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Made available in DSpace on 2020-12-11T06:34:45Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-01-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) 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/kg(0.75) of EBW; dependent variable) from MEI (kcal/kg(0.75) 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 (k(m)) was calculated as the ratio between NEM and the metabolizable energy requirement for maintenance. Efficiency of energy utilization for growth (k(g)) 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 (k(p)) and as fat (k(f)) 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/kg(0.)(75) of EBW for males and 63.6 +/- 2.89 kcal/kg(0.75) of EBW for females) and sex did not affect k(m) (0.63). In contrast, sex no longer affected NEM when degree of maturity was considered on its estimation. The k(g) was different between sexes (0.31 for castrated males and females, and 0.26 for intact males), but k(p) (0.21) and k(f) (0.80) were similar between sexes. These results may be useful for improving robustness of the energy requirement recommendations for dairy goats. Univ Estadual Paulista, Dept Anim Sci, BR-14884900 Jaboticabal, SP, Brazil Univ Fed Sul & Sudeste Para, Inst Estudos Trop Umido, BR-68557335 Xinguara, PA, Brazil Ohio State Univ, Dept Anim Sci, Columbus, OH 43201 USA Univ New England, Sch Environm & Rural Sci, Armidale, NSW 2351, Australia Univ Estadual Paulista, Dept Anim Sci, BR-14884900 Jaboticabal, SP, Brazil FAPESP: 2014/14734-9 CAPES: 001

Made available in DSpace on 2018-12-11T17:31:27Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-09-01 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

Sound design of experiments combined with proper implementation of appropriate statistical methods for data analysis are critical for producing meaningful scientific results that are both replicable and reproducible. This communication addresses specific aspects of design and analysis of experiments relevant to the dairy sciences and, in so doing, responds to recent concerns raised in a letter to the editor of the Journal of Dairy Science regarding journal policy for research publications on pen-based animal studies. We further elaborate on points raised, rectify interpretation of important concepts, and show how aspects of statistical inference and elicitation of research conclusions are affected.

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.

There are numerous factors that can significantly influence embryonic development in poultry and thus make simple days of incubation (chronological age) a less than perfect metric for studying embryonic physiology. The developmental fast skeletal muscle myosin (MyHC), the predominant protein in the Pectoralis major (PM), is temporally expressed as a cadre of highly specific developmental isoforms. In the study described herein, a novel molecular technology (NanoString) was used to characterize the myosin isoform transcriptional patterns in the PM of Single Comb White Leghorn (SCWL) embryos. NanoString technology is based on quantitative analysis of the transcriptome through digital detection and quantification of target mRNA transcripts. Total RNA was isolated and gene transcription quantified using NanoString in embryonic muscle samples collected daily from 6 through 19 days of incubation. Data were analyzed using the LOESS smoothing function at a 95% confidence level. The temporal transcription of MyHC isoforms obtained in this study was consistent with the literature at higher specificity and resolution, thus validating NanoString for use in gene transcription analyses. The results support a hypothesis that the transcription patterns of the embryonic MyHC isoforms may be used as molecular clocks to further investigate the developmental relationships underlying embryonic fast skeletal muscle growth and development.

Objective—To provide an updated evaluation of the efficacy and safety of sometribove zinc suspension (rbST-Zn), a form of recombinant bovine somatotropin, in lactating dairy cows. Design—Meta-analysis. Sample—26 studies published in peer-reviewed journals or reviewed by a regulatory agency. Procedures—To be included, a study had to involve the use of the rbST-Zn formulation available to US producers in accordance with the label instructions for treatment initiation (57 to 70 days postpartum), dose (500 mg, q 14 d), and route (SC). Results—For cows treated with rbST-Zn, mean milk, 3.5% fat-corrected milk, fat, and protein yields were increased by 4.00, 4.04, 0.144, and 0.137 kg/d (8.8, 8.89, 0.32, and 0.30 lb/d), respectively; however, the concentration of milk components did not change. Pregnancy proportion for the first 2 breeding cycles was increased by 5.4%, and pregnancy proportion for the duration of the trial was reduced by 5.5% for rbST-Zn–treated cows, compared with proportions for untreated cows. Mean body condition score (1 to 5 scale) was reduced by 0.06 points during the period of rbST-Zn use for treated cows. Administration of rbST-Zn had no effect on milk somatic cell count, the number of days to pregnancy, or inseminations per pregnancy; rates of fetal loss, twins, cystic ovaries, clinical lameness, lameness lesions, or traumatic lesions of the integumentary system; and odds of clinical mastitis or culling. Conclusions and Clinical Relevance—Results indicated that rbST-Zn administration to dairy cows effectively increases milk production with no adverse effects on cow health and well-being.

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.

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

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.

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.

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.

In a previous study, we reported on a quantitative transcriptomic method which confirmed the temporal transcription of developmental fast skeletal muscle myosin heavy chain (fsMyHC) embryonic isoforms in the embryonic Pectoralis major (PM) of the Single Comb White Leghorn (SCWL). The objective of the current study was to further investigate the transcriptional events underlying embryonic PM growth in the SCWL and a genotype exhibiting partial muscular dystrophy, the Low Score Normal (LSN). We hypothesized that within the SCWL and LSN embryos, there would be differences in the temporal transcription of the fsMyHC isoforms and other myogenic regulatory genes. Samples of PM tissues were collected daily from embryonic day (ED) 6 through ED19. Total RNA was isolated from each PM tissue sample and mRNA transcripts from 28 target genes were simultaneously quantified using a probe hybridization method. Raw data counts were normalized against the geometric mean of 5 housekeeping genes and analyzed using Local Regression (LOESS) smoothing methods. Predicted estimates based on LOESS smoothing were plotted with 95% upper and lower confidence intervals, allowing for line comparisons between the SCWL and LSN. Differences (P 0.05) were determined by non-overlapping confidence intervals between the SCWL and LSN. Among genes exhibiting line differences (P 0.05), were the developmental fsMyHC isoforms, transcription factors, growth factors, and proteoglycans. The current study is the first to report transcription of the chicken fast skeletal adult myosin isoform (Cad) during PM myogenesis. Samples were submitted for capillary-liquid chromatography-tandem mass spectrometry analysis which confirmed the translation of all the developmental fsMyHC isoforms including Cad in both lines. The LSN exhibited altered transcription patterns of early myogenic markers (MYOD, MRF4, Cemb1, six4, and pax3) during late embryogenesis, continued transcription of Cvent, and delayed transcription of Cneo.

A method that accurately quantifies changes in the supply of metabolizable Met following a dietary change will allow accurate economic comparisons of various Met sources. This paper describes a novel method of estimating the relative supply of metabolizable Met based on changes in the concentration of Se in milk. Selenized yeast (Se-yeast) contains selenomethionine (Se-met) and because Se-met and Met are indistinguishable by cells, Se-met can be used as a tracer of Met. We hypothesized that if the size of the Met pool was increased but intake of Se-met was constant, the concentration of Se in milk relative to milk Met would decrease. To test this hypothesis, 6 Holstein cows were fed a diet that contained 0.3 mg of Se from Se-yeast/kg of diet DM and then in a 2-period crossover experiment, were abomasally infused with water (control) or an aqueous solution that provided 9 g of Met/d. Milk was sampled during the infusion and the specific activity (SA) of milk (Se concentration divided by Met concentration) was calculated for each treatment. The SA in milk from Met-infused cows was divided by SA in milk from control cows to calculate the change in supply of metabolizable Met. As hypothesized, infusing Met reduced the SA of milk (84.7 vs. 72.5 microg of Se/mg of Met). The calculated flow of metabolizable Met was 17% greater when cows were infused with 9 g of Met/d compared with cows infused with water (essentially the same difference was measured using SA calculated with N concentrations of milk). Assuming the infused Met was 100% absorbed, the flow of metabolizable Met for control cows was 9/0.17 = 53 g of Met/d, which agreed well with literature data and estimates derived from common nutritional models.

Various recommendations have been issued regarding the sampling schedule of diet components, especially forages. Their basis is unclear and none are justified from an economic standpoint. The objective of this research was to derive a general method for determining the optimal sampling design for forages. The process of forage removal from storage can be conceptualized as a quality control issue that can be monitored using a Shewhart X-bar chart. This procedure requires 3 control parameters: number of samples (n), sampling interval (h), and control limits (L). A quality cost function made of 4 parts is proposed: cost per cycle while the process is in-control (I); cost per cycle while the process is out-of-control (O); cost per cycle for sampling and analyses (A); and expected duration of a cycle (D). Thirteen inputs enter the cost function: the mean time that process is in control, the number of animals in the herd, the unit price of milk, the milk production loss due to white noise, the milk production loss from an abrupt change in forage composition, the time to sample and analyze one item, the expected time to discover the assignable cause, the expected time to fix the diet, the cost per false alarm, the cost to fix the diet, the fixed cost of sampling at each sampling time, the cost for each unit sampled, and the number of standard deviation slips when forage changes. The total quality cost per day C = (I + O + A)/D. The C function can be optimized with respect to n, h, and L to yield an optimal sampling schedule. Because n and h are discrete variables in a highly nonlinear function, parametric optimization algorithms cannot be used to optimize the function. A genetic algorithm was used for the minimization of C. Results showed that the optimal sampling designs are close to current practices in small herds of 50 cows, but very different in large herds of 1,000 cows, resulting in reduced total quality costs of $250/d. Total sensitivity of C was greatest for the number of cows in the herd, the shift in milk production when forage changes, the mean time that the process is in control, the price of milk, and the time to sample and analyze one item. Total sensitivities of n, h, and L were greatest for the mean time that the process is in control, the extent of the change in composition when there is a change in forage composition, the number of cows in the herd, the shift in milk production when forage changes, and the cost per unit sampled.

Increasingly, research is being performed in which animals subjected to a common treatment are also housed in a common pen. Issues have been raised regarding the proper planning of experiments and conduct of statistical analyses in these instances. This paper reviews the problems associated with ignoring animal grouping during data analyses, and examples are provided for appropriate methods to use when animals are grouped in pens. Using animals as the error term when treatments are applied to pens can result in biased estimates of treatment effects when pens are of unequal sizes and animals are moved in and out of the pens. It always results in biased probability statements regarding their significance. The pen effect includes systematic effects other than that of the treatment, which is why pens must be replicated and randomized. In essence, pen studies have an implicit split-plot design in which the main plots (pens) receive the treatments of interest, whereas the subplots (cows) receive all the same subplot treatment. Using the subplot error to test main-plot treatment effects creates inflated degrees of freedom and uses the wrong denominator mean square to test the effect; hence, severely biasing the test of significance for the treatment effects and resulting in an invalid causal inference base. The interactions of pens with the fixed-effect elements of the treatment design are the correct error terms for those fixed-effects factors applied to the pens. The same statistical designs used with animals as experimental units can be used with pens. The number of experimental units to achieve a given power can be, and generally is, considerably less with pens because the variance among pens is generally less than the variance of cows within pens. Pens must be replicated, randomized, and included in the statistical model to ensure valid statistical inference.

Biohydrogenation (BH) of fatty acids (FA) from fresh alfalfa and alfalfa hay with varying levels of supplemental sucrose and media pH was evaluated in vitro. A multicompartmental model was then developed to estimate pool size and flux of vaccenic acid (VA) during BH of FA in fresh alfalfa. To vary incubation pH, alfalfa samples were inoculated with rumen fluid in 2 media differing in molarity of the bicarbonate buffer. Samples were incubated for 0, 1, 2, 3, 4, 6, 9, and 12 h; pH was measured and tubes were put in ice and stored until analysis. The BH rates of linoleic acid (18:2) and linolenic acid (18:3) were estimated by PROC NLIN of SAS (single pool, first-order kinetic model) and SAAM II (multiple pools, first-order kinetic model). Both methods gave similar estimates for the BH rates of 18:2 and 18:3 as well as the temporal pool size of VA. The BH rates (%/h) in the strong (SB) and weak buffers (WB) were 27.4 (+/-0.7) and 23.5 (+/-0.9) for 18:2, and 43.8 (+/-0.2) and 30.3 (+/-0.6) for 18:3, respectively. The WB decreased the BH rates of 18:2 and 18:3 for both forage sources. However, BH rates of 18:3 were higher from fresh alfalfa than alfalfa hay. There was no effect of sucrose addition on the BH rates of 18:2 and 18:3. Moreover, there was no effect of buffer on the BH of VA estimated by the multiple pools model between the SB and WB (12.5 +/- 2.1 and 14.1 +/- 3.7%/h, respectively). The BH rates of the conjugated linoleic acid isomers were not different between the SB and WB treatments (36.7 +/- 19.8 and 25.9 +/- 27.2, respectively). Because we could estimate fluxes as well as mass of the VA pools, more information was generated from the data when a multiple pools model was used compared with a single pool, first-order kinetic model.

Methionine supplemented as 2-hydroxy-4-(methylthio)-butanoic acid (HMB) has been suggested to alter bacterial or protozoal populations in the rumen. Our objective was to determine if source of Met would change microbial populations in the rumen and to compare those results to samples from the omasum. The ruminal and omasal samples were collected from cows fed control (no Met), dl-Met, HMB, or the isopropyl ester of HMB (HMBi; estimated 50% rumen protection) in a replicated 4×4 Latin square design. In one square, changes in protozoal populations were determined using microscopic counts and denaturing gradient gel electrophoresis (DGGE), whereas changes in bacterial populations were determined using DGGE and ribosomal intergenic spacer length polymorphism (RIS-LP). Neither the protozoal counts nor the DGGE banding patterns derived from protozoa were different among the dietary treatments or for ruminal vs. omasal samples. As revealed by both DGGE and RIS-LP, bacterial populations clustered by treatments in ruminal and especially in omasal samples. Using cows from both Latin squares, the flow of protozoal cells from the rumen was quantified by multiplying protozoal cell count in omasal fluid by the omasal fluid flow (using CoEDTA as a liquid flow marker) or was estimated by rumen pool size of cells multiplied by either the ruminal dilution rate of CoEDTA (after termination of CoEDTA dosing) or the passage rate of Yb-marked particles. Compared with the omasal fluid flow measurement (16.4h), protozoal generation time was approximated much more closely using the particulate than the fluid passage rate from the rumen (generation times of 15.7 and 7.5h, respectively). There seems to be minimal selective retention of protozoal genera in the rumen in dairy cattle fed every 2h. Data support the validity of the omasal sampling technique under our conditions.

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.

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.

An important objective is to identify nutrients or dietary factors that are most critical for advancing our knowledge of, and improving our ability to predict, milk protein production. The Dairy NRC (2001) model is sensitive to prediction of microbial protein synthesis, which is among the most important component of models integrating requirement and corresponding supply of metabolizable protein or amino acids. There are a variety of important considerations when assessing appropriate use of microbial marker methodology. Statistical formulas and examples are included to document and explain limitations in using a calibration equation from a source publication to predict duodenal flow of purine bases from measured urinary purine derivatives in a future study, and an improved approach was derived. Sources of specific carbohydrate rumen-degraded protein components probably explain microbial interactions and differences among studies. Changes in microbial populations might explain the variation in ruminal outflow of biohydrogenation intermediates that modify milk fat secretion. Finally, microbial protein synthesis can be better integrated with the production of volatile fatty acids, which do not necessarily reflect volatile fatty acid molar proportions in the rumen. The gut and splanchnic tissues metabolize varying amounts of volatile fatty acids, and propionate has important hormonal responses influencing milk protein percentage. Integration of ruminal metabolism with that in the mammary and peripheral tissues can be improved to increase the efficiency of conversion of dietary nutrients into milk components for more efficient milk production with decreased environmental impact.

The low score normal (LSN) chicken exhibits a genetic muscle weakness and altered in vitro myogenesis compared to the normal White Leghorn chicken. The ventricular myosin heavy chain isoform has been reported to be the initial muscle-specific contractile protein expressed during myogenesis. The goals of this study were to determine whether altered myogenesis of the LSN satellite cells in culture was accompanied by delayed ventricular myosin heavy chain expression and to further characterize the altered myogenic events exhibited by the LSN chicken. Immunocytochemical and ELISA analyses were employed to document the temporal expression of the ventricular myosin heavy chain during LSN chicken myogenesis. Satellite cells derived from the LSN chicken pectoralis major exhibited lower (P/= 0.05) expression of ventricular myosin heavy chain during proliferation and differentiation in culture than did satellite cells derived from White Leghorn chickens. Low score normal cells failing to express the ventricular myosin heavy chain generally remained mononucleated and unfused, whereas cells that were multinucleated appeared to express ventricular myosin heavy chain regardless of the avian source. These results suggest that the altered myogenesis observed in LSN chickens is associated with delayed ventricular myosin heavy chain expression.

2-Hydroxy-4-(methylthio) butanoic acid (HMB) positively affects milk composition and yield, potentially through ruminal actions. Four continuous culture fermenters were used to determine the optimal concentration of HMB for digestibility of organic matter (OM), neutral detergent fiber (NDF), acid detergent fiber (ADF), and hemicellulose and synthesis of microbial N. A highly degradable mix of hay and grain was used as a basal diet to simulate a typical lactation diet. Three concentrations of HMB (0, 0.055, and 0.110%) and one concentration of dl-Met (0.097%) were infused into the fermenters according to a 4 x 4 Latin square design. Digesta samples were collected during the last 3 d of each of the four 10-d experimental periods. Digestibility of OM, hemicellulose, and NDF was largely insensitive to treatment. Digestibility of ADF showed a quadratic effect to supplementation of HMB, with 0.055% having lower digestibility than 0 or 0.110%. Total production of VFA was not influenced by HMB supplementation, but differences in concentration and production of individual VFA were seen. Isobutyrate increased linearly with increasing HMB supplementation. Propionate concentration decreased linearly with increased HMB supplementation, but propionate production showed a quadratic trend (P = 0.13). A higher concentration of acetate was detected for dl-Met compared with the highest HMB concentration. There were trends (P < 0.15) for dl-Met to decrease the production of isobutyrate and to lower the concentration of butyrate when compared with HMB. Microbial efficiency was not different among treatments. The proportion of bacterial N produced from NH3-N decreased linearly with increasing HMB, and bacteria receiving dl-Met synthesized more N from NH3-N than those receiving HMB. These data suggest that supplementation of HMB may have a sparing effect on branched chain volatile fatty acids because the fatty acids are not needed to provide carbon for synthesis of valine, isoleucine and leucine with ammonia. Comparisons of bacterial community structure in the fermenter effluent samples using PCR amplicons containing the ribosomal intergenic spacer region and its flanking partial 16S ribosomal RNA gene showed no distinct banding patterns, though treatments tended to group together. Both Met and HMB affect the rumen microbial population, but Met supplied as dl-Met does not act identically to that supplied as HMB.

Metabolizable protein (MP) supply and amino acid balance were manipulated through selection of highly digestible rumen-undegradable protein (RUP) sources and methionine (Met) supplementation. Effects on production efficiency and N utilization of lactating dairy cows were determined. Thirty-two multiparous (647 kg) and 28 primiparous (550 kg) Holstein cows were assigned during the fourth week of lactation to one of four dietary treatments. Treatments were 1) 18.3% crude protein (CP) with low estimated intestinal digestibility of RUP (HiCP-LoDRUP), 2) 18.3% CP with high digestibility RUP (HiCP-HiDRUP), 3) 16.9% CP with high digestibility RUP (LoCP-HiDRUP), and 4) 17.0% CP with high digestibility RUP and supplemental Met (LoCP-HiDRUP + Met). Diets were balanced to have equal concentrations of net energy for lactation (NE(L)), acid detergent fiber (ADF), neutral detergent fiber (NDF), and ash. Milk yields (40.8, 46.2, 42.9, 46.6 kg/d), protein percentages (2.95, 2.98, 2.99, 3.09%), and fat percentages (3.42, 3.64, 3.66, 3.73%) are reported here for HiCP-LoDRUP, HiCP-HiDRUP, LoCP-HiDRUP, and LoCP-HiDRUP + Met, respectively. Milk urea N and BUN decreased when feeding a lower CP diet. Efficiency of use of N for milk protein production was higher when feeding higher digestibility RUP, especially with the LoCP-HiDRUP + Met diet. A digestibility study followed the production trial, with six cows per treatment group continuing on the same treatment for an additional week. The experimental periods were 5 d long, with 1 d of adjustment and 4 d of total collection of urine and feces. Dry matter intake, milk production, milk protein production, and N digestibility were not significantly different among treatments during the collection trial, whereas N intake and N absorbed increased with the higher CP diets. The quantity of N in feces did not change with diet, but quantity of N in urine decreased in the low CP diets. Milk N as a percentage of intake N and milk N as a percentage of N absorbed showed a trend toward increasing as CP concentration in the diet decreased. The supplementation of Met did not improve the efficiency of N utilization during the digestibility study, in contrast to what was estimated during the production trial. Supplementing the highly digestible RUP source with rumen available and rumen escape sources of Met resulted in maximal milk and protein production and maximum N efficiency by cows during the production trial, indicating that postruminal digestibility of RUP and amino acid balance can be more important than total RUP supplementation.

The appearance of numerous plots in recent literature from which the residuals are plotted against observed values ( Y ) to assess a model's potential bias raises this question: should residuals be regressed against Y or against predicted values ( Y ˆ )? The answer requires knowing the expected relationship under the assumption of an unbiased model. The objectives of this paper are: 1) to derive the expected relationship between residuals, Y , and Y ˆ ; 2) to determine whether Y or Y ˆ should be used for the assessment of bias; and 3) to reassess the extent of mean and linear bias in the prediction of N flows to the duodenum by the NRC (2001). In the simplest case, we can assume a true model of the form Y = Xβ + ɛ . This model is estimated by Y = Xb + e , and Y ˆ = X b . The correlation between the residual vector e and the vector of observations Y can easily be derived. The numerator of the correlation coefficient is shown to be equal to e′e , the residual sum of squares. The denominator of this correlation is equal to the square root of e′e multiplied by the total sum of squares. Algebraic simplifications show that the correlation between e and Y is equal to the square root of (1-R 2 ). That is, under the assumption of an unbiased model, the residuals are correlated with the observed values and the slope of e regressed on Y is equal to (1-R 2 ). Thus, a graph of e versus Y will show a positive slope between e and Y unless the model is a perfect predictor (i.e., R 2 is equal to 1.0). Significant slopes linking e to Y have been erroneously interpreted as evidence of biased models in the NRC (2001). Conversely, the slope of e regressed on Y ˆ is expected to be zero under the assumption of an unbiased model. Therefore, residuals should be regressed against Y ˆ and not Y . When Y ˆ , as opposed to Y , was used to assess biases in the prediction of flows to the duodenum of microbial N, nonammonia-nonmicrobial N and nonammonia N in NRC (2001), mean biases became nonsignificant and linear biases over the range of predicted values are of the same magnitude or smaller than the standard errors of measurements reported in literature. Thus, although N flow predictions from NRC (2001) may not be precise, they appear to have insignificant and inconsequential biases.

Six ruminally and duodenally cannulated Holstein cows were used in a 6 × 6 Latin square design to 1) evaluate the potential interaction in effectiveness of neutral detergent fiber (NDF) from whole cottonseed (WCS) when it was substituted for forage NDF (FNDF) and fed with ground (G) or steam-flaked (SF) corn and 2) to determine whether the kinetic properties of NDF digestion further clarify the effectiveness of WCS. The six dietary treatments were: forage control with G corn (21% FNDF), 5% WCS with G or SF corn (18% FNDF), 10% WCS with G or SF corn (15% FNDF), and 15% WCS with G corn (12% FNDF). Based on chewing activity, the NDF from WCS was estimated to be 84% (SE = 36%) as effective as alfalfa silage NDF. Decreasing passage and digestion rates of potentially digestible NDF with increasing WCS increased the evacuated pool size of ruminal DM, apparently explaining the similar ruminal mat consistency among treatments. Measures of effectiveness of WCS treatments did not interact with corn source. Fluid dilution rate was estimated based on a two-compartment model describing Co dilution, but no treatment differences were detected. There was a strong linear bias for estimates of ruminal NDF digestibility based on a single compartment model using the digestion rate of potentially digestible NDF and the passage rate of either indigestible NDF or digestible NDF when compared with NDF digestibility calculated using duodenal flows. Although further verification is needed, these digestion and passage kinetics help explain why WCS are effective at stimulating chewing during eating and rumination.

Dairy scientists specializing in the area of farm management are increasingly involved in analysis of farm investments in fixed assets. There have been instances where the wrong procedures were used to assess investments in fixed assets, leading to erroneous and possibly disastrous conclusions. A detailed case study of a dairy farm facing the decision of where best to invest an unexpected $120,000 windfall is used to illustrate the various facets of financial analysis. Indicators of profitability, liquidity, solvency, repayment capacity, and financial efficiency are explained and applied to the farm case to produce a detailed analysis of the current financial position of the firm. Long-range budgets of four alternate investment options and their impact on all financial indicators are presented. The four options are: 1) to pay down debt, 2) to purchase an additional 100 cows, 3) to install automatic milk yield recording in the parlor, and 4) to build new heifer facilities. All four investments are profitable. Therefore, an analysis limited to profitability indicators would conclude that any of the four options is a good investment. However, liquidity and financial efficiency issues showed that the option of purchasing 100 cows is far superior to the three others. We conclude that a complete and thorough financial analysis is required to evaluate the impact of long-run investments in fixed assets.

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.

The effect of additional dietary potassium in early lactation dairy cows was evaluated with the addition of potassium carbonate sesquihydrate, which increased dietary K from 1.3 to 2.1% of dry matter (DM) from wk 3 to 12 of lactation. Cows fed potassium carbonate sesquihydrate in the form of DCAD Plus (Church & Dwight Co. Inc., Princeton, NJ) had increased DM intake, milk fat percentage and yield, energy-corrected milk, and efficiency of milk production per unit of DM intake. Milk fat of cows fed higher dietary K had a lower concentration of trans fatty acids, suggesting a role for potassium carbonate sesquihydrate in the rumen in the biohydrogenation processes converting linoleic to stearic acid. Cows fed the diet with 2.1% K had greater apparent balance of K, and no effects were noted on the concentration of blood Mg or amount of fecal Mg. The data support the feeding of greater amounts of K in the early lactation cow.

International audience; 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.

The response of a biological process to various factors is generally nonlinear, with many interactions among those factors. Although meta-analyses of data across multiple studies can help in identifying and quantifying interactions among factors, missing latent variables can result in serious misinterpretation. Eventually, all influential factors have to be studied simultaneously in one single experiment. Because of the curvature of the expected response and the presence of interactions among factors, the size of experiments grows very large, even when only 3 or 4 factors are fully arranged. There exists a class of experimental designs, named central composite designs (CCD), that considerably reduces the number of treatments required to estimate all the terms of a second-order polynomial equation without any loss of efficiency compared with the full factorial design. The objective of this technical note is to explain the construction of a CCD and its statistical analysis using the Statistical Analysis System. In short, a CCD consists of 2(k) treatment points (a first-order factorial design, where k represents the number of factors), augmented by at least one center point and 2 x k axial treatments. For 3 factors, the resulting design has 16 treatment points, compared with 27 for a full factorial design. For 4 factors, the CCD has 25 treatment points, compared with 81 for a full factorial design. The CCD can be made orthogonal (no correlation between parameter estimates) or rotatable (the variance of the estimated response is a function only of the distance from the design center and not the direction) by the location of the axial treatments. In spite of the reduced number of treatments compared with a full 3(k) factorial, the CCD is relatively efficient in estimation of the quadratic and interaction terms. Blocking of experimental units is often desirable and is sometimes required. Randomized block designs for CCD are found in some statistical design textbooks. The construction of incomplete, balanced (or near-balanced) designs for CCD experimental layouts is explained using an example. The Statistical Analysis System statements used to analyze a CCD, to identify the significant parameters in the polynomial equation, and to produce parameter estimates are presented and explained.

Defaunation studies have documented decreased ammonia concentrations associated with reduced microbial protein recycling and wastage of dietary protein, whereas many methods to suppress protozoa can reduce feed intake or depress ruminal organic matter or fiber digestibility. Therefore, more research is needed to optimize dietary conditions that improve protozoal growth and ruminal outflow relative to autolysis and recycling. Response in growth rate to ruminal outflow was simulated by abrupt changes in transfer interval of batch cultures, and substrate availability was evaluated by feeding without or with abrupt addition of monensin, which was postulated to inhibit digestive vacuole function. In experiment 1, Entodinium caudatum , a mix of Entodinium species, Epidinium caudatum , or Ophryoscolex caudatus cultures rapidly adjusted their generation times to approach respective changes in transfer interval from 3 to 2 or 1 d (cultures were always fed at 24-h intervals). Monensin (0.25μ M ) consistently delayed this response. To evaluate a metabolic upshift associated with feeding or a downshift associated with substrate depletion, experiment 2 used real-time PCR to quantify protozoal 18S rRNA gene (rDNA) copies that were expressed relative to cell numbers or to the cellular constituents N and nucleic acids after feeding without or with monensin (0.5μ M ). The 18S rDNA copies per milligram of nucleic acids were least for Ophryoscolex compared with the other cultures. When averaged over cultures (no culture×treatment interaction), 18S rDNA copies per unit of nucleic acids decreased at 16h when cultures were starved but increased with feeding unless monensin uncoupled availability of consumed substrate. Rumen protozoal growth increased in response to decreased transfer interval in experiment 1. Substrate availability appeared to initiate metabolic responses preparing for cell growth, explaining how cultures could rapidly adjust to decreasing transfer interval in experiment 2. Because feeding was not coupled with transfer in experiment 2, however, a metabolic control probably arrested cell division to prevent overgrowth relative to substrate availability.

The goal of commercial yellow perch aquaculture is to increase muscle mass which leads to increased profitability. The accumulation and degradation of muscle-specific gene products underlies the variability in body mass (BM) and length observed in pond-cultured yellow perch. Our objective was to apply a combination of statistical and proteomic technologies to identify intact and/or proteolytic fragments of muscle specific gene products involved in muscle growth in yellow perch. Seventy yellow perch randomly selected at 10, 12, 16, 20, and 26 wk of age were euthanized; BM and length were measured and a muscle sample taken. Muscle proteins were resolved using 5-20% gradient SDS-PAGE, stained with SYPRO ® Ruby and analyzed using TotalLab™ software. Data were analyzed using stepwise multiple regression with the dependent variables, BM and length and proportional OD of each band in a sample as a potential regressor. Eight bands associated with BM (R 2 = 0.84) and nine bands with length (R 2 = 0.85) were detected. Protein sequencing by nano-LC/MS/MS identified 20 proteins/peptides associated with BM and length. These results contribute the identification of gene products and/or proteolytic fragments associated with muscle growth in yellow perch.

Monitoring the nutritional composition of forage can be conceptualized as a quality control process that can be accomplished using control charts such as the Shewhart X-bar chart. A sampling schedule for an X-bar chart is defined by 3 parameters: the number of samples n taken at each sampling time, the sampling interval h, and the control limits L. All 3 parameters affect the performance of the chart, and thus, the total quality cost (TQC). A TQC function consists of cost per cycle while the process is in-control, cost per cycle while the process is out-of-control, cost per cycle for sampling and analyses, and the expected duration of a cycle, with a cycle defined as the time between the start of successive in-control periods. A general TQC function was derived for a renewal reward process. Optimization of this TQC function allows for the determination of the optimal n, h, and L values that minimize the total daily quality costs. The model assumes an abrupt change in composition of the forage when the process goes out-of-control. It also assumes a normal distribution of the measurements when the process is in-control and an absence of outlier measurements. The objective of this research was to evaluate model robustness to departure from these 3 basic assumptions. A series of Monte Carlo simulations was performed while varying the average time that the process is in control from 5 to 90 d using 1) errors of measurements that follow a standard normal distribution (SN); 2) SN with +/- 3.5 SD outliers inserted with a frequency of 1, 5, and 10%; 3) log normal error of measurements with SD = 1; and finally 4) SN with a gradual shift of the mean from 0 to 1.5 SD over 7, 14, and 28 d. The model was very robust to the presence of outliers; the average change in TQC was less than 1%, even with a frequency of outliers of 10%. The model is also very robust to asymmetry in the distribution of the measurements (i.e., probability distribution function with a long right tail): the log normal distribution, as opposed to the assumed normal, resulted in an increase in TQC of less than 1.4%. Finally, the gradual shift in mean composition did not result in an increased TQC but in a 17.3% decrease compared with an abrupt change. The model appears very robust to departure from normality, presence of outliers, and a skewed distribution of measurements. Gradual changes in the process are readily detected by the optimum X-bar chart with the conventional decision criterion, and monitoring performance is not markedly improved by augmenting the number of decision criteria in the X-bar chart or by the addition of a cumulative sum chart. Because of its robustness, the model can be applied to optimize forage sampling on dairy farms, with expected savings ranging between $80 and $100/cow per yr.

The typical cow has a maintenance requirement of about 10 Mcal of net energy for lactation (NEL) per day. Each kilogram of milk takes an additional 0.7 Mcal of NEL. Thus, the cow producing 45 kg of milk per day needs 4 times as much total energy as she needs for her maintenance requirement alone. The elite cow producing 90 kg/d needs 7 times as much total energy as she needs for maintenance alone. Consequently, the efficiency of using feed energy is much greater for the elite cow than it was for the cow of 100 yr ago consuming a diet of mostly forage. With increased productivity has come the need for fewer cows to produce milk on a per capita basis and increases in net income per cow. However, compared with energetic efficiency, the efficiency of using feed protein to make milk protein has not increased as dramatically, partly because cows are often fed protein in excess. This nitrogen waste is an environmental concern; N losses in manure contribute to water pollution and ammonia emissions from dairy farms. However, the complexities of protein nutrition and limitations in measuring feed N fractions make accurate specifications for feed protein fractions difficult. The economic risk of underfeeding protein is greater than the risk of overfeeding protein, so protein efficiency has not been maximized in the past, nor is it likely to be maximized in the near future. Most cows also are fed excess P, a notable contaminant of surface waters, but several recent studies have shown that feeding P above NRC recommendations has no utility for milk production or fertility. The goal of this article is to examine the impact of nutrition on productivity, efficiency, environmental sustainability, and profitability of the dairy industry.

The temporal expression of chicken skeletal fast myosin heavy chain (MyHC) isoforms in pectoralis major muscle was characterized in 3 commercial broiler lines at embryonic d 19 and at 7, 14, and 21 d posthatch. Lines A and B have been selected for breast yield, and line C is a fast' growing commercial line with limited selection for carcass traits. The isoform transitions in breast muscle samples were compared with samples from Single Comb White Leghorns (line D) using a semiquantitative immunoassay. The hypothesis was that selection for growth and carcass development in broilers would be accompanied by changes in the temporal expression of one or more of the chicken fast MyHC isoforms. Embryos from all lines were sampled at 19 d of incubation, and chicks were randomly sampled at 7, 14, and 21 d post-hatch. Myosin was extracted from pectoralis major muscle and assayed for purity and total protein concentration by SDS-PAGE and bincinchoninic acid protein analyses, respectively. The relative concentration of MyHC isoforms was evaluated by semiquantitative ELISA with 3 monoclonal antibodies specific for chicken skeletal fast embryonic and adult (eMyHC, aMyHC; EB165), neonatal (nMyHC; 2E9), and adult (aMyHC; AB8) myosin, respectively. The overall temporal expression of the myosin isoforms, eMyHC, nMyHC, and aMyHC, was similar in all lines. With eMyHC, at 19 d of incubation, line B had lower expression than lines A, C, and D. Expression of nMyHC, in lines C and D was similar with expression being highest at 7 d and lower at 14 d and 21 d. In lines A and B, however, nMyHC expression was higher at hatch than lines C and D. In line D, aMyHC was expressed at 14 d and increased through 21 d, whereas in lines A, B, and C, aMyHC isoform was expressed and was higher at 7 d and increased through 21 d. The results of this experiment support our hypothesis that commercial broilers have different temporal expression patterns of the developmental chicken fast MyHC isoforms.

Pelleting cottonseed (CS) improves handling characteristics. Our objectives were to determine whether increasing the particle size of the CS pellet or dilution of a smaller pellet with delinted CS would limit the rate of CS oil release to optimize digestibility of fatty acids (FA) and fiber while maintaining milk fat production. In a 5 x 5 Latin square design with 3-wk periods, 5 rumen-cannulated cows were fed 1) control with CS hulls (CSH) and CS meal plus tallow and Ca soaps of FA, 2) whole CS (WCS), 3) small CS pellets (SP; 0.44-cm die diameter), 4) larger CS pellets (LP; 0.52-cm die diameter), or 5) a blend of 1/2 SP plus 1/2 partially delinted CS (SPD). Diets contained 39.6% concentrate, 14.4% CS, and 46% forage (40:60, alfalfa hay:corn silage) on a DM basis and were balanced to have similar concentrations of CS protein, CS fiber, and total fat. In a production trial, dietary treatments were 1) WCS control, 2) LP, 3) SPD, and 4) SPD fed at 90%. Sixty cows averaging 105 d in milk were fed the WCS diet for 2 wk and then assigned to one of the 4 diets for 12 wk. Total tract digestibility of NDF was unaffected, but N digestibility was lower for SPD than for other treatments. Fatty acid digestibility was higher for SP and LP (82.6 and 82.3%) than for CSH or SPD treatments (78.8 and 75.3%), and WCS was intermediate (81.1%). The trans-11 C18:1 from cows fed SP and LP (6.58 and 6.24% of total milk FA) was greater than that from cows fed CSH, WCS, and SPD (3.23, 3.79, and 3.97%). The trans-10 C18:1 in milk fat from SP and LP (0.508 and 0.511%) was higher than that in WCS and SPD diets (0.316 and 0.295%); CSH was intermediate (0.429%). Using passage rates estimated from the NRC, disappearance of total FA in situ was estimated to be 17.7, 44.2, 46.6, and 35.0% for WCS, SP, LP, and SPD, respectively. In the production trial, a diet x week interaction was explained by a trend for progressively greater milk production for SPD and SPD90 than for WCS or LP. Milk fat was lower for LP (2.74%) and SPD90 (2.85%) than for WCS or SPD (3.07 and 3.08%). The fat yield was lower for LP than for SPD (1.09 and 1.30 kg/d); WCS and SPD90 were intermediate (1.23 and 1.21 kg/d). Although having a lower FA digestibility, SPD appeared to minimize negative effects of free oil from SP in the rumen, explaining higher DMI and milk production compared with WCS or LP.

Accurate estimates of manure excretion are needed for planning manure storage facilities and for nutrient management. Data sets from metabolism studies conducted at several universities were compiled and evaluated for excretion of total manure, N, P, and K. Animal groups included calves weighing up to 204 kg, heifers weighing between 274 and 613 kg, nonlactating cows, and lactating cows. Regression equations were developed to predict excretion of total manure, total dry matter, N, P, and K. Predictors used in the regression equations for lactating cows included milk yield, percentages of protein and fat in milk, dietary concentrations of crude protein and neutral detergent fiber, and intakes of nutrients. The regression equations provide improved predictions of excretion and enable more accurate planning of manure storage and nutrients to be managed at the farm level.

The esterification of 2-hydroxy-4-(methylthio)-butanoic acid (HMB) to isopropanol (HMBi) decreases the rate and extent of its ruminal breakdown. The modes of action of HMB and HMBi appear to be different. The quantification of the production response to HMBi has not been done. The objectives of this study were (1) to determine the lactation response to HMB, (2) to determine the lactation response to HMBi, and (3) to evaluate whether the response to HMBi is affected by HMB in the diet. Sixty-one Holstein cows (24 primiparous, 37 multiparous) were assigned to 1 of 4 dietary treatments 21 to 28 d after calving. The base diet consisted of [on a dry matter (DM) basis] 32.5% corn silage, 17.5% alfalfa hay, 10% whole cottonseed, and 40% of a pelleted concentrate made primarily of ground corn, soybean meal, and blood meal, and was fed for 16 wk as a control diet. To prepare the dietary treatments, the base diet was supplemented with 0.1% of diet DM with HMB (treatment 2), with 0.15% HMBi (treatment 3), or with 0.045% HMB and 0.15% HMBi (treatment 4). Results showed a significant increase in milk yield (2.9 kg/d), protein content (0.15%), protein yield (115 g/d), fat yield (165 g/d), and lactose yield (182 g/d) from HMBi. Supplementation of HMB had small and nonsignificant effects on milk yield and composition. There were no significant interaction effects of HMB with HMBi on any of the production traits measured in this experiment. Plasma free Met as a proportion of essential amino acids was increased by HMBi, but not by HMB. Dietary supplementation of HMBi increased gross N efficiency expressed as the proportion of ingested N secreted in milk. Consequently, HMBi significantly improved N efficiency.

The recovery of broiler chickens experiencing skeletal muscle myopathy caused by a selenium deficiency was compared with control broiler chickens in an age matched study by ultrastructural analysis of the pectoralis major (PM) muscle and examination of the temporal expression of the developmental fast skeletal myosin heavy chain (MyHC) isoforms. Selenium-deficient chicks showing signs of exudative diathesis (ED) were injected subcutaneously with sodium selenite in water and allowed to recover. At 0, 2, 5, 10, 20, and 30 d after selenium injection, a sample of the PM muscle was removed from selenium-deficient and control chicks for analysis. Ultrastructural analysis revealed vacuolization in the PM of selenium-deficient chicks with little or no visible damage to the sarcomere. Relative amounts of chicken ventricular, embryonic, neonatal, and adult fast skeletal MyHC isoforms were determined using chicken fast skeletal MyHC isoform specific monoclonal antibodies. The temporal expression of the developmental MyHC isoforms was similar in all chickens (P > 0.05). There was no expression of chicken ventricular MyHC observed in the PM of either group. These results indicate that chicken fast muscle recovering from exudative diathetic myopathy does not use the same pathways as chicken skeletal fast muscle regenerating from physical or toxic injury in which temporal expression of the MyHC isoforms is initially predominantly ventricular, then predominantly embryonic, neonatal, and finally predominantly adult developmental MyHC isoform.

Objectives were to quantify the ruminal effects and flows to the omasum of Met provided as 2-hydroxy-4-(methylthio)-butanoic acid (HMB), the isopropyl ester of HMB (HMBi), and DL-Met. Eight ruminally cannulated cows were used in a replicated 4 x 4 Latin square design. Treatments were 1) no Met (control), 2) HMB at 0.10% of DM, 3) HMBi at 0.13% of DM, and 4) DL-Met at 0.088% of DM. Diets were identical except for type of Met supplement and were based on corn silage and alfalfa hay at 30 and 13% of dietary DM, respectively. Samples of omasal fluid were used to determine the proportion of Met supplements passing out of the reticulorumen. Dry matter intake (20.1 kg/d) was restricted during the week of sampling to a maximum of 95% of ad libitum DMI determined during the first 2 wk of the period. Milk yields (37.7 +/- 0.8 kg/d) and fat concentration (3.42 +/- 0.15%) were not significantly different for control, HMB, HMBi, and DL-Met. Milk protein concentration (2.91, 2.95, 3.02, 2.96 +/- 0.07%, respectively) was significantly increased by the HMBi treatment. Rumen volatile fatty acids profile and NH3 concentrations were similar across treatments. Apparent ruminal digestibility of organic matter and neutral detergent fiber were higher for the three diets supplemented with Met sources than for the control diet. In situ rate of digestibility of CP from alfalfa hay, TMR, and corn silage was affected by Met sources. Passage rates of small particles (0.071/h) and fluid (0.167/h) were not affected by treatments. Protozoal counts in the rumen and omasum were not significantly affected by Met sources. Proportion of omasal N from bacterial N was not different (0.54 +/- 0.03), and bacterial N flow (305 +/- 24.4 g/d) was similar across treatments. The proportion of HMB that passed into the omasum was 5.3 +/- 1.5% of the amount consumed. Only a small amount (2.3%) of HMBi was found as HMB in the omasum. These results indicate that little HMB escapes ruminal degradation through passage to the omasum and that the site of HMBi absorption must be preomasal.

Nonregulatory feeding trials are used to determine the frequency and magnitude of response to a nutritional treatment, the odds of success, and factors that influence the odds and to provide an estimate of potential economic impact. These types of trials are not appropriate for elucidating mechanisms or modes of action. Correct experimental design is critical. Important factors that impact the validity of these trials are animal randomization, potential confounding with time, identification of the proper experimental unit, and adequate replication. Animals should be assigned to treatment without a systematic influence of environmental or physiological factors. The experimental design must account for and remove these influences. The experimental unit is the smallest entity to which the treatment can be applied randomly. In commercial settings, this is often a pen of animals. In a pen feeding situation, the experimental unit is the pen, although measurements may be taken on an individual animal basis. Frequency of data collection generally does not influence the treatment effect; however, it does influence the variance associated with the observations and the power to detect differences in treatments. Statistical methods that account for repeated observations over time are required when analyzing data with multiple observations on the same animal. Improper accounting for environmental changes over time is the most common error. Other errors include improper assignment of animals to treatment, failure to replicate the treatment across multiple experimental units, lack of on-farm oversight, and poor calibration of test equipment.

A survey was conducted to determine the importance of various location factors during the site selection process for relocating dairy farms. The objectives were to identify the importance of location decision factors (LDF) and characterize how importance differs among respondents with different demographic characteristics. Information was collected from sampled populations of Grade A milk producers in the top 35 milk-producing states in the United States and from U.S. agribusiness professionals using a mailed questionnaire. Location decision factors (n = 110) were rated on importance using a numerical scale of 0 to 10, where 0 = not important and 10 = critically important. Demographic data were collected from each respondent. Of 906 respondents, 72.4% identified their primary occupation as dairy producer. The five overall most important LDF were 1) availability of fresh water supplies (9.16 +/- 0.05); 2) availability of land for waste management (8.94 +/- 0.05); 3) average mailbox price of milk (8.79 +/- 0.05); 4) quality of fresh water supply (8.41 +/- 0.06); and 5) complexity of laws governing waste management (8.35 +/- 0.06). Factors pertaining to dairy production activities, such as cost of feeds and milk handling, were prevalent among those LDF in the upper quartile of importance. Region and herd size had significant effects on the overall importance of LDF. The relative importance of factors differed between western and eastern regions of the United States. Observed differences in importance of LDF among subclasses of respondents suggest that characteristics of the geographic regions evaluated and dairy production activities at various scales affect perceived importance of certain LDF.

Substantial increases in milk price volatility have resulted from changes in federal dairy policies. For a dairy farm, however, monthly gross milk receipts are a function of unit price and quantity produced. Both can vary substantially over time. Therefore, to be effective, risk management strategies must address milk and input price volatility (price risk management) and fluctuations in milk production per cow and cow numbers (production risk management). Herd milk production through time can be modeled as a discrete stochastic process using finite Markov chains. Cows at time t = 0 are assigned to homogeneous production cells in four-dimensional arrays with coordinates determined by parity (1, 2, 3), week in milk (1, ..., 104), pregnancy status (0, 1), and week pregnant (1, ..., 40). The processes of aging, pregnancy, involuntary cull, voluntary cull, abortion, dry-off, and freshening from week i-1 to week i are accounted for, using nonstationary transition probabilities. Bayesian estimates of transition probabilities are derived from historical herd data, assuming that individual outcomes are from Bernoulli distributions. The values of parameters theta(i) for the Bernoulli distributions are unknown but have prior distributions that follow beta distributions with parameters alpha(i) and beta(i) estimated from historical data. Herd observations are then used to generate posterior distributions of theta(i), also from beta distributions. Projecting from one week to the next is accomplished by moving virtual animals from one production cell to the next based on the transition probability assigned to that path. Summing production estimates and variances of all independent cells provides for an expected herd production with an associated variance. As expected, the forecast variance increases with time, reflecting increased uncertainty of distant projections. Model validation presents an interesting problem because future observations used for validation are under human control and are not independent of the forecast.

In animal agriculture, the need to understand complex biological, environmental, and management relationships is increasing. In addition, as knowledge increases and profit margins shrink, our ability and desire to predict responses to various management decisions also increases. Therefore, the purpose of this review is to help show how improved mathematical and statistical tools and computer technology can help us gain more accurate information from published studies and improve future research. Researchers, in several recent reviews, have gathered data from multiple published studies and attempted to formulate a quantitative model that best explains the observations. In statistics, this process has been labeled meta-analysis. Generally, there are large differences between studies: e. g., different physiological status of the experimental units, different experimental design, different measurement methods, and laboratory technicians. From a statistical standpoint, studies are blocks and their effects must be considered random because the inference being sought is to future, unknown studies. Meta-analyses in the animal sciences have generally ignored the Study effect. Because data gathered across studies are unbalanced with respect to predictor variables, ignoring the Study effect has as a consequence that the estimation of parameters (slopes and intercept) of regression models can be severely biased. Additionally, variance estimates are biased upward, resulting in large type II errors when testing the effect of independent variables. Historically, the Study effect has been considered a fixed effect not because of a strong argument that such effect is indeed fixed but because of our prior inability to efficiently solve even modest-sized mixed models (those containing both fixed and random effects). Modern statistical software has, however, overcome this limitation. Consequently, meta-analyses should now incorporate the Study effect and its interaction effects as random components of a mixed model. This would result in better prediction equations of biological systems and a more accurate description of their prediction errors.

The determinations of nutrient costs and breakeven prices of feedstuffs are important activities in the field of nutritional economics. Current methods are either extensions of the Petersen method, which dates back to 1932, or mathematical programming methods generally set as linear programming problems. Both sets of methods have severe limitations that make them unsuitable or biased for deriving unit costs of nutrients and aggregate breakeven costs of feedstuffs in a given market. We propose a least-squares method that, under verifiable conditions, yields maximum likelihood estimates of unit costs of nutrients and breakeven prices of feedstuffs. Assumptions to the maximum likelihood estimates are verified with studentized residuals, leverage values, and variance inflation factors. The method has been programmed into a Windows application and can be used by those with little formal training in statistics.

The objectives of this study were: 1) to evaluate the National Research Council equation used to predict microbial N flow to the duodenum in lactating cows, and 2) to determine whether improved equations could be developed by using dietary parameters used in the field. Treatment means from 55 trials with lactating and nonlactating cattle with duodenal cannulas were subjected to the backward elimination procedure of multiple regression. Variation within and among trials was accounted for by weighting the observations and including trial effects in all models. The equations to predict microbial N flow based on net energy for lactation (NE L ) intake were different from the equation based on NE L intake used by the dairy National Research Council. Dry matter intake (DMI) estimated microbial N flow as well as did NE L intake, indicating that DMI drives predictions based on NE L intake. When multiple dietary factors [i.e., DMI; dietary percentages of crude protein, forage, and neutral detergent fiber; and all two-way interactions] were included, the resulting equation [microbial N (grams per day) = 16.1 + 22.9 × DMI (kilograms per day) – 0.365 × DMI 2 – 1.74 × dietary neutral detergent fiber (percentage of dry matter)] tended to fit the data better than the equations based on NE L intake but not better than the equation based on DMI alone. The multiple-factor equation appeared to be the best overall equation for prediction; in contrast to the equation based on DMI, this equation is sensitive to diet composition. An asymptotic multiple-factor equation was developed, which may be more appropriate when extrapolating beyond the data range.

Carbohydrates are the major source of energy for dairy cows and for microbial protein synthesis in the rumen. The prediction of ruminal carbohydrate digestibility and of the flow of microbial protein to the small intestine is difficult because of the variability among various feeds in the kinetics of digestion and passage of neutral detergent fiber and starch. Disappearance of fiber and starch in vitro or in situ and gas production in vitro have been extensively evaluated, improved, and reviewed. Similarly, markers and models to measure ruminal passage rate have been extensively researched and improved. Sources of variation and decreased accuracy for these techniques are discussed. Variation and potential errors also remain for the prediction of microbial protein flow to the duodenum using in vivo procedures. However, when in vivo results were accumulated into a database, microbial N flow to the duodenum over a wide range of conditions could be predicted accurately by intake of net energy for lactation or by dry matter intake and percentage of neutral detergent fiber in the diet. Although evaluation of feeding interactions and specific dietary limitations for microbial protein production in the rumen are possible with some models but not with this regression approach, mechanistic models need further validation and more accurate rate constants for improved accuracy over a wide range of conditions.