LCFA), 23.7% distillers grains, and 1.1% of dry matter as corn oil. The average concentration of LCFA over the 16-d period for the moderate variation and high variation treatments was also 5.9%, but concentrations of LCFA varied over time by the addition or removal of corn oil. The moderate variation treatment had a 4-d phase of 5.4% LCFA, followed by a 4-d phase with 6.4% LCFA to complete the cycle, and then the cycle was repeated. The high variation treatment followed the same cycle pattern, but concentration of LCFA was either 4.8 or 7.0%. Over the 16 d, dry matter intake and milk yield were significantly decreased by the high variation treatment (intake = 21.7, 21.8, and 20.7 kg/d; milk = 36.4, 37.6, and 35.4 kg/d for the control, moderate variation, and high variation treatments). The effect of variation appeared to be cumulative; differences were not significant in the first 8-d cycle but were in the second 8-d cycle. Milk fat concentration was low (2.4%) and was not affected by treatment or cycle × treatment. The concentration of trans-10 C18:1 in milk fat was very high (4.2% of total milk fatty acids) but was not affected by treatment. However, cows on the high variation treatment had higher concentrations of trans-10, cis-12 C18:2 in milk fat (0.036, 0.042, and 0.047% of milk fatty acids for the control, moderate variation, and high variation treatments). Overall, an extreme short-term fluctuation in dietary fat concentration was needed before negative effects were observed.

A meta-analysis of the effects of high ambient temperature on growth performance of growing-finishing pigs.

High ambient temperature (T) is one of the most important climatic factors influencing pig performance. Increased T occurs sporadically during summer heat waves in temperate climates and year round in tropical climates. Results of published experiments assessing the effects of high T on pig performance are surprisingly variable. Thus, a meta-analysis was performed to aggregate our knowledge and attempt to explain differences in the results across studies on the effect of increased T on ADFI and ADG in growing-finishing pigs. Data for ADFI and ADG were extracted from 86 and 80 trials, respectively, from articles published in scientific journals indexed in PubMed, Science Direct, and from proceedings of scientific meetings through November 2009. Data on ADFI and ADG were analyzed using a linear mixed model that included the linear and the quadratic effects of T and BW, and their interactions as continuous, fixed effects variables, and the trial as a random effect factor (i.e., block). In addition, the effects of housing type (2 levels: individual and group housing) and the year of publication (3 levels: 1970 to 1989, 1990 to 1999, and 2000 to 2009) on the intercept and the linear regression term for T (i.e., the slope) were also tested. Results showed that high T had a curvilinear effect on ADFI and ADG and that this effect was more pronounced in heavier pigs. Across T, ADFI was less when pigs were group-housed. The intercept and the regression coefficient (slope) for T were significantly affected by the year of publication. The effect of increased T was greater in more contemporary works, suggesting that modern genotypes could be more sensitive to heat stress than older genotypes of lesser growth potential. In conclusion, pig performance decreases at an accelerating rate as T is increased. The large between-study variability on the effects of high T on pig performance is partially explained by differences in pig BW and to a lesser extent by the year the study was published.

Applications of population data analysis in on-farm dairy trials.

With appropriate management controls and statistical designs, on-farm trials are an increasingly valuable research tool. On-farm trials can speed up technology adoption, particularly with those studies requiring large numbers of animals. Useful designs include longitudinal (pen vs. pen) trials, in which pen is the experimental unit, and crossover or switchback designs, in which treatments are imposed on a schedule over 1 or more experimental groups. A paired-herd design has been used, in which herds are the experimental units in a crossover trial. Others have published similar studies, including a multisite crossover design that used 35 dairy farms to compare milk responses with a protein source by using individual cow records to evaluate differences in milk production. Recently, statistical process control (SPC) techniques have been used to evaluate management changes by using repeated measures on the farm. Although a drawback to SPC may be the lack of traditional statistics to test differences (i.e., the lack of a control group), standard run rules are used to demonstrate with statistical certainty that a process or variable has changed, or to characterize a seasonal change. With SPC, the inference is limited to the herd or group of animals being monitored. Meta-analysis techniques are powerful tools used to combine results from many similar trials in which the response of interest is either small (i.e., continuous variables) or of low frequency (i.e., discrete variables). Meta-analysis can be used to segment a database so as to validate and compare trial methods or to investigate publication bias. Additional design concerns for reproduction studies include the need for adequate numbers of observations and planning for the lag time between an experimental treatment and response measurement (e.g., confirmation of pregnancy).

Varying type of forage, concentration of metabolizable protein, and source of carbohydrate affects nutrient digestibility and production by dairy cows.

The effects of forage source, concentration of metabolizable protein (MP), type of carbohydrate, and their interactions on nutrient digestibility and production were evaluated using a central composite treatment design. All diets (dry basis) contained 50% forage that ranged from 25:75 to 75:25 alfalfa silage:corn silage. Rumen-degradable protein comprised 10.7% of the dry matter (DM) in all diets, but undegradable protein ranged from 4.1 to 7.1%, resulting in dietary MP concentrations of 8.8 to 12.0% of the DM. Dietary starch ranged from 22 to 30% of the DM with a concomitant decrease in neutral detergent fiber concentrations. A total of 15 diets were fed to 36 Holstein cows grouped in 6 blocks. Each block consisted of three 21-d periods, and each cow was assigned a unique sequence of 3 diets, resulting in 108 observations. Milk production and composition, feed intake, and digestibility of major nutrients (via total collection of feces and urine) were measured. Few significant interactions between main effects were observed. Starch concentration had only minor effects on digestibility and production. Replacing corn silage with alfalfa decreased digestibility of N but increased digestibility of neutral detergent fiber. Increasing the concentration of MP increased N digestibility. The concentration (Mcal/kg) of dietary digestible energy (DE) increased linearly as starch concentration increased (very small effect) and was affected by a forage by MP interaction. At low MP, high alfalfa reduced DE concentration, but at high MP, increasing alfalfa increased DE concentration. Increasing alfalfa increased DM and DE intakes, which increased yields of energy-corrected milk, protein, and fat. Increasing MP increased yields of energy-corrected milk and protein. The response in milk protein to changes in MP was much less than predicted using the National Research Council (2001) model.